diff --git a/asterixdb/asterix-doc/pom.xml b/asterixdb/asterix-doc/pom.xml index ea23f5e1464..8f21e7d1903 100644 --- a/asterixdb/asterix-doc/pom.xml +++ b/asterixdb/asterix-doc/pom.xml @@ -51,18 +51,6 @@ pre-site - - - - - - - - - - - - @@ -86,6 +74,13 @@ org.apache.maven.plugins maven-site-plugin + + + org.asciidoctor + asciidoctor-maven-plugin + 1.5.8 + + false diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc.md b/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc.md deleted file mode 100644 index c81c6563d08..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc.md +++ /dev/null @@ -1,20 +0,0 @@ - - -# Builtin Functions # diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc_aql.md b/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc_aql.md deleted file mode 100644 index f9e81dda059..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc_aql.md +++ /dev/null @@ -1,34 +0,0 @@ - - -## Table of Contents ## - -* [Numeric Functions](#NumericFunctions) -* [String Functions](#StringFunctions) -* [Binary Functions](#BinaryFunctions) -* [Spatial Functions](#SpatialFunctions) -* [Similarity Functions](#SimilarityFunctions) -* [Tokenizing Functions](#TokenizingFunctions) -* [Temporal Functions](#TemporalFunctions) -* [Object Functions](#ObjectFunctions) -* [Aggregate Functions (Array Functions)](#AggregateFunctions) -* [Comparison Functions](#ComparisonFunctions) -* [Type Functions](#TypeFunctions) -* [Conditional Functions](#ConditionalFunctions) -* [Miscellaneous Functions](#MiscFunctions) diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc_common.md b/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc_common.md deleted file mode 100644 index c1a97cb0089..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc_common.md +++ /dev/null @@ -1,21 +0,0 @@ - - -The system provides various classes of functions to support operations on numeric, string, spatial, and temporal data. -This document explains how to use these functions. diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc_sqlpp.md b/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc_sqlpp.md deleted file mode 100644 index 186916983c6..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/0_toc_sqlpp.md +++ /dev/null @@ -1,36 +0,0 @@ - - -## Table of Contents ## - -* [Numeric Functions](#NumericFunctions) -* [String Functions](#StringFunctions) -* [Binary Functions](#BinaryFunctions) -* [Spatial Functions](#SpatialFunctions) -* [Similarity Functions](#SimilarityFunctions) -* [Tokenizing Functions](#TokenizingFunctions) -* [Temporal Functions](#TemporalFunctions) -* [Object Functions](#ObjectFunctions) -* [Aggregate Functions (Array Functions)](#AggregateFunctions) -* [Comparison Functions](#ComparisonFunctions) -* [Type Functions](#TypeFunctions) -* [Conditional Functions](#ConditionalFunctions) -* [Miscellaneous Functions](#MiscFunctions) -* [Bitwise Functions](#BitwiseFunctions) -* [Window Functions](#WindowFunctions) diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/10_comparison.md b/asterixdb/asterix-doc/src/main/markdown/builtins/10_comparison.md deleted file mode 100644 index 9a1956653bb..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/10_comparison.md +++ /dev/null @@ -1,76 +0,0 @@ - - -## Comparison Functions ## - -### greatest ### - * Syntax: - - greatest(numeric_value1, numeric_value2, ...) - - * Computes the greatest value among arguments. - * Arguments: - * `numeric_value1`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value, - * `numeric_value2`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value, - * .... - * Return Value: - * the greatest values among arguments. - The returning type is decided by the item type with the highest - order in the numeric type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) - among items. - * `null` if any argument is a `missing` value or `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": greatest(1, 2, 3), "v2": greatest(float("0.5"), double("-0.5"), 5000) }; - - - * The expected result is: - - { "v1": 3, "v2": 5000.0 } - - -### least ### - * Syntax: - - least(numeric_value1, numeric_value2, ...) - - * Computes the least value among arguments. - * Arguments: - * `numeric_value1`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value, - * `numeric_value2`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value, - * .... - * Return Value: - * the least values among arguments. - The returning type is decided by the item type with the highest - order in the numeric type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) - among items. - * `null` if any argument is a `missing` value or `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": least(1, 2, 3), "v2": least(float("0.5"), double("-0.5"), 5000) }; - - - * The expected result is: - - { "v1": 1, "v2": -0.5 } - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/11_type.md b/asterixdb/asterix-doc/src/main/markdown/builtins/11_type.md deleted file mode 100644 index c9eab132b51..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/11_type.md +++ /dev/null @@ -1,554 +0,0 @@ - - -## Type Functions ## - -### is_array ### - * Syntax: - - is_array(expr) - - * Checks whether the given expression is evaluated to be an `array` value. - * Arguments: - * `expr` : an expression (any type is allowed). - * Return Value: - * a `boolean` on whether the argument is an `array` value or not, - * a `missing` if the argument is a `missing` value, - * a `null` if the argument is a `null` value. - - * Example: - - { - "a": is_array(true), - "b": is_array(false), - "c": isarray(null), - "d": isarray(missing), - "e": isarray("d"), - "f": isarray(4.0), - "g": isarray(5), - "h": isarray(["1", 2]), - "i": isarray({"a":1}) - }; - - - * The expected result is: - - { "a": false, "b": false, "c": null, "e": false, "f": false, "g": false, "h": true, "i": false } - - The function has an alias `isarray`. - -### is_atomic (is_atom) ### - * Syntax: - - is_atomic(expr) - - * Checks whether the given expression is evaluated to be a value of a [primitive](../datamodel.html#PrimitiveTypes) type. - * Arguments: - * `expr` : an expression (any type is allowed). - * Return Value: - * a `boolean` on whether the argument is a primitive type or not, - * a `missing` if the argument is a `missing` value, - * a `null` if the argument is a `null` value. - - * Example: - - { - "a": is_atomic(true), - "b": is_atomic(false), - "c": isatomic(null), - "d": isatomic(missing), - "e": isatomic("d"), - "f": isatom(4.0), - "g": isatom(5), - "h": isatom(["1", 2]), - "i": isatom({"a":1}) - }; - -* The expected result is: - - { "a": true, "b": true, "c": null, "e": true, "f": true, "g": true, "h": false, "i": false } - - The function has three aliases: `isatomic`, `is_atom`, and `isatom`. - -### is_boolean (is_bool) ### - * Syntax: - - is_boolean(expr) - - * Checks whether the given expression is evaluated to be a `boolean` value. - * Arguments: - * `expr` : an expression (any type is allowed). - * Return Value: - * a `boolean` on whether the argument is a `boolean` value or not, - * a `missing` if the argument is a `missing` value, - * a `null` if the argument is a `null` value. - - * Example: - - { - "a": isboolean(true), - "b": isboolean(false), - "c": is_boolean(null), - "d": is_boolean(missing), - "e": isbool("d"), - "f": isbool(4.0), - "g": isbool(5), - "h": isbool(["1", 2]), - "i": isbool({"a":1}) - }; - - - * The expected result is: - - { "a": true, "b": true, "c": null, "e": false, "f": false, "g": false, "h": false, "i": false } - - The function has three aliases: `isboolean`, `is_bool`, and `isbool`. - - -### is_number (is_num) ### - * Syntax: - - is_number(expr) - - * Checks whether the given expression is evaluated to be a numeric value. - * Arguments: - * `expr` : an expression (any type is allowed). - * Return Value: - * a `boolean` on whether the argument is a `smallint`/`tinyint`/`integer`/`bigint`/`float`/`double` - value or not, - * a `missing` if the argument is a `missing` value, - * a `null` if the argument is a `null` value. - - * Example: - - { - "a": is_number(true), - "b": is_number(false), - "c": isnumber(null), - "d": isnumber(missing), - "e": isnumber("d"), - "f": isnum(4.0), - "g": isnum(5), - "h": isnum(["1", 2]), - "i": isnum({"a":1}) - }; - - - * The expected result is: - - { "a": false, "b": false, "c": null, "e": false, "f": true, "g": true, "h": false, "i": false } - - The function has three aliases: `isnumber`, `is_num`, and `isnum`. - -### is_object (is_obj) ### - * Syntax: - - is_object(expr) - - * Checks whether the given expression is evaluated to be a `object` value. - * Arguments: - * `expr` : an expression (any type is allowed). - * Return Value: - * a `boolean` on whether the argument is a `object` value or not, - * a `missing` if the argument is a `missing` value, - * a `null` if the argument is a `null` value. - - * Example: - - { - "a": is_object(true), - "b": is_object(false), - "c": isobject(null), - "d": isobject(missing), - "e": isobj("d"), - "f": isobj(4.0), - "g": isobj(5), - "h": isobj(["1", 2]), - "i": isobj({"a":1}) - }; - - - * The expected result is: - - { "a": false, "b": false, "c": null, "e": false, "f": false, "g": false, "h": false, "i": true } - - The function has three aliases: `isobject`, `is_obj`, and `isobj`. - - -### is_string (is_str) ### - * Syntax: - - is_string(expr) - - * Checks whether the given expression is evaluated to be a `string` value. - * Arguments: - * `expr` : an expression (any type is allowed). - * Return Value: - * a `boolean` on whether the argument is a `string` value or not, - * a `missing` if the argument is a `missing` value, - * a `null` if the argument is a `null` value. - - * Example: - - { - "a": is_string(true), - "b": isstring(false), - "c": isstring(null), - "d": isstr(missing), - "e": isstr("d"), - "f": isstr(4.0), - "g": isstr(5), - "h": isstr(["1", 2]), - "i": isstr({"a":1}) - }; - - - * The expected result is: - - { "a": false, "b": false, "c": null, "e": true, "f": false, "g": false, "h": false, "i": false } - - The function has three aliases: `isstring`, `is_str`, and `isstr`. - - -### is_null ### - * Syntax: - - is_null(expr) - - * Checks whether the given expression is evaluated to be a `null` value. - * Arguments: - * `expr` : an expression (any type is allowed). - * Return Value: - * a `boolean` on whether the variable is a `null` or not, - * a `missing` if the input is `missing`. - - * Example: - - { "v1": is_null(null), "v2": is_null(1), "v3": is_null(missing) }; - - - * The expected result is: - - { "v1": true, "v2": false } - - The function has an alias `isnull`. - -### is_missing ### - * Syntax: - - is_missing(expr) - - * Checks whether the given expression is evaluated to be a `missing` value. - * Arguments: - * `expr` : an expression (any type is allowed). - * Return Value: - * a `boolean` on whether the variable is a `missing` or not. - - * Example: - - { "v1": is_missing(null), "v2": is_missing(1), "v3": is_missing(missing) }; - - - * The expected result is: - - { "v1": false, "v2": false, "v3": true } - - The function has an alias `ismissing`. - -### is_unknown ### - * Syntax: - - is_unknown(expr) - - * Checks whether the given variable is a `null` value or a `missing` value. - * Arguments: - * `expr` : an expression (any type is allowed). - * Return Value: - * a `boolean` on whether the variable is a `null`/``missing` value (`true`) or not (`false`). - - * Example: - - { "v1": is_unknown(null), "v2": is_unknown(1), "v3": is_unknown(missing) }; - - - * The expected result is: - - { "v1": true, "v2": false, "v3": true } - - The function has an alias `isunknown`. - -### to_array ### - * Syntax: - - to_array(expr) - - * Converts input value to an `array` value - * Arguments: - * `expr` : an expression - * Return Value: - * if the argument is `missing` then `missing` is returned - * if the argument is `null` then `null` is returned - * if the argument is of `array` type then it is returned as is - * if the argument is of `multiset` type then it is returned as an `array` with elements in an undefined order - * otherwise an `array` containing the input expression as its single item is returned - - * Example: - - { - "v1": to_array("asterix"), - "v2": to_array(["asterix"]), - }; - - * The expected result is: - - { "v1": ["asterix"], "v2": ["asterix"] } - - The function has an alias `toarray`. - -### to_atomic (to_atom) ### - * Syntax: - - to_atomic(expr) - - * Converts input value to a [primitive](../datamodel.html#PrimitiveTypes) value - * Arguments: - * `expr` : an expression - * Return Value: - * if the argument is `missing` then `missing` is returned - * if the argument is `null` then `null` is returned - * if the argument is of primitive type then it is returned as is - * if the argument is of `array` or `multiset` type and has only one element then the result of invoking - to_atomic() on that element is returned - * if the argument is of `object` type and has only one field then the result of invoking to_atomic() on the - value of that field is returned - * otherwise `null` is returned - - * Example: - - { - "v1": to_atomic("asterix"), - "v2": to_atomic(["asterix"]), - "v3": to_atomic([0, 1]), - "v4": to_atomic({"value": "asterix"}), - "v5": to_number({"x": 1, "y": 2}) - }; - - * The expected result is: - - { "v1": "asterix", "v2": "asterix", "v3": null, "v4": "asterix", "v5": null } - - The function has three aliases: `toatomic`, `to_atom`, and `toatom`. - -### to_boolean (to_bool) ### - * Syntax: - - to_boolean(expr) - - * Converts input value to a `boolean` value - * Arguments: - * `expr` : an expression - * Return Value: - * if the argument is `missing` then `missing` is returned - * if the argument is `null` then `null` is returned - * if the argument is of `boolean` type then it is returned as is - * if the argument is of numeric type then `false` is returned if it is `0` or `NaN`, otherwise `true` - * if the argument is of `string` type then `false` is returned if it's empty, otherwise `true` - * if the argument is of `array` or `multiset` type then `false` is returned if it's size is `0`, otherwise `true` - * if the argument is of `object` type then `false` is returned if it has no fields, otherwise `true` - * type error is raised for all other input types - - * Example: - - { - "v1": to_boolean(0), - "v2": to_boolean(1), - "v3": to_boolean(""), - "v4": to_boolean("asterix") - }; - - * The expected result is: - - { "v1": false, "v2": true, "v3": false, "v4": true } - - The function has three aliases: `toboolean`, `to_bool`, and `tobool`. - -### to_bigint ### - * Syntax: - - to_bigint(expr) - - * Converts input value to an integer value - * Arguments: - * `expr` : an expression - * Return Value: - * if the argument is `missing` then `missing` is returned - * if the argument is `null` then `null` is returned - * if the argument is of `boolean` type then `1` is returned if it is `true`, `0` if it is `false` - * if the argument is of numeric integer type then it is returned as the same value of `bigint` type - * if the argument is of numeric `float`/`double` type then it is converted to `bigint` type - * if the argument is of `string` type and can be parsed as integer then that integer value is returned, - otherwise `null` is returned - * if the argument is of `array`/`multiset`/`object` type then `null` is returned - * type error is raised for all other input types - - * Example: - - { - "v1": to_bigint(false), - "v2": to_bigint(true), - "v3": to_bigint(10), - "v4": to_bigint(float("1e100")), - "v5": to_bigint(double("1e1000")), - "v6": to_bigint("20") - }; - - * The expected result is: - - { "v1": 0, "v2": 1, "v3": 10, "v4": 9223372036854775807, "v5": 9223372036854775807, "v6": 20 } - - The function has an alias `tobigint`. - -### to_double ### - * Syntax: - - to_double(expr) - - * Converts input value to a `double` value - * Arguments: - * `expr` : an expression - * Return Value: - * if the argument is `missing` then `missing` is returned - * if the argument is `null` then `null` is returned - * if the argument is of `boolean` type then `1.0` is returned if it is `true`, `0.0` if it is `false` - * if the argument is of numeric type then it is returned as the value of `double` type - * if the argument is of `string` type and can be parsed as `double` then that `double` value is returned, - otherwise `null` is returned - * if the argument is of `array`/`multiset`/`object` type then `null` is returned - * type error is raised for all other input types - - * Example: - - { - "v1": to_double(false), - "v2": to_double(true), - "v3": to_double(10), - "v4": to_double(11.5), - "v5": to_double("12.5") - }; - - * The expected result is: - - { "v1": 0.0, "v2": 1.0, "v3": 10.0, "v4": 11.5, "v5": 12.5 } - - The function has an alias `todouble`. - -### to_number (to_num) ### - * Syntax: - - to_number(expr) - - * Converts input value to a numeric value - * Arguments: - * `expr` : an expression - * Return Value: - * if the argument is `missing` then `missing` is returned - * if the argument is `null` then `null` is returned - * if the argument is of numeric type then it is returned as is - * if the argument is of `boolean` type then `1` is returned if it is `true`, `0` if it is `false` - * if the argument is of `string` type and can be parsed as `bigint` then that `bigint` value is returned, - otherwise if it can be parsed as `double` then that `double` value is returned, - otherwise `null` is returned - * if the argument is of `array`/`multiset`/`object` type then `null` is returned - * type error is raised for all other input types - - * Example: - - { - "v1": to_number(false), - "v2": to_number(true), - "v3": to_number(10), - "v4": to_number(11.5), - "v5": to_number("12.5") - }; - - * The expected result is: - - { "v1": 0, "v2": 1, "v3": 10, "v4": 11.5, "v5": 12.5 } - - The function has three aliases: `tonumber`, `to_num`, and `tonum`. - -### to_object (to_obj) ### - * Syntax: - - to_object(expr) - - * Converts input value to an `object` value - * Arguments: - * `expr` : an expression - * Return Value: - * if the argument is `missing` then `missing` is returned - * if the argument is `null` then `null` is returned - * if the argument is of `object` type then it is returned as is - * otherwise an empty `object` is returned - - * Example: - - { - "v1": to_object({"value": "asterix"}), - "v2": to_object("asterix") - }; - - * The expected result is: - - { "v1": {"value": "asterix"}, "v2": {} } - - The function has three aliases: `toobject`, `to_obj`, and `toobj`. - -### to_string (to_str) ### - * Syntax: - - to_string(expr) - - * Converts input value to a string value - * Arguments: - * `expr` : an expression - * Return Value: - * if the argument is `missing` then `missing` is returned - * if the argument is `null` then `null` is returned - * if the argument is of `boolean` type then `"true"` is returned if it is `true`, `"false"` if it is `false` - * if the argument is of numeric type then its string representation is returned - * if the argument is of `string` type then it is returned as is - * if the argument is of `array`/`multiset`/`object` type then `null` is returned - * type error is raised for all other input types - - * Example: - - { - "v1": to_string(false), - "v2": to_string(true), - "v3": to_string(10), - "v4": to_string(11.5), - "v5": to_string("asterix") - }; - - * The expected result is: - - { "v1": "false", "v2": "true", "v3": "10", "v4": "11.5", "v5": "asterix" } - - The function has three aliases: `tostring`, `to_str`, and `tostr`. diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/12_misc.md b/asterixdb/asterix-doc/src/main/markdown/builtins/12_misc.md deleted file mode 100644 index df7cf8c40f2..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/12_misc.md +++ /dev/null @@ -1,206 +0,0 @@ - - -## Miscellaneous Functions ## - -### uuid ### - * Syntax: - - uuid() - -* Generates a `uuid`. -* Arguments: - * none -* Return Value: - * a generated, random `uuid`. - - -### len ### - * Syntax: - - len(array) - - * Returns the length of the array array. - * Arguments: - * `array` : an `array`, `multiset`, `null`, or `missing`, represents the collection that needs to be checked. - * Return Value: - * an `integer` that represents the length of input array or the size of the input multiset, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value. - - * Example: - - len(["Hello", "World"]) - - - * The expected result is: - - 2 - - -### not ### - * Syntax: - - not(expr) - - * Inverts a `boolean` value - * Arguments: - * `expr` : an expression - * Return Value: - * a `boolean`, the inverse of `expr`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * other non-boolean argument value will cause a type error. - * Example: - - { "v1": `not`(true), "v2": `not`(false), "v3": `not`(null), "v4": `not`(missing) }; - - * The expected result is: - - { "v1": false, "v2": true, "v3": null } - - -### random ### - * Syntax: - - random( [seed_value] ) - - * Returns a random number, accepting an optional seed value - * Arguments: - * `seed_value`: an optional `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value representing the seed number. - * Return Value: - * A random number of type `double` between 0 and 1, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value or a non-numeric value. - - * Example: - - { - "v1": random(), - "v2": random(unix_time_from_datetime_in_ms(current_datetime())) - }; - - -### range ### - * Syntax: - - range(start_numeric_value, end_numeric_value) - -* Generates a series of `bigint` values based start the `start_numeric_value` until the `end_numeric_value`. -* Arguments: - * `start_numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint` value representing the start value. - * `end_numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint` value representing the max final value. -* Return Value: - * an array that starts with the integer value of `start_numeric_value` and ends with - the integer value of `end_numeric_value`, where the value of each entry in the array is - the integer successor of the value in the preceding entry. -* Example: - - range(0, 3); - - * The expected result is: - - [ 0, 1, 2, 3 ] - - -### switch_case ### - * Syntax: - - switch_case( - condition, - case1, case1_result, - case2, case2_result, - ..., - default, default_result - ) - - * Switches amongst a sequence of cases and returns the result of the first matching case. If no match is found, the result of the default case is returned. - * Arguments: - * `condition`: a variable (any type is allowed). - * `caseI/default`: a variable (any type is allowed). - * `caseI/default_result`: a variable (any type is allowed). - * Return Value: - * `caseI_result` if `condition` matches `caseI`, otherwise `default_result`. - * Example 1: - - switch_case( - "a", - "a", 0, - "x", 1, - "y", 2, - "z", 3 - ); - - - * The expected result is: - - 0 - - * Example 2: - - switch_case( - "a", - "x", 1, - "y", 2, - "z", 3 - ); - - * The expected result is: - - 3 - - -### deep_equal ### -* Syntax: - - deep_equal(expr1, expr2) - - - * Assess the equality between two expressions of any type (e.g., object, arrays, or multiset). - Two objects are deeply equal iff both their types and values are equal. - * Arguments: - * `expr1` : an expression, - * `expr2` : an expression. - * Return Value: - * `true` or `false` depending on the data equality, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value. - - - * Example: - - deep_equal( - { - "id":1, - "project":"AsterixDB", - "address":{"city":"Irvine", "state":"CA"}, - "related":["Hivestrix", "Preglix", "Apache VXQuery"] - }, - { - "id":1, - "project":"AsterixDB", - "address":{"city":"San Diego", "state":"CA"}, - "related":["Hivestrix", "Preglix", "Apache VXQuery"] - } - ); - - * The expected result is: - - false - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/13_conditional.md b/asterixdb/asterix-doc/src/main/markdown/builtins/13_conditional.md deleted file mode 100644 index 8c2dce7a65e..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/13_conditional.md +++ /dev/null @@ -1,348 +0,0 @@ - - -## Conditional Functions ## - -### if_null (ifnull) ### - - * Syntax: - - if_null(expression1, expression2, ... expressionN) - - * Finds first argument which value is not `null` and returns that value - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * a `null` if all arguments evaluate to `null` or no arguments specified - * a value of the first non-`null` argument otherwise - - * Example: - - { - "a": if_null(), - "b": if_null(null), - "c": if_null(null, "asterixdb"), - "d": is_missing(if_null(missing)) - }; - - * The expected result is: - - { "a": null, "b": null, "c": "asterixdb", "d": true } - - The function has an alias `ifnull`. - -### if_missing (ifmissing) ### - - * Syntax: - - if_missing(expression1, expression2, ... expressionN) - - * Finds first argument which value is not `missing` and returns that value - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * a `null` if all arguments evaluate to `missing` or no arguments specified - * a value of the first non-`missing` argument otherwise - - * Example: - - { - "a": if_missing(), - "b": if_missing(missing), - "c": if_missing(missing, "asterixdb"), - "d": if_missing(null, "asterixdb") - }; - - * The expected result is: - - { "a": null, "b": null, "c": "asterixdb", "d": null } - - The function has an alias `ifmissing`. - -### if_missing_or_null (ifmissingornull, coalesce) ### - - * Syntax: - - if_missing_or_null(expression1, expression2, ... expressionN) - - * Finds first argument which value is not `null` or `missing` and returns that value - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * a `null` if all arguments evaluate to either `null` or `missing`, or no arguments specified - * a value of the first non-`null`, non-`missing` argument otherwise - -* Example: - - { - "a": if_missing_or_null(), - "b": if_missing_or_null(null, missing), - "c": if_missing_or_null(null, missing, "asterixdb") - }; - - * The expected result is: - - { "a": null, "b": null, "c": "asterixdb" } - - The function has two aliases: `ifmissingornull` and `coalesce`. - -### if_inf (ifinf) ### - - * Syntax: - - if_inf(expression1, expression2, ... expressionN) - - * Finds first argument which is a non-infinite (`INF` or`-INF`) number - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * a `missing` if `missing` argument was encountered before the first non-infinite number argument - * a `null` if `null` argument or any other non-number argument was encountered before the first non-infinite number argument - * the first non-infinite number argument otherwise - - * Example: - - { - "a": is_null(if_inf(null)), - "b": is_missing(if_inf(missing)), - "c": is_null(if_inf(double("INF"))), - "d": if_inf(1, null, missing) ], - "e": is_null(if_inf(null, missing, 1)) ], - "f": is_missing(if_inf(missing, null, 1)) ], - "g": if_inf(float("INF"), 1) ], - "h": to_string(if_inf(float("INF"), double("NaN"), 1)) ] - }; - - * The expected result is: - - { "a": true, "b": true, "c": true, "d": 1, "e": true, "f": true, "g": 1, "h": "NaN" } - - The function has an alias `ifinf`. - -### if_nan (ifnan) ### - - * Syntax: - - if_nan(expression1, expression2, ... expressionN) - - * Finds first argument which is a non-`NaN` number - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * a `missing` if `missing` argument was encountered before the first non-`NaN` number argument - * a `null` if `null` argument or any other non-number argument was encountered before the first non-`NaN` number argument - * the first non-`NaN` number argument otherwise - - * Example: - - { - "a": is_null(if_nan(null)), - "b": is_missing(if_nan(missing)), - "c": is_null(if_nan(double("NaN"))), - "d": if_nan(1, null, missing) ], - "e": is_null(if_nan(null, missing, 1)) ], - "f": is_missing(if_nan(missing, null, 1)) ], - "g": if_nan(float("NaN"), 1) ], - "h": to_string(if_nan(float("NaN"), double("INF"), 1)) ] - }; - - * The expected result is: - - { "a": true, "b": true, "c": true, "d": 1, "e": true, "f": true, "g": 1, "h": "INF" } - - The function has an alias `ifnan`. - -### if_nan_or_inf (ifnanorinf) ### - - * Syntax: - - if_nan_or_inf(expression1, expression2, ... expressionN) - - * Finds first argument which is a non-infinite (`INF` or`-INF`) and non-`NaN` number - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * a `missing` if `missing` argument was encountered before the first non-infinite and non-`NaN` number argument - * a `null` if `null` argument or any other non-number argument was encountered before the first non-infinite and non-`NaN` number argument - * the first non-infinite and non-`NaN` number argument otherwise - - * Example: - - { - "a": is_null(if_nan_or_inf(null)), - "b": is_missing(if_nan_or_inf(missing)), - "c": is_null(if_nan_or_inf(double("NaN"), double("INF"))), - "d": if_nan_or_inf(1, null, missing) ], - "e": is_null(if_nan_or_inf(null, missing, 1)) ], - "f": is_missing(if_nan_or_inf(missing, null, 1)) ], - "g": if_nan_or_inf(float("NaN"), float("INF"), 1) ], - }; - - * The expected result is: - - { "a": true, "b": true, "c": true, "d": 1, "e": true, "f": true, "g": 1 } - - The function has an alias `ifnanorinf`. - - -### null_if (nullif) ### - - * Syntax: - - null_if(expression1, expression2) - - * Compares two arguments and returns `null` if they are equal, otherwise returns the first argument. - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * `missing` if any argument is a `missing` value, - * `null` if - * any argument is a `null` value but no argument is a `missing` value, or - * `argument1` = `argument2` - * a value of the first argument otherwise - - * Example: - - { - "a": null_if("asterixdb", "asterixdb"), - "b": null_if(1, 2) - }; - - * The expected result is: - - { "a": null, "b": 1 } - - The function has an alias `nullif`. - - -### missing_if (missingif) ### - - * Syntax: - - missing_if(expression1, expression2) - - * Compares two arguments and returns `missing` if they are equal, otherwise returns the first argument. - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * `missing` if - * any argument is a `missing` value, or - * no argument is a `null` value and `argument1` = `argument2` - * `null` if any argument is a `null` value but no argument is a `missing` value - * a value of the first argument otherwise - - * Example: - - { - "a": missing_if("asterixdb", "asterixdb") - "b": missing_if(1, 2), - }; - - * The expected result is: - - { "b": 1 } - - The function has an alias `missingif`. - - -### nan_if (nanif) ### - - * Syntax: - - nan_if(expression1, expression2) - - * Compares two arguments and returns `NaN` value if they are equal, otherwise returns the first argument. - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value - * `NaN` value of type `double` if `argument1` = `argument2` - * a value of the first argument otherwise - - * Example: - - { - "a": to_string(nan_if("asterixdb", "asterixdb")), - "b": nan_if(1, 2) - }; - - * The expected result is: - - { "a": "NaN", "b": 1 } - - The function has an alias `nanif`. - - -### posinf_if (posinfif) ### - - * Syntax: - - posinf_if(expression1, expression2) - - * Compares two arguments and returns `+INF` value if they are equal, otherwise returns the first argument. - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value - * `+INF` value of type `double` if `argument1` = `argument2` - * a value of the first argument otherwise - - * Example: - - { - "a": to_string(posinf_if("asterixdb", "asterixdb")), - "b": posinf_if(1, 2) - }; - - * The expected result is: - - { "a": "+INF", "b": 1 } - - The function has an alias `posinfif`. - - -### neginf_if (neginfif) ### - - * Syntax: - - neginf_if(expression1, expression2) - - * Compares two arguments and returns `-INF` value if they are equal, otherwise returns the first argument. - * Arguments: - * `expressionI` : an expression (any type is allowed). - * Return Value: - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value - * `-INF` value of type `double` if `argument1` = `argument2` - * a value of the first argument otherwise - - * Example: - - { - "a": to_string(neginf_if("asterixdb", "asterixdb")), - "b": neginf_if(1, 2) - }; - - * The expected result is: - - { "a": "-INF", "b": 1 } - - The function has an alias `neginfif`. diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/14_window.md b/asterixdb/asterix-doc/src/main/markdown/builtins/14_window.md deleted file mode 100644 index d88d5e82027..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/14_window.md +++ /dev/null @@ -1,1325 +0,0 @@ - - -## Window Functions ## - -Window functions are used to compute an aggregate or cumulative value, based on -a portion of the tuples selected by a query. -For each input tuple, a movable window of tuples is defined. -The window determines the tuples to be used by the window function. - -The tuples are not grouped into a single output tuple — each tuple remains -separate in the query output. - -All window functions must be used with an OVER clause. -Refer to [OVER Clauses](manual.html#Over_clauses) for details. - -Window functions cannot appear in the FROM clause clause or LIMIT clause. - -The examples in this section use the `GleambookMessages` dataset, -described in the section on [SELECT Statements](manual.html#SELECT_statements). - -### cume_dist ### - -* Syntax: - - CUME_DIST() OVER ([window-partition-clause] [window-order-clause]) - -* Returns the percentile rank of the current tuple as part of the cumulative - distribution – that is, the number of tuples ranked lower than or equal to - the current tuple, including the current tuple, divided by the total number - of tuples in the window partition. - - The window order clause determines the sort order of the tuples. - If the window order clause is omitted, the function returns the same - result (1.0) for each tuple. - -* Arguments: - - * None. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - -* Return Value: - - * A number greater than 0 and less than or equal to 1. - The higher the value, the higher the ranking. - -* Example: - - For each author, find the cumulative distribution of all messages - in order of message ID. - - SELECT m.messageId, m.authorId, CUME_DIST() OVER ( - PARTITION BY m.authorId - ORDER BY m.messageId - ) AS `rank` - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "rank": 0.2, - "messageId": 2, - "authorId": 1 - }, - { - "rank": 0.4, - "messageId": 4, - "authorId": 1 - }, - { - "rank": 0.6, - "messageId": 8, - "authorId": 1 - }, - { - "rank": 0.8, - "messageId": 10, - "authorId": 1 - }, - { - "rank": 1, - "messageId": 11, - "authorId": 1 - }, - { - "rank": 0.5, - "messageId": 3, - "authorId": 2 - }, - { - "rank": 1, - "messageId": 6, - "authorId": 2 - } - ] - -### dense_rank ### - -* Syntax: - - DENSE_RANK() OVER ([window-partition-clause] [window-order-clause]) - -* Returns the dense rank of the current tuple – that is, the number of - distinct tuples preceding this tuple in the current window partition, plus - one. - - The tuples are ordered by the window order clause. - If any tuples are tied, they will have the same rank. - If the window order clause is omitted, the function returns the same - result (1) for each tuple. - - For this function, when any tuples have the same rank, the rank of the next - tuple will be consecutive, so there will not be a gap in the sequence of - returned values. - For example, if there are three tuples ranked 2, the next dense rank is 3. - -* Arguments: - - * None. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - -* Return Value: - - * An integer, greater than or equal to 1. - -* Example: - - For each author, find the dense rank of all messages in order of location. - - SELECT m.authorId, m.messageId, m.senderLocation[1] as longitude, - DENSE_RANK() OVER ( - PARTITION BY m.authorId - ORDER BY m.senderLocation[1] - ) AS `rank` - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "rank": 1, - "authorId": 1, - "messageId": 10, - "longitude": 70.01 - }, - { - "rank": 2, - "authorId": 1, - "messageId": 11, - "longitude": 77.49 - }, - { - "rank": 3, - "authorId": 1, - "messageId": 2, - "longitude": 80.87 - }, - { - "rank": 3, - "authorId": 1, - "messageId": 8, - "longitude": 80.87 - }, - { - "rank": 4, - "authorId": 1, - "messageId": 4, - "longitude": 97.04 - }, - { - "rank": 1, - "authorId": 2, - "messageId": 6, - "longitude": 75.56 - }, - { - "rank": 2, - "authorId": 2, - "messageId": 3, - "longitude": 81.01 - } - ] - -### first_value ### - -* Syntax: - - FIRST_VALUE(expr) [nulls-treatment] OVER (window-definition) - -* Returns the requested value from the first tuple in the current window - frame, where the window frame is specified by the window definition. - -* Arguments: - - * `expr`: The value that you want to return from the first - tuple in the window frame. \[[1](#fn_1)\] - -* Modifiers: - - * [Nulls Treatment](manual.html#Nulls_treatment): (Optional) Determines how - NULL or MISSING values are treated when finding the first value in the - window frame. - - - `IGNORE NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are ignored when finding the first tuple. - In this case, the function returns the first non-NULL, non-MISSING - value. - - - `RESPECT NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are included when finding the first tuple. - - If this modifier is omitted, the default is `RESPECT NULLS`. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - - * (Optional) [Window Frame Clause](manual.html#Window_frame_clause). - -* Return Value: - - * The specified value from the first tuple. - The order of the tuples is determined by the window order clause. - - * NULL, if the frame was empty or if all values were NULL or MISSING and - the `IGNORE NULLS` modifier was specified. - - * In the following cases, this function may return unpredictable results. - - - If the window order clause is omitted. - - - If the window frame is defined by `ROWS`, and there are tied tuples - in the window frame. - - * To make the function return deterministic results, add a window order - clause, or add further ordering terms to the window order clause so that - no tuples are tied. - - * If the window frame is defined by `RANGE` or `GROUPS`, and there are - tied tuples in the window frame, the function returns the first value - of the input expression. - -* Example: - - For each author, show the length of each message, including the - length of the shortest message from that author. - - SELECT m.authorId, m.messageId, - LENGTH(m.message) AS message_length, - FIRST_VALUE(LENGTH(m.message)) OVER ( - PARTITION BY m.authorId - ORDER BY LENGTH(m.message) - ) AS shortest_message - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "message_length": 31, - "shortest_message": 31, - "authorId": 1, - "messageId": 8 - }, - { - "message_length": 39, - "shortest_message": 31, - "authorId": 1, - "messageId": 11 - }, - { - "message_length": 44, - "shortest_message": 31, - "authorId": 1, - "messageId": 4 - }, - { - "message_length": 45, - "shortest_message": 31, - "authorId": 1, - "messageId": 2 - }, - { - "message_length": 51, - "shortest_message": 31, - "authorId": 1, - "messageId": 10 - }, - { - "message_length": 35, - "shortest_message": 35, - "authorId": 2, - "messageId": 3 - }, - { - "message_length": 44, - "shortest_message": 35, - "authorId": 2, - "messageId": 6 - } - ] - -### lag ### - -* Syntax: - - LAG(expr[, offset[, default]]) [nulls-treatment] OVER ([window-partition-clause] [window-order-clause]) - -* Returns the value from a tuple at a given offset prior to the current tuple - position. - - The window order clause determines the sort order of the tuples. - If the window order clause is omitted, the return values may be - unpredictable. - -* Arguments: - - * `expr`: The value that you want to return from the offset - tuple. \[[1](#fn_1)\] - - * `offset`: (Optional) A positive integer. - If omitted, the default is 1. - - * `default`: (Optional) The value to return when the offset goes out of - partition scope. - If omitted, the default is NULL. - -* Modifiers: - - * [Nulls Treatment](manual.html#Nulls_treatment): (Optional) Determines how - NULL or MISSING values are treated when finding the offset tuple in the - window partition. - - - `IGNORE NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are ignored when finding the offset tuple. - - - `RESPECT NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are included when finding the offset tuple. - - If this modifier is omitted, the default is `RESPECT NULLS`. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - -* Return Value: - - * The specified value from the offset tuple. - - * If the offset tuple is out of partition scope, it returns the default value, - or NULL if no default is specified. - -* Example: - - For each author, show the length of each message, including the - length of the next-shortest message. - - SELECT m.authorId, m.messageId, - LENGTH(m.message) AS message_length, - LAG(LENGTH(m.message), 1, "No shorter message") OVER ( - PARTITION BY m.authorId - ORDER BY LENGTH(m.message) - ) AS next_shortest_message - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "message_length": 31, - "authorId": 1, - "messageId": 8, - "next_shortest_message": "No shorter message" - }, - { - "message_length": 39, - "authorId": 1, - "messageId": 11, - "next_shortest_message": 31 - }, - { - "message_length": 44, - "authorId": 1, - "messageId": 4, - "next_shortest_message": 39 - }, - { - "message_length": 45, - "authorId": 1, - "messageId": 2, - "next_shortest_message": 44 - }, - { - "message_length": 51, - "authorId": 1, - "messageId": 10, - "next_shortest_message": 45 - }, - { - "message_length": 35, - "authorId": 2, - "messageId": 3, - "next_shortest_message": "No shorter message" - }, - { - "message_length": 44, - "authorId": 2, - "messageId": 6, - "next_shortest_message": 35 - } - ] - -### last_value ### - -* Syntax: - - LAST_VALUE(expr) [nulls-treatment] OVER (window-definition) - -* Returns the requested value from the last tuple in the current window frame, - where the window frame is specified by the window definition. - -* Arguments: - - * `expr`: The value that you want to return from the last tuple - in the window frame. \[[1](#fn_1)\] - -* Modifiers: - - * [Nulls Treatment](manual.html#Nulls_treatment): (Optional) Determines how - NULL or MISSING values are treated when finding the last tuple in the - window frame. - - - `IGNORE NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are ignored when finding the last tuple. - In this case, the function returns the last non-NULL, non-MISSING - value. - - - `RESPECT NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are included when finding the last tuple. - - If this modifier is omitted, the default is `RESPECT NULLS`. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - - * (Optional) [Window Frame Clause](manual.html#Window_frame_clause). - -* Return Value: - - * The specified value from the last tuple. - The order of the tuples is determined by the window order clause. - - * NULL, if the frame was empty or if all values were NULL or MISSING and - the `IGNORE NULLS` modifier was specified. - - * In the following cases, this function may return unpredictable results. - - - If the window order clause is omitted. - - - If the window frame clause is omitted. - - - If the window frame is defined by `ROWS`, and there are tied tuples - in the window frame. - - * To make the function return deterministic results, add a window order - clause, or add further ordering terms to the window order clause so that - no tuples are tied. - - * If the window frame is defined by `RANGE` or `GROUPS`, and there are - tied tuples in the window frame, the function returns the last - value of the input expression. - -* Example: - - For each author, show the length of each message, including the - length of the longest message from that author. - - SELECT m.authorId, m.messageId, - LENGTH(m.message) AS message_length, - LAST_VALUE(LENGTH(m.message)) OVER ( - PARTITION BY m.authorId - ORDER BY LENGTH(m.message) - ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING -- ➊ - ) AS longest_message - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "message_length": 31, - "longest_message": 51, - "authorId": 1, - "messageId": 8 - }, - { - "message_length": 39, - "longest_message": 51, - "authorId": 1, - "messageId": 11 - }, - { - "message_length": 44, - "longest_message": 51, - "authorId": 1, - "messageId": 4 - }, - { - "message_length": 45, - "longest_message": 51, - "authorId": 1, - "messageId": 2 - }, - { - "message_length": 51, - "longest_message": 51, - "authorId": 1, - "messageId": 10 - }, - { - "message_length": 35, - "longest_message": 44, - "authorId": 2, - "messageId": 3 - }, - { - "message_length": 44, - "longest_message": 44, - "authorId": 2, - "messageId": 6 - } - ] - - ➀ This clause specifies that the window frame should extend to the - end of the window partition. - Without this clause, the end point of the window frame would always be the - current tuple. - This would mean that the longest message would always be the same as the - current message. - -### lead ### - -* Syntax: - - LEAD(expr[, offset[, default]]) [nulls-treatment] OVER ([window-partition-clause] [window-order-clause]) - -* Returns the value from a tuple at a given offset ahead of the current tuple - position. - - The window order clause determines the sort order of the tuples. - If the window order clause is omitted, the return values may be - unpredictable. - -* Arguments: - - * `expr`: The value that you want to return from the offset - tuple. \[[1](#fn_1)\] - - * `offset`: (Optional) A positive integer. If omitted, the - default is 1. - - * `default`: (Optional) The value to return when the offset goes out of - window partition scope. - If omitted, the default is NULL. - -* Modifiers: - - * [Nulls Treatment](manual.html#Nulls_treatment): (Optional) Determines how - NULL or MISSING values are treated when finding the offset tuple in the - window partition. - - - `IGNORE NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are ignored when finding the offset tuple. - - - `RESPECT NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are included when finding the offset tuple. - - If this modifier is omitted, the default is `RESPECT NULLS`. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - -* Return Value: - - * The specified value from the offset tuple. - - * If the offset tuple is out of partition scope, it returns the default value, or - NULL if no default is specified. - -* Example: - - For each author, show the length of each message, including the - length of the next-longest message. - - SELECT m.authorId, m.messageId, - LENGTH(m.message) AS message_length, - LEAD(LENGTH(m.message), 1, "No longer message") OVER ( - PARTITION BY m.authorId - ORDER BY LENGTH(m.message) - ) AS next_longest_message - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "message_length": 31, - "authorId": 1, - "messageId": 8, - "next_longest_message": 39 - }, - { - "message_length": 39, - "authorId": 1, - "messageId": 11, - "next_longest_message": 44 - }, - { - "message_length": 44, - "authorId": 1, - "messageId": 4, - "next_longest_message": 45 - }, - { - "message_length": 45, - "authorId": 1, - "messageId": 2, - "next_longest_message": 51 - }, - { - "message_length": 51, - "authorId": 1, - "messageId": 10, - "next_longest_message": "No longer message" - }, - { - "message_length": 35, - "authorId": 2, - "messageId": 3, - "next_longest_message": 44 - }, - { - "message_length": 44, - "authorId": 2, - "messageId": 6, - "next_longest_message": "No longer message" - } - ] - -### nth_value ### - -* Syntax: - - NTH_VALUE(expr, offset) [nthval-from] [nulls-treatment] OVER (window-definition) - -* Returns the requested value from a tuple in the current window frame, where - the window frame is specified by the window definition. - -* Arguments: - - * `expr`: The value that you want to return from the offset - tuple in the window frame. \[[1](#fn_1)\] - - * `offset`: The number of the offset tuple within the window - frame, counting from 1. - -* Modifiers: - - * [Nth Val From](manual.html#Nth_val_from): (Optional) Determines where the - function starts counting the offset. - - - `FROM FIRST`: Counting starts at the first tuple in the window frame. - In this case, an offset of 1 is the first tuple in the window frame, - 2 is the second tuple, and so on. - - - `FROM LAST`: Counting starts at the last tuple in the window frame. - In this case, an offset of 1 is the last tuple in the window frame, - 2 is the second-to-last tuple, and so on. - - The order of the tuples is determined by the window order clause. - If this modifier is omitted, the default is `FROM FIRST`. - - * [Nulls Treatment](manual.html#Nulls_treatment): (Optional) Determines how - NULL or MISSING values are treated when finding the offset tuple in the - window frame. - - - `IGNORE NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are ignored when finding the offset tuple. - - - `RESPECT NULLS`: If the values for any tuples evaluate to NULL or - MISSING, those tuples are included when finding the offset tuple. - - If this modifier is omitted, the default is `RESPECT NULLS`. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - - * (Optional) [Window Frame Clause](manual.html#Window_frame_clause). - -* Return Value: - - * The specified value from the offset tuple. - - * In the following cases, this function may return unpredictable results. - - - If the window order clause is omitted. - - - If the window frame is defined by `ROWS`, and there are tied tuples - in the window frame. - - * To make the function return deterministic results, add a window order - clause, or add further ordering terms to the window order clause so that - no tuples are tied. - - * If the window frame is defined by `RANGE` or `GROUPS`, and there are - tied tuples in the window frame, the function returns the first value - of the input expression when counting `FROM FIRST`, or the last - value of the input expression when counting `FROM LAST`. - -* Example 1: - - For each author, show the length of each message, including the - length of the second shortest message from that author. - - SELECT m.authorId, m.messageId, - LENGTH(m.message) AS message_length, - NTH_VALUE(LENGTH(m.message), 2) FROM FIRST OVER ( - PARTITION BY m.authorId - ORDER BY LENGTH(m.message) - ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING -- ➊ - ) AS shortest_message_but_1 - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "message_length": 31, - "shortest_message_but_1": 39, - "authorId": 1, - "messageId": 8 - }, - { - "message_length": 39, - "shortest_message_but_1": 39, - "authorId": 1, - "messageId": 11 // ➋ - }, - { - "message_length": 44, - "shortest_message_but_1": 39, - "authorId": 1, - "messageId": 4 - }, - { - "message_length": 45, - "shortest_message_but_1": 39, - "authorId": 1, - "messageId": 2 - }, - { - "message_length": 51, - "shortest_message_but_1": 39, - "authorId": 1, - "messageId": 10 - }, - { - "message_length": 35, - "shortest_message_but_1": 44, - "authorId": 2, - "messageId": 3 - }, - { - "message_length": 44, - "shortest_message_but_1": 44, - "authorId": 2, - "messageId": 6 // ➋ - } - ] - - ➀ This clause specifies that the window frame should extend to the - end of the window partition. - Without this clause, the end point of the window frame would always be the - current tuple. - This would mean that for the shortest message, the function - would be unable to find the route with the second shortest message. - - ➁ The second shortest message from this author. - -* Example 2: - - For each author, show the length of each message, including the - length of the second longest message from that author. - - SELECT m.authorId, m.messageId, - LENGTH(m.message) AS message_length, - NTH_VALUE(LENGTH(m.message), 2) FROM LAST OVER ( - PARTITION BY m.authorId - ORDER BY LENGTH(m.message) - ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING -- ➊ - ) AS longest_message_but_1 - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "message_length": 31, - "longest_message_but_1": 45, - "authorId": 1, - "messageId": 8 - }, - { - "message_length": 39, - "longest_message_but_1": 45, - "authorId": 1, - "messageId": 11 - }, - { - "message_length": 44, - "longest_message_but_1": 45, - "authorId": 1, - "messageId": 4 - }, - { - "message_length": 45, - "longest_message_but_1": 45, - "authorId": 1, - "messageId": 2 // ➋ - }, - { - "message_length": 51, - "longest_message_but_1": 45, - "authorId": 1, - "messageId": 10 - }, - { - "message_length": 35, - "longest_message_but_1": 35, - "authorId": 2, - "messageId": 3 // ➋ - }, - { - "message_length": 44, - "longest_message_but_1": 35, - "authorId": 2, - "messageId": 6 - } - ] - - ➀ This clause specifies that the window frame should extend to the - end of the window partition. - Without this clause, the end point of the window frame would always be the - current tuple. - This would mean the function would be unable to find the second longest - message for shorter messages. - - ➁ The second longest message from this author. - -### ntile ### - -* Syntax: - - NTILE(num_tiles) OVER ([window-partition-clause] [window-order-clause]) - -* Divides the window partition into the specified number of tiles, and - allocates each tuple in the window partition to a tile, so that as far as - possible each tile has an equal number of tuples. - When the set of tuples is not equally divisible by the number of tiles, the - function puts more tuples into the lower-numbered tiles. - For each tuple, the function returns the number of the tile into which that - tuple was placed. - - The window order clause determines the sort order of the tuples. - If the window order clause is omitted then the tuples are processed in - an undefined order. - -* Arguments: - - * `num_tiles`: The number of tiles into which you want to divide - the window partition. - This argument can be an expression and must evaluate to a number. - If the number is not an integer, it will be truncated. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - -* Return Value: - - * An value greater than or equal to 1 and less than or equal to the number - of tiles. - -* Example: - - Allocate each message to one of three tiles by length and message ID. - - SELECT m.messageId, LENGTH(m.message) AS `length`, - NTILE(3) OVER ( - ORDER BY LENGTH(m.message), m.messageId - ) AS `ntile` - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "length": 31, - "ntile": 1, - "messageId": 8 - }, - { - "length": 35, - "ntile": 1, - "messageId": 3 - }, - { - "length": 39, - "ntile": 1, - "messageId": 11 - }, - { - "length": 44, - "ntile": 2, - "messageId": 4 - }, - { - "length": 44, - "ntile": 2, - "messageId": 6 - }, - { - "length": 45, - "ntile": 3, - "messageId": 2 - }, - { - "length": 51, - "ntile": 3, - "messageId": 10 - } - ] - -### percent_rank ### - -* Syntax: - - PERCENT_RANK() OVER ([window-partition-clause] [window-order-clause]) - -* Returns the percentile rank of the current tuple – that is, the rank of the - tuples minus one, divided by the total number of tuples in the window - partition minus one. - - The window order clause determines the sort order of the tuples. - If the window order clause is omitted, the function returns the same - result (0) for each tuple. - -* Arguments: - - * None. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - -* Return Value: - - * A number between 0 and 1. - The higher the value, the higher the ranking. - -* Example: - - For each author, find the percentile rank of all messages in order - of message ID. - - SELECT m.messageId, m.authorId, PERCENT_RANK() OVER ( - PARTITION BY m.authorId - ORDER BY m.messageId - ) AS `rank` - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "rank": 0, - "messageId": 2, - "authorId": 1 - }, - { - "rank": 0.25, - "messageId": 4, - "authorId": 1 - }, - { - "rank": 0.5, - "messageId": 8, - "authorId": 1 - }, - { - "rank": 0.75, - "messageId": 10, - "authorId": 1 - }, - { - "rank": 1, - "messageId": 11, - "authorId": 1 - }, - { - "rank": 0, - "messageId": 3, - "authorId": 2 - }, - { - "rank": 1, - "messageId": 6, - "authorId": 2 - } - ] - -### rank ### - -* Syntax: - - RANK() OVER ([window-partition-clause] [window-order-clause]) - -* Returns the rank of the current tuple – that is, the number of distinct - tuples preceding this tuple in the current window partition, plus one. - - The tuples are ordered by the window order clause. - If any tuples are tied, they will have the same rank. - If the window order clause is omitted, the function returns the same - result (1) for each tuple. - - When any tuples have the same rank, the rank of the next tuple will include - all preceding tuples, so there may be a gap in the sequence of returned - values. - For example, if there are three tuples ranked 2, the next rank is 5. - - To avoid gaps in the returned values, use the DENSE_RANK() function instead. - -* Arguments: - - * None. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - -* Return Value: - - * An integer, greater than or equal to 1. - -* Example: - - For each author, find the rank of all messages in order of location. - - SELECT m.authorId, m.messageId, m.senderLocation[1] as longitude, - RANK() OVER ( - PARTITION BY m.authorId - ORDER BY m.senderLocation[1] - ) AS `rank` - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "rank": 1, - "authorId": 1, - "messageId": 10, - "longitude": 70.01 - }, - { - "rank": 2, - "authorId": 1, - "messageId": 11, - "longitude": 77.49 - }, - { - "rank": 3, - "authorId": 1, - "messageId": 2, - "longitude": 80.87 - }, - { - "rank": 3, - "authorId": 1, - "messageId": 8, - "longitude": 80.87 - }, - { - "rank": 5, - "authorId": 1, - "messageId": 4, - "longitude": 97.04 - }, - { - "rank": 1, - "authorId": 2, - "messageId": 6, - "longitude": 75.56 - }, - { - "rank": 2, - "authorId": 2, - "messageId": 3, - "longitude": 81.01 - } - ] - -### ratio_to_report ### - -* Syntax: - - RATIO_TO_REPORT(expr) OVER (window-definition) - -* Returns the fractional ratio of the specified value for each tuple to the - sum of values for all tuples in the window frame. - -* Arguments: - - * `expr`: The value for which you want to calculate the - fractional ratio. \[[1](#fn_1)\] - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - - * (Optional) [Window Frame Clause](manual.html#Window_frame_clause). - -* Return Value: - - * A number between 0 and 1, representing the fractional ratio of the value - for the current tuple to the sum of values for all tuples in the - current window frame. - The sum of returned values for all tuples in the current window frame is 1. - - * If the input expression does not evaluate to a number, or the sum of - values for all tuples is zero, it returns NULL. - -* Example: - - For each author, calculate the length of each message as a - fraction of the total length of all messages. - - SELECT m.messageId, m.authorId, - RATIO_TO_REPORT(LENGTH(m.message)) OVER ( - PARTITION BY m.authorId - ) AS length_ratio - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "length_ratio": 0.21428571428571427, - "messageId": 2, - "authorId": 1 - }, - { - "length_ratio": 0.20952380952380953, - "messageId": 4, - "authorId": 1 - }, - { - "length_ratio": 0.14761904761904762, - "messageId": 8, - "authorId": 1 - }, - { - "length_ratio": 0.24285714285714285, - "messageId": 10, - "authorId": 1 - }, - { - "length_ratio": 0.18571428571428572, - "messageId": 11, - "authorId": 1 - }, - { - "length_ratio": 0.4430379746835443, - "messageId": 3, - "authorId": 2 - }, - { - "length_ratio": 0.5569620253164557, - "messageId": 6, - "authorId": 2 - } - ] - -### row_number ### - -* Syntax: - - ROW_NUMBER() OVER ([window-partition-clause] [window-order-clause]) - -* Returns a unique row number for every tuple in every window partition. - In each window partition, the row numbering starts at 1. - - The window order clause determines the sort order of the tuples. - If the window order clause is omitted, the return values may be - unpredictable. - -* Arguments: - - * None. - -* Clauses: - - * (Optional) [Window Partition Clause](manual.html#Window_partition_clause). - - * (Optional) [Window Order Clause](manual.html#Window_order_clause). - -* Return Value: - - * An integer, greater than or equal to 1. - -* Example: - - For each author, number all messages in order of length. - - SELECT m.messageId, m.authorId, - ROW_NUMBER() OVER ( - PARTITION BY m.authorId - ORDER BY LENGTH(m.message) - ) AS `row` - FROM GleambookMessages AS m; - -* The expected result is: - - [ - { - "row": 1, - "messageId": 8, - "authorId": 1 - }, - { - "row": 2, - "messageId": 11, - "authorId": 1 - }, - { - "row": 3, - "messageId": 4, - "authorId": 1 - }, - { - "row": 4, - "messageId": 2, - "authorId": 1 - }, - { - "row": 5, - "messageId": 10, - "authorId": 1 - }, - { - "row": 1, - "messageId": 3, - "authorId": 2 - }, - { - "row": 2, - "messageId": 6, - "authorId": 2 - } - ] - ---- - -1. -If the query contains the GROUP BY clause or any -[aggregate functions](#AggregateFunctions), this expression must only -depend on GROUP BY expressions or aggregate functions. diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/15_bitwise.md b/asterixdb/asterix-doc/src/main/markdown/builtins/15_bitwise.md deleted file mode 100644 index e86f679ed4b..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/15_bitwise.md +++ /dev/null @@ -1,653 +0,0 @@ - - -## Bitwise Functions ## - -All Bit/Binary functions can only operate on 64-bit signed integers. - -**Note:** All non-integer numbers and other data types result in null. - -**Note:** The query language uses two’s complement representation. - -When looking at the value in binary form, bit 1 is the Least Significant -Bit (LSB) and bit 32 is the Most Significant Bit (MSB). - -(MSB) Bit 32 → `0000 0000 0000 0000 0000 0000 0000 0000` ← Bit 1 (LSB) - -### bitand ### - -* Syntax: - - BITAND(int_value1, int_value2, ... , int_valueN) - -* Returns the result of a bitwise AND operation performed on all input - integer values. - - The bitwise AND operation compares each bit of `int_value1` to the - corresponding bit of every other `int_value`. - If all bits are 1, then the corresponding result bit is set to 1; - otherwise it is set to 0 (zero). - -* Arguments: - - * `int_valueI`: Integers, or any valid expressions which evaluate to - integers, that are used to compare. - -* Return Value: - - * An integer, representing the bitwise AND between all of the input - integers. - -* Limitations: - - * Input values must be integers (such as 1 or 1.0) and cannot contain - decimals (such as 1.2). - -* Example 1: - - Compare 3 (0011 in binary) and 6 (0110 in binary). - - { "BitAND": BITAND(3,6) }; - -* The expected result is: - - { "BitAND": 2 } - - This results in 2 (0010 in binary) because only bit 2 is set in both 3 - (00**1**1) and 6 (01**1**0). - -* Example 2: - - Compare 4.5 and 3 (0011 in binary). - - { "BitAND": BITAND(4.5,3) }; - -* The expected result is: - - { "BitAND": null } - - The result is null because 4.5 is not an integer. - -* Example 3: - - Compare 4.0 (0100 in binary) and 3 (0011 in binary). - - { "BitAND": BITAND(4.0,3) }; - -* The expected result is: - - { "BitAND": 0 } - - This results in 0 (zero) because 4.0 (0100) and 3 (0011) do not share - any bits that are both 1. - -* Example 4: - - Compare 3 (0011 in binary) and 6 (0110 in binary) and 15 (1111 in binary). - - { "BitAND": BITAND(3,6,15) }; - -* The expected result is: - - { "BitAND": 2 } - - This results in 2 (0010 in binary) because only the 2nd bit from the - right is 1 in all three numbers. - -### bitclear ### - -* Syntax: - - BITCLEAR(int_value, positions) - -* Returns the result after clearing the specified bit, or array of bits in - `int_value` using the given `positions`. - - **Note:** Specifying a negative or zero bit position makes the function - return a null. - -* Arguments: - - * `int_value`: An integer, or any valid expression which evaluates to an - integer, that contains the target bit or bits to clear. - - * `positions`: An integer or an array of integers specifying the position - or positions to be cleared. - -* Return Value: - - * An integer, representing the result after clearing the bit or bits - specified. - -* Limitations: - - * Input values must be integers (such as 1 or 1.0) and cannot contain - decimals (such as 1.2). - -* Example 1: - - Clear bit 1 from 6 (0110 in binary). - - { "BitCLEAR": BITCLEAR(6,1) }; - -* The expected result is: - - { "BitCLEAR": 6 } - - This results in 6 (011**0** in binary) because bit 1 was already zero. - -* Example 2: - - Clear bits 1 and 2 from 6 (01**10** in binary). - - { "BitCLEAR": BITCLEAR(6,[1,2]) }; - -* The expected result is: - - { "BitCLEAR": 4 } - - This results in 4 (01**0**0 in binary) because bit 2 changed to zero. - -* Example 3: - - Clear bits 1, 2, 4, and 5 from 31 (0**11**1**11** in binary). - - { "BitCLEAR": BITCLEAR(31,[1,2,4,5]) }; - -* The expected result is: - - { "BitCLEAR": 4 } - - This results in 4 (0**00**1**00**) because bits 1, 2, 4, and 5 changed to - zero. - -### bitnot ### - -* Syntax: - - BITNOT(int_value) - -* Returns the results of a bitwise logical NOT operation performed on - an integer value. - - The bitwise logical NOT operation reverses the bits in the value. - For each value bit that is 1, the corresponding result bit will be - set to 0 (zero); and for each value bit that is 0 (zero), the - corresponding result bit will be set to 1. - - **Note:** All bits of the integer will be altered by this operation. - -* Arguments: - - * `int_value`: An integer, or any valid expression which evaluates to an - integer, that contains the target bits to reverse. - -* Return Value: - - * An integer, representing the result after performing the logical NOT - operation. - -* Limitations: - - * Input values must be integers (such as 1 or 1.0) and cannot contain - decimals (such as 1.2). - -* Example 1: - - Perform the NOT operation on 3 (0000 0000 0000 0000 0000 0000 0000 0011 in binary). - - { "BitNOT": BITNOT(3) }; - -* The expected result is: - - { "BitNOT": -4 } - - This results in -4 (**1111 1111 1111 1111 1111 1111 1111 1100** in - binary) because all bits changed. - -### bitor ### - -* Syntax: - - BITOR(int_value1, int_value2, ... , int_valueN) - -* Returns the result of a bitwise inclusive OR operation performed on all input - integer values. - - The bitwise inclusive OR operation compares each bit of `int_value1` to the - corresponding bit of every other `int_value`. - If any bit is 1, the corresponding result bit is set to 1; otherwise, it - is set to 0 (zero). - -* Arguments: - - * `int_valueI`: Integers, or any valid expressions which evaluate to - integers, that are used to compare. - -* Return Value: - - * An integer, representing the bitwise OR between all of the input - integers. - -* Limitations: - - * Input values must be integers (such as 1 or 1.0) and cannot contain - decimals (such as 1.2). - -* Example 1: - - Perform OR on 3 (0011 in binary) and 6 (0110 in binary). - - { "BitOR": BITOR(3,6) }; - -* The expected result is: - - { "BitOR": 7 } - - This results in 7 (0**111** in binary) because at least 1 bit of each - (00**11** and 0**11**0) is 1 in bits 1, 2, and 3. - -* Example 2: - - Perform OR on 3 (0011 in binary) and -4 (1000 0000 0000 ... 0000 1100 in - binary). - - { "BitOR": BITOR(3,-4) }; - -* The expected result is: - - { "BitOR": -1 } - - This results in -1 (**1111 1111 1111 ... 1111 1111** in binary) because - the two 1 bits in 3 fill in the two 0 bits in -4 to turn on all the bits. - -* Example 3: - - Perform OR on 3 (0011 in binary) and 6 (0110 in binary) and 15 (1111 in - binary). - - { "BitOR": BITOR(3,6,15) }; - -* The expected result is: - - { "BitOR": 15 } - - This results in 15 (1111 in binary) because there is at least one 1 in - each of the four rightmost bits. - -### bitset ### - -* Syntax: - - BITSET(int_value, positions) - -* Returns the result after setting the specified bit `position`, or - array of bit positions, to 1 in the given `int_value`. - - **Note:** Specifying a negative or zero position makes the function return - a null. - -* Arguments: - - * `int_value`: An integer, or any valid expression which evaluates to an - integer, that contains the target bit or bits to set. - - * `positions`: An integer or an array of integers specifying the position - or positions to be set. - -* Return Value: - - * An integer, representing the result after setting the bit or bits - specified. - If the bit is already set, then it stays set. - -* Limitations: - - * Input values must be integers (such as 1 or 1.0) and cannot contain - decimals (such as 1.2). - -* Example 1: - - Set bit 1 in the value 6 (011**0** in binary). - - { "BitSET": BITSET(6,1) }; - -* The expected result is: - - { "BitSET": 7 } - - This results in 7 (011**1** in binary) because bit 1 changed to 1. - -* Example 2: - - Set bits 1 and 2 in the value 6 (01**10** in binary). - - { "BitSET": BITSET(6,[1,2]) }; - -* The expected result is: - - { "BitSET": 7 } - - This also results in 7 (01**11** in binary) because bit 1 changed while - bit 2 remained the same. - -* Example 3: - - Set bits 1 and 4 in the value 6 (**0**11**0** in binary). - - { "BitSET": BITSET(6,[1,4]) }; - -* The expected result is: - - { "BitSET": 15 } - - This results in 15 (**1**11**1** in binary) because bit 1 and 4 changed - to ones. - -### bitshift ### - -* Syntax: - - BITSHIFT(int_value, shift_amount[, rotate]) - -* Returns the result of a bit shift operation performed on the integer - value `int_value`. - The `shift_amount` supports left and right shifts. - These are logical shifts. - The third parameter `rotate` supports circular shift. - This is similar to the BitROTATE function in Oracle. - -* Arguments: - - * `int_value`: An integer, or any valid expression which evaluates to an - integer, that contains the target bit or bits to shift. - - * `shift_amount`: An integer, or any valid expression which evaluates to an - integer, that contains the number of bits to shift. - - - A positive (+) number means this is a LEFT shift. - - - A negative (-) number means this is a RIGHT shift. - - * `rotate`: (Optional) A boolean, or any valid expression which evaluates - to a boolean, where: - - - FALSE means this is a LOGICAL shift, where bits shifted off - the end of a value are considered lost. - - - TRUE means this is a CIRCULAR shift (shift-and-rotate - operation), where bits shifted off the end of a value are - rotated back onto the value at the *other* end. - In other words, the bits rotate in what might be thought of as a - circular pattern; therefore, these bits are not lost. - - If omitted, the default is FALSE. - - For comparison, see the below table. - - | Input | Shift | Result of Logical Shift (Rotate FALSE) | Result of Circular Shift (Rotate TRUE) | - |-------------------|-------|-------------------|------------------------------------------------| - | 6 (0000 0110) | 4 | 96 (0110 0000) | 96 (0110 0000) | - | 6 (0000 0110) | 3 | 48 (0011 0000) | 48 (0011 0000) | - | 6 (0000 0110) | 2 | 24 (0001 1000) | 24 (0001 1000) | - | 6 (0000 0110) | 1 | 12 (0000 1100) | 12 (0000 1100) | - | **6 (0000 0110)** | **0** | **6 (0000 0110)** | **6 (0000 0110)** | - | 6 (0000 0110) | -1 | 3 (0000 0011) | 3 (0000 0011) | - | 6 (0000 0110) | -2 | 1 (0000 0001) | -9223372036854775807 (1000 0000 ... 0000 0001) | - | 6 (0000 0110) | -3 | 0 (0000 0000) | -4611686018427387904 (1100 0000 ... 0000 0000) | - | 6 (0000 0110) | -4 | 0 (0000 0000) | 6917529027641081856 (0110 0000 ... 0000 0000) | - -* Return Value: - - * An integer, representing the result of either a logical or circular - shift of the given integer. - -* Limitations: - - * Input values must be integers (such as 1 or 1.0) and cannot contain - decimals (such as 1.2). - -* Example 1: - - Logical left shift of the number 6 (0110 in binary) by one bit. - - { "BitSHIFT": BITSHIFT(6,1,FALSE) }; - -* The expected result is: - - { "BitSHIFT": 12 } - - This results in 12 (1100 in binary) because the 1-bits moved from - positions 2 and 3 to positions 3 and 4. - -* Example 2: - - Logical right shift of the number 6 (0110 in binary) by two bits. - - { "BitSHIFT": BITSHIFT(6,-2) }; - -* The expected result is: - - { "BitSHIFT": 1 } - - This results in 1 (0001 in binary) because the 1-bit in position 3 moved - to position 1 and the 1-bit in position 2 was dropped. - -* Example 2b: - - Circular right shift of the number 6 (0110 in binary) by two bits. - - { "BitSHIFT": BITSHIFT(6,-2,TRUE) }; - -* The expected result is: - - { "BitSHIFT": -9223372036854775807 } - - This results in -9223372036854775807 (1100 0000 0000 0000 0000 0000 0000 - 0000 in binary) because the two 1-bits wrapped right, around to the Most - Significant Digit position and changed the integer’s sign to negative. - -* Example 3: - - Circular left shift of the number 524288 (1000 0000 0000 0000 0000 in - binary) by 45 bits. - - { "BitSHIFT": BITSHIFT(524288,45,TRUE) }; - -* The expected result is: - - { "BitSHIFT": 1 } - - This results in 1 because the 1-bit wrapped left, around to the Least - Significant Digit position. - -### bittest ### - -* Syntax: - - BITTEST(int_value, positions [, all_set]) - -* Returns TRUE if the specified bit, or bits, is a 1; otherwise, - returns FALSE if the specified bit, or bits, is a 0 (zero). - - **Note:** Specifying a negative or zero bit position will result in null - being returned. - -* Arguments: - - * `int_value`: An integer, or any valid expression which evaluates to an - integer, that contains the target bit or bits to test. - - * `positions`: An integer or an array of integers specifying the position - or positions to be tested. - - * `all_set`: (Optional) A boolean, or any valid expression which evaluates - to a boolean. - - - When `all_set` is FALSE, then it returns TRUE even if one bit in - one of the positions is set. - - - When `all_set` is TRUE, then it returns TRUE only if all input - positions are set. - - If omitted, the default is FALSE. - -* Return Value: - - * A boolean, that follows the below table: - - | `int_value` | `all_set` | Return Value | - |--------------------------------|-----------|--------------| - | *all* specified bits are TRUE | FALSE | TRUE | - | *all* specified bits are TRUE | TRUE | TRUE | - | *some* specified bits are TRUE | FALSE | TRUE | - | *some* specified bits are TRUE | TRUE | FALSE | - -* Limitations: - - * Input values must be integers (such as 1 or 1.0) and cannot contain - decimals (such as 1.2). - -* Example 1: - - In the number 6 (0110 in binary), is bit 1 set? - - { "IsBitSET": ISBITSET(6,1) }; - -* The expected result is: - - { "IsBitSET": false } - - This returns FALSE because bit 1 of 6 (011**0** in binary) is not set to 1. - -* Example 2: - - In the number 1, is either bit 1 or bit 2 set? - - { "BitTEST": BITTEST(1,[1,2],FALSE) }; - -* The expected result is: - - { "BitTEST": true } - - This returns TRUE because bit 1 of the number 1 (000**1** in binary) is - set to 1. - -* Example 3: - - In the number 6 (0110 in binary), are both bits 2 and 3 set? - - { "IsBitSET": ISBITSET(6,[2,3],TRUE) }; - -* The expected result is: - - { "IsBitSET": true } - - This returns TRUE because both bits 2 and 3 in the number 6 (0**11**0 in - binary) are set to 1. - -* Example 4: - - In the number 6 (0110 in binary), are all the bits in positions 1 through 3 - set? - - { "BitTEST": BITTEST(6,[1,3],TRUE) }; - -* The expected result is: - - { "BitTEST": false } - - This returns FALSE because bit 1 in the number 6 (011**0** in binary) is - set to 0 (zero). - -The function has an alias `isbitset`. - -### bitxor ### - -* Syntax: - - BITXOR(int_value1, int_value2, ... , int_valueN) - -* Returns the result of a bitwise Exclusive OR operation performed on - two or more integer values. - - The bitwise Exclusive OR operation compares each bit of `int_value1` to - the corresponding bit of `int_value2`. - - If there are more than two input values, the first two are compared; - then their result is compared to the next input value; and so on. - - When the compared bits do not match, the result bit is 1; otherwise, - the compared bits do match, and the result bit is 0 (zero), as - summarized: - - | Bit 1 | Bit 2 | XOR Result Bit | - |-------|-------|----------------| - | 0 | 0 | 0 | - | 0 | 1 | 1 | - | 1 | 0 | 1 | - | 1 | 1 | 0 | - -* Arguments: - - * `int_valueI`: Integers, or any valid expressions which evaluate to - integers, that are used to compare. - -* Return Value: - - * An integer, representing the bitwise XOR between the input - integers. - -* Limitations: - - * Input values must be integers (such as 1 or 1.0) and cannot contain - decimals (such as 1.2). - -* Example 1: - - Perform the XOR operation on 3 (0011 in binary) and 6 (0110 in binary). - - { "BitXOR": BITXOR(3,6) }; - -* The expected result is: - - { "BitXOR": 5 } - - This returns 5 (0101 in binary) because the 1st bit pair and 3rd bit - pair are different (resulting in 1) while the 2nd bit pair and 4th bit - pair are the same (resulting in 0): - - 0011 (3) - 0110 (6) - ==== - 0101 (5) - -* Example 2: - - Perform the XOR operation on 3 (0011 in binary) and 6 (0110 in binary) and - 15 (1111 in binary). - - { "BitXOR": BITXOR(3,6,15) }; - -* The expected result is: - - { "BitXOR": 10 } - - This returns 10 (1010 in binary) because 3 XOR 6 equals 5 (0101 in binary), - and then 5 XOR 15 equals 10 (1010 in binary). diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/1_numeric_common.md b/asterixdb/asterix-doc/src/main/markdown/builtins/1_numeric_common.md deleted file mode 100644 index 5afec07b777..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/1_numeric_common.md +++ /dev/null @@ -1,653 +0,0 @@ - - -## Numeric Functions ## -### abs ### - * Syntax: - - abs(numeric_value) - - * Computes the absolute value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * The absolute value of the argument with the same type as the input argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": abs(2013), "v2": abs(-4036), "v3": abs(0), "v4": abs(float("-2013.5")), "v5": abs(double("-2013.593823748327284")) }; - - - * The expected result is: - - { "v1": 2013, "v2": 4036, "v3": 0, "v4": 2013.5, "v5": 2013.5938237483274 } - - -### acos ### - * Syntax: - - acos(numeric_value) - - * Computes the arc cosine value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` arc cosine in radians for the argument, - if the argument is in the range of -1 (inclusive) to 1 (inclusive), - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error, - * "NaN" for other legitimate numeric values. - - * Example: - - { "v1": acos(1), "v2": acos(2), "v3": acos(0), "v4": acos(float("0.5")), "v5": acos(double("-0.5")) }; - - - * The expected result is: - - { "v1": 0.0, "v2": "NaN", "v3": 1.5707963267948966, "v4": 1.0471975511965979, "v5": 2.0943951023931957 } - - - -### asin ### - * Syntax: - - asin(numeric_value) - - * Computes the arc sine value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` arc sin in radians for the argument, - if the argument is in the range of -1 (inclusive) to 1 (inclusive), - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error, - * "NaN" for other legitimate numeric values. - - * Example: - - { "v1": asin(1), "v2": asin(2), "v3": asin(0), "v4": asin(float("0.5")), "v5": asin(double("-0.5")) }; - - - * The expected result is: - - { "v1": 1.5707963267948966, "v2": "NaN", "v3": 0.0, "v4": 0.5235987755982989, "v5": -0.5235987755982989 } - - -### atan ### - * Syntax: - - atan(numeric_value) - - * Computes the arc tangent value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` arc tangent in radians for the argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": atan(1), "v2": atan(2), "v3": atan(0), "v4": atan(float("0.5")), "v5": atan(double("1000")) }; - - - * The expected result is: - - { "v1": 0.7853981633974483, "v2": 1.1071487177940904, "v3": 0.0, "v4": 0.4636476090008061, "v5": 1.5697963271282298 } - - -### atan2 ### - * Syntax: - - atan2(numeric_value1, numeric_value2) - - * Computes the arc tangent value of numeric_value2/numeric_value1. - * Arguments: - * `numeric_value1`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value, - * `numeric_value2`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` arc tangent in radians for `numeric_value1` and `numeric_value2`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": atan2(1, 2), "v2": atan2(0, 4), "v3": atan2(float("0.5"), double("-0.5")) }; - - - * The expected result is: - - { "v1": 0.4636476090008061, "v2": 0.0, "v3": 2.356194490192345 } - - -### ceil ### - * Syntax: - - ceil(numeric_value) - - * Computes the smallest (closest to negative infinity) number with no fractional part that is not less than the value of the argument. If the argument is already equal to mathematical integer, then the result is the same as the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * The ceiling value for the given number in the same type as the input argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { - "v1": ceil(2013), - "v2": ceil(-4036), - "v3": ceil(0.3), - "v4": ceil(float("-2013.2")), - "v5": ceil(double("-2013.893823748327284")) - }; - - - * The expected result is: - - { "v1": 2013, "v2": -4036, "v3": 1.0, "v4": -2013.0, "v5": -2013.0 } - - -### cos ### - * Syntax: - - cos(numeric_value) - - * Computes the cosine value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` cosine value for the argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": cos(1), "v2": cos(2), "v3": cos(0), "v4": cos(float("0.5")), "v5": cos(double("1000")) }; - - - * The expected result is: - - { "v1": 0.5403023058681398, "v2": -0.4161468365471424, "v3": 1.0, "v4": 0.8775825618903728, "v5": 0.562379076290703 } - - -### cosh ### - * Syntax: - - cosh(numeric_value) - - * Computes the hyperbolic cosine value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` hyperbolic cosine value for the argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": cosh(1), "v2": cosh(2), "v3": cosh(0), "v4": cosh(float("0.5")), "v5": cosh(double("8")) }; - - - * The expected result is: - - { "v1": 1.5430806348152437, "v2": 3.7621956910836314, "v3": 1.0, "v4": 1.1276259652063807, "v5": 1490.479161252178 } - - -### degrees ### - * Syntax: - - degrees(numeric_value) - - * Converts radians to degrees - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * The degrees value for the given radians value. The returned value has type `double`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": degrees(pi()) }; - - - * The expected result is: - - { "v1": 180.0 } - - -### e ### - * Syntax: - - e() - - * Return Value: - * e (base of the natural logarithm) - - * Example: - - { "v1": e() }; - - * The expected result is: - - { "v1": 2.718281828459045 } - - -### exp ### - * Syntax: - - exp(numeric_value) - - * Computes enumeric_value. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * enumeric_value, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": exp(1), "v2": exp(2), "v3": exp(0), "v4": exp(float("0.5")), "v5": exp(double("1000")) }; - - - * The expected result is: - - { "v1": 2.718281828459045, "v2": 7.38905609893065, "v3": 1.0, "v4": 1.6487212707001282, "v5": "Infinity" } - - -### floor ### - * Syntax: - - floor(numeric_value) - - * Computes the largest (closest to positive infinity) number with no fractional part that is not greater than the value. - If the argument is already equal to mathematical integer, then the result is the same as the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * The floor value for the given number in the same type as the input argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { - "v1": floor(2013), - "v2": floor(-4036), - "v3": floor(0.8), - "v4": floor(float("-2013.2")), - "v5": floor(double("-2013.893823748327284")) - }; - - - * The expected result is: - - { "v1": 2013, "v2": -4036, "v3": 0.0, "v4": -2014.0, "v5": -2014.0 } - - -### ln ### - * Syntax: - - ln(numeric_value) - - * Computes logenumeric_value. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * logenumeric_value, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": ln(1), "v2": ln(2), "v3": ln(0), "v4": ln(float("0.5")), "v5": ln(double("1000")) }; - - - * The expected result is: - - { "v1": 0.0, "v2": 0.6931471805599453, "v3": "-Infinity", "v4": -0.6931471805599453, "v5": 6.907755278982137 } - - - -### log ### - * Syntax: - - log(numeric_value) - - * Computes log10numeric_value. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * log10numeric_value, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": log(1), "v2": log(2), "v3": log(0), "v4": log(float("0.5")), "v5": log(double("1000")) }; - - * The expected result is: - - { "v1": 0.0, "v2": 0.3010299956639812, "v3": "-Infinity", "v4": -0.3010299956639812, "v5": 3.0 } - - -### pi ### - * Syntax: - - pi() - - * Return Value: - * Pi - - * Example: - - { "v1": pi() }; - - * The expected result is: - - { "v1": 3.141592653589793 } - - -### power ### - * Syntax: - - power(numeric_value1, numeric_value2) - - * Computes numeric_value1numeric_value2. - * Arguments: - * `numeric_value1`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value, - * `numeric_value2`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * numeric_value1numeric_value2, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": power(1, 2), "v3": power(0, 4), "v4": power(float("0.5"), double("-0.5")) }; - - - * The expected result is: - - { "v1": 1, "v3": 0, "v4": 1.4142135623730951 } - - -### radians ### - * Syntax: - - radians(numeric_value) - - * Converts degrees to radians - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * The radians value for the given degrees value. The returned value has type `double`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": radians(180) }; - - - * The expected result is: - - { "v1": 3.141592653589793 } - - -### round ### - * Syntax: - - round(numeric_value[, round_digit]) - - * Rounds the value to the given number of integer digits to the right of the decimal point, - or to the left of the decimal point if the number of digits is negative. - - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value - that represents the numeric value to be rounded. - * `round_digit`: (Optional) a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value - that specifies the digit to round to. - This argument may be positive or negative; - positive indicating that rounding needs to be to the right of the decimal point, - and negative indicating that rounding needs to be to the left of the decimal point. - Values such as 1.0 and 2.0 are acceptable, but values such as 1.3 and 1.5 result in a `null`. - If omitted, the default is 0. - * Return Value: - * The rounded value for the given number. - The returned value has the following type: - - `bigint` if the input value has type `tinyint`, `smallint`, `integer` or `bigint`, - - `float` if the input value has type `float`, - - `double` if the input value has type `double`; - * `missing` if the input value is a `missing` value, - * `null` if the input value is a `null` value, - * any other non-numeric input value will return a `null` value. - - * Example: - - { - "v1": round(2013), - "v2": round(-4036), - "v3": round(0.8), - "v4": round(float("-2013.256")), - "v5": round(double("-2013.893823748327284")) - "v6": round(123456, -1), - "v7": round(456.456, 2), - "v8": round(456.456, -1), - "v9": round(-456.456, -2) - }; - - * The expected result is: - - { "v1": 2013, "v2": -4036, "v3": 1.0, "v4": -2013.0, "v5": -2014.0, "v6": 123460, "v7": 456.46, "v8": 460, "v9": -500 } - - -### sign ### - * Syntax: - - sign(numeric_value) - - * Computes the sign of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the sign (a `tinyint`) of the argument, -1 for negative values, 0 for 0, and 1 for positive values, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": sign(1), "v2": sign(2), "v3": sign(0), "v4": sign(float("0.5")), "v5": sign(double("-1000")) }; - - - * The expected result is: - - { "v1": 1, "v2": 1, "v3": 0, "v4": 1, "v5": -1 } - - - -### sin ### - * Syntax: - - sin(numeric_value) - - * Computes the sine value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` sine value for the argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": sin(1), "v2": sin(2), "v3": sin(0), "v4": sin(float("0.5")), "v5": sin(double("1000")) }; - - - * The expected result is: - - { "v1": 0.8414709848078965, "v2": 0.9092974268256817, "v3": 0.0, "v4": 0.479425538604203, "v5": 0.8268795405320025 } - - -### sinh ### - * Syntax: - - sinh(numeric_value) - - * Computes the hyperbolic sine value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` hyperbolic sine value for the argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": sinh(1), "v2": sinh(2), "v3": sinh(0), "v4": sinh(float("0.5")), "v5": sinh(double("8")) }; - - - * The expected result is: - - { "v1": 1.1752011936438014, "v2": 3.626860407847019, "v3": 0.0, "v4": 0.5210953054937474, "v5": 1490.4788257895502 } - - -### sqrt ### - * Syntax: - - sqrt(numeric_value) - - * Computes the square root of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` square root value for the argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": sqrt(1), "v2": sqrt(2), "v3": sqrt(0), "v4": sqrt(float("0.5")), "v5": sqrt(double("1000")) }; - - - * The expected result is: - - { "v1": 1.0, "v2": 1.4142135623730951, "v3": 0.0, "v4": 0.7071067811865476, "v5": 31.622776601683793 } - - -### tan ### - * Syntax: - - tan(numeric_value) - - * Computes the tangent value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` tangent value for the argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": tan(1), "v2": tan(2), "v3": tan(0), "v4": tan(float("0.5")), "v5": tan(double("1000")) }; - - - * The expected result is: - - { "v1": 1.5574077246549023, "v2": -2.185039863261519, "v3": 0.0, "v4": 0.5463024898437905, "v5": 1.4703241557027185 } - - -### tanh ### - * Syntax: - - tanh(numeric_value) - - * Computes the hyperbolic tangent value of the argument. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * Return Value: - * the `double` hyperbolic tangent value for the argument, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { "v1": tanh(1), "v2": tanh(2), "v3": tanh(0), "v4": tanh(float("0.5")), "v5": tanh(double("8")) }; - - - * The expected result is: - - { "v1": 0.7615941559557649, "v2": 0.964027580075817, "v3": 0.0, "v4": 0.4621171572600098, "v5": 0.999999774929676 } - - -### trunc ### - * Syntax: - - trunc(numeric_value, number_digits) - - * Truncates the number to the given number of integer digits to the right of the decimal point (left if digits is negative). - Digits is 0 if not given. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value, - * `number_digits`: a `tinyint`/`smallint`/`integer`/`bigint` value. - * Return Value: - * the `double` tangent value for the argument, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is `missing`, - * a type error will be raised if: - * the first argument is any other non-numeric value, - * the second argument is any other non-tinyint, non-smallint, non-integer, and non-bigint value. - - * Example: - - { "v1": trunc(1, 1), "v2": trunc(2, -2), "v3": trunc(0.122, 2), "v4": trunc(float("11.52"), -1), "v5": trunc(double("1000.5252"), 3) }; - - - * The expected result is: - - { "v1": 1, "v2": 2, "v3": 0.12, "v4": 10.0, "v5": 1000.525 } - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/1_numeric_delta.md b/asterixdb/asterix-doc/src/main/markdown/builtins/1_numeric_delta.md deleted file mode 100644 index 151233eb4c3..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/1_numeric_delta.md +++ /dev/null @@ -1,57 +0,0 @@ - - -### round_half_to_even ### - * Syntax: - - round_half_to_even(numeric_value, [precision]) - - * Computes the closest numeric value to `numeric_value` that is a multiple of ten to the power of minus `precision`. - `precision` is optional and by default value `0` is used. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint`/`float`/`double` value. - * `precision`: an optional `tinyint`/`smallint`/`integer`/`bigint` field representing the - number of digits in the fraction of the the result - * Return Value: - * The rounded value for the given number in the same type as the input argument, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-numeric value, - * or, the second argument is any other non-tinyint, non-smallint, non-integer, or non-bigint value. - - * Example: - - { - "v1": round_half_to_even(2013), - "v2": round_half_to_even(-4036), - "v3": round_half_to_even(0.8), - "v4": round_half_to_even(float("-2013.256")), - "v5": round_half_to_even(double("-2013.893823748327284")), - "v6": round_half_to_even(double("-2013.893823748327284"), 2), - "v7": round_half_to_even(2013, 4), - "v8": round_half_to_even(float("-2013.256"), 5) - }; - - - * The expected result is: - - { "v1": 2013, "v2": -4036, "v3": 1.0, "v4": -2013.0, "v5": -2014.0, "v6": -2013.89, "v7": 2013, "v8": -2013.256 } - - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/2_string_common.md b/asterixdb/asterix-doc/src/main/markdown/builtins/2_string_common.md deleted file mode 100644 index 58d0e10bdda..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/2_string_common.md +++ /dev/null @@ -1,639 +0,0 @@ - - -## String Functions ## -### concat ### - * Syntax: - - concat(string1, string2, ...) - - * Returns a concatenated string from arguments. - * Arguments: - * `string1`: a string value, - * `string2`: a string value, - * .... - * Return Value: - * a concatenated string from arguments, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error. - - * Example: - - concat("test ", "driven ", "development"); - - - * The expected result is: - - "test driven development" - - -### contains ### - * Syntax: - - contains(string, substring_to_contain) - - * Checks whether the string `string` contains the string `substring_to_contain` - * Arguments: - * `string` : a `string` that might contain the given substring, - * `substring_to_contain` : a target `string` that might be contained. - * Return Value: - * a `boolean` value, `true` if `string` contains `substring_to_contain`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error, - * `false` otherwise. - - * Note: an [n_gram index](similarity.html#UsingIndexesToSupportSimilarityQueries) can be utilized for this function. - * Example: - - { "v1": contains("I like x-phone", "phone"), "v2": contains("one", "phone") }; - - - * The expected result is: - - { "v1": true, "v2": false } - - -### ends_with ### - * Syntax: - - ends_with(string, substring_to_end_with) - - * Checks whether the string `string` ends with the string `substring_to_end_with`. - * Arguments: - * `string` : a `string` that might end with the given string, - * `substring_to_end_with` : a `string` that might be contained as the ending substring. - * Return Value: - * a `boolean` value, `true` if `string` contains `substring_to_contain`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error, - * `false` otherwise. - - * Example: - - { - "v1": ends_with(" love product-b its shortcut_menu is awesome:)", ":)"), - "v2": ends_with(" awsome:)", ":-)") - }; - - - * The expected result is: - - { "v1": true, "v2": false } - - -### initcap (or title) ### - * Syntax: - - initcap(string) - - * Converts a given string `string` so that the first letter of each word is uppercase and - every other letter is lowercase. - The function has an alias called "title". - * Arguments: - * `string` : a `string` to be converted. - * Return Value: - * a `string` as the title form of the given `string`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-string input value will cause a type error. - - * Example: - - { "v1": initcap("ASTERIXDB is here!"), "v2": title("ASTERIXDB is here!") }; - - - * The expected result is: - - { "v1": "Asterixdb Is Here!", "v2": "Asterixdb Is Here!" } - - -### length ### - * Syntax: - - length(string) - - * Returns the length of the string `string`. - * Arguments: - * `string` : a `string` or `null` that represents the string to be checked. - * Return Value: - * an `bigint` that represents the length of `string`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-string input value will cause a type error. - - * Example: - - length("test string"); - - - * The expected result is: - - 11 - - -### lower ### - * Syntax: - - lower(string) - - * Converts a given string `string` to its lowercase form. - * Arguments: - * `string` : a `string` to be converted. - * Return Value: - * a `string` as the lowercase form of the given `string`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-string input value will cause a type error. - - * Example: - - lower("ASTERIXDB"); - - - * The expected result is: - - "asterixdb" - - -### ltrim ### - * Syntax: - - ltrim(string[, chars]); - - * Returns a new string with all leading characters that appear in `chars` removed. - By default, white space is the character to trim. - * Arguments: - * `string` : a `string` to be trimmed, - * `chars` : a `string` that contains characters that are used to trim. - * Return Value: - * a trimmed, new `string`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error. - - - * Example: - - ltrim("me like x-phone", "eml"); - - - * The expected result is: - - " like x-phone" - - -### position ### - * Syntax: - - position(string, string_pattern) - - * Returns the first position of `string_pattern` within `string`. The function returns the 0-based position. Another - version of the function returns the 1-based position. Below are the aliases for each version: - - * Aliases: - * 0-based: `position`, `pos`, `position0`, `pos0`. - * 1-based: `position1`, `pos1`. - - * Arguments: - * `string` : a `string` that might contain the pattern. - * `string_pattern` : a pattern `string` to be matched. - * Return Value: - * the first position that `string_pattern` appears within `string` - (starting at 0), or -1 if it does not appear, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will return a `null`. - - * Example: - - { - "v1": position("ppphonepp", "phone"), - "v2": position("hone", "phone"), - "v3": position1("ppphonepp", "phone"), - "v4": position1("hone", "phone"), - }; - - - * The expected result is: - - { "v1": 2, "v2": -1, v3": 3, "v4": -1 } - - -### regexp_contains ### - * Syntax: - - regexp_contains(string, string_pattern[, string_flags]) - - * Checks whether the strings `string` contains the regular expression - pattern `string_pattern` (a Java regular expression pattern). - - * Aliases: - * `regexp_contains`, `regex_contains`, `contains_regexp`, `contains_regex`. - - * Arguments: - * `string` : a `string` that might contain the pattern. - * `string_pattern` : a pattern `string` to be matched. - * `string_flag` : (Optional) a `string` with flags to be used during regular expression matching. - * The following modes are enabled with these flags: dotall (s), multiline (m), case_insensitive (i), and comments and whitespace (x). - * Return Value: - * a `boolean`, returns `true` if `string` contains the pattern `string_pattern`, `false` otherwise. - * `missing` if any argument is a `missing` value. - * `null` if any argument is a `null` value but no argument is a `missing` value. - * any other non-string input value will return a `null`. - - * Example: - - { - "v1": regexp_contains("pphonepp", "p*hone"), - "v2": regexp_contains("hone", "p+hone") - }; - - - * The expected result is: - - { "v1": true, "v2": false } - - -### regexp_like ### - * Syntax: - - regexp_like(string, string_pattern[, string_flags]) - - * Checks whether the string `string` exactly matches the regular expression pattern `string_pattern` - (a Java regular expression pattern). - - * Aliases: - * `regexp_like`, `regex_like`. - - * Arguments: - * `string` : a `string` that might contain the pattern. - * `string_pattern` : a pattern `string` that might be contained. - * `string_flag` : (Optional) a `string` with flags to be used during regular expression matching. - * The following modes are enabled with these flags: dotall (s), multiline (m), case_insensitive (i), and comments and whitespace (x). - * Return Value: - * a `boolean` value, `true` if `string` contains the pattern `string_pattern`, `false` otherwise. - * `missing` if any argument is a `missing` value. - * `null` if any argument is a `null` value but no argument is a `missing` value. - * any other non-string input value will return a `null`. - - * Example: - - { - "v1": regexp_like(" can't stand acast the network is horrible:(", ".*acast.*"), - "v2": regexp_like("acast", ".*acst.*") - }; - - * The expected result is: - - { "v1": true, "v2": false } - - -### regexp_position ### - * Syntax: - - regexp_position(string, string_pattern[, string_flags]) - - * Returns first position of the regular expression `string_pattern` (a Java regular expression pattern) within `string`. - The function returns the 0-based position. Another version of the function returns the 1-based position. Below are the - aliases for each version: - - * Aliases: - * 0-Based: `regexp_position`, `regexp_pos`, `regexp_position0`, `regexp_pos0`, `regex_position`, `regex_pos`, - `regex_position0`, `regex_pos0`. - * 1-Based: `regexp_position1`, `regexp_pos1`, `regex_position1` `regex_pos1`. - - * Arguments: - * `string` : a `string` that might contain the pattern. - * `string_pattern` : a pattern `string` to be matched. - * `string_flag` : (Optional) a `string` with flags to be used during regular expression matching. - * The following modes are enabled with these flags: dotall (s), multiline (m), case_insensitive (i), and comments and whitespace (x). - * Return Value: - * the first position that the regular expression `string_pattern` appears in `string` - (starting at 0), or -1 if it does not appear. - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will return a `null`. - - * Example: - - { - "v1": regexp_position("pphonepp", "p*hone"), - "v2": regexp_position("hone", "p+hone"), - "v3": regexp_position1("pphonepp", "p*hone"), - "v4": regexp_position1("hone", "p+hone") - }; - - * The expected result is: - - { "v1": 0, "v2": -1, "v3": 1, "v4": -1 } - - -### regexp_replace ### - * Syntax: - - regexp_replace(string, string_pattern, string_replacement[, string_flags]) - regexp_replace(string, string_pattern, string_replacement[, replacement_limit]) - - * Checks whether the string `string` matches the given - regular expression pattern `string_pattern` (a Java regular expression pattern), - and replaces the matched pattern `string_pattern` with the new pattern `string_replacement`. - - * Aliases: - * `regexp_replace`, `regex_replace`. - - * Arguments: - * `string` : a `string` that might contain the pattern. - * `string_pattern` : a pattern `string` to be matched. - * `string_replacement` : a pattern `string` to be used as the replacement. - * `string_flag` : (Optional) a `string` with flags to be used during replace. - * The following modes are enabled with these flags: dotall (s), multiline (m), case_insensitive (i), and comments and whitespace (x). - * `replacement_limit`: (Optional) an `integer` specifying the maximum number of replacements to make - (if negative then all occurrences will be replaced) - * Return Value: - * Returns a `string` that is obtained after the replacements. - * `missing` if any argument is a `missing` value. - * `null` if any argument is a `null` value but no argument is a `missing` value. - * any other non-string input value will return a `null`. - - * Example: - - regexp_replace(" like x-phone the voicemail_service is awesome", " like x-phone", "like product-a"); - - - * The expected result is: - - "like product-a the voicemail_service is awesome" - - -### repeat ### - * Syntax: - - repeat(string, n) - - * Returns a string formed by repeating the input `string` `n` times. - * Arguments: - * `string` : a `string` to be repeated, - * `n` : an `tinyint`/`smallint`/`integer`/`bigint` value - how many times the string should be repeated. - * Return Value: - * a string that repeats the input `string` `n` times, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-string value, - * or, the second argument is not a `tinyint`, `smallint`, `integer`, or `bigint`. - - * Example: - - repeat("test", 3); - - - * The expected result is: - - "testtesttest" - -### replace ### - * Syntax: - - replace(string, search_string, replacement_string[, limit]) - - * Finds occurrences of the given substring `search_string` in the input string `string` - and replaces them with the new substring `replacement_string`. - * Arguments: - * `string` : an input `string`, - * `search_string` : a `string` substring to be searched for, - * `replacement_string` : a `string` to be used as the replacement, - * `limit` : (Optional) an `integer` - maximum number of occurrences to be replaced. - If not specified or negative then all occurrences will be replaced - * Return Value: - * Returns a `string` that is obtained after the replacements, - * `missing` if any argument is a `missing` value, - * any other non-string input value or non-integer `limit` will cause a type error, - * `null` if any argument is a `null` value but no argument is a `missing` value. - - * Example: - - { - "v1": replace(" like x-phone the voicemail_service is awesome", " like x-phone", "like product-a"), - "v2": replace("x-phone and x-phone", "x-phone", "product-a", 1) - }; - - * The expected result is: - - { - "v1": "like product-a the voicemail_service is awesome", - "v2": "product-a and x-phone" - } - -### reverse ### - * Syntax: - - reverse(string) - - * Returns a string formed by reversing characters in the input `string`. - * Arguments: - * `string` : a `string` to be reversed - * Return Value: - * a string containing characters from the the input `string` in the reverse order, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-string value - - * Example: - - reverse("hello"); - - - * The expected result is: - - "olleh" - -### rtrim ### - * Syntax: - - rtrim(string[, chars]); - - * Returns a new string with all trailing characters that appear in `chars` removed. - By default, white space is the character to trim. - * Arguments: - * `string` : a `string` to be trimmed, - * `chars` : a `string` that contains characters that are used to trim. - * Return Value: - * a trimmed, new `string`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error. - - - * Example: - - { - "v1": rtrim("i like x-phone", "x-phone"), - "v2": rtrim("i like x-phone", "onexph") - }; - - * The expected result is: - - { "v1": "i like ", "v2": "i like " } - -### split ### - * Syntax: - - split(string, sep) - - * Splits the input `string` into an array of substrings separated by the string `sep`. - * Arguments: - * `string` : a `string` to be split. - * Return Value: - * an array of substrings by splitting the input `string` by `sep`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-string input value will cause a type error. - - * Example: - - split("test driven development", " "); - - - * The expected result is: - - [ "test", "driven", "development" ] - - -### starts_with ### - * Syntax: - - starts_with(string, substring_to_start_with) - - * Checks whether the string `string` starts with the string `substring_to_start_with`. - * Arguments: - * `string` : a `string` that might start with the given string. - * `substring_to_start_with` : a `string` that might be contained as the starting substring. - * Return Value: - * a `boolean`, returns `true` if `string` starts with the string `substring_to_start_with`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error, - * `false` otherwise. - - * Example: - - { - "v1" : starts_with(" like the plan, amazing", " like"), - "v2" : starts_with("I like the plan, amazing", " like") - }; - - - * The expected result is: - - { "v1": true, "v2": false } - - -### substr ### - * Syntax: - - substr(string, offset[, length]) - - * Returns the substring from the given string `string` based on the given start offset `offset` with the optional `length`. - The function uses the 0-based position. Another version of the function uses the 1-based position. Below are the - aliases for each version: - - * Aliases: - * 0-Based: `substring`, `substr`, `substring0`, `substr0`. - * 1-Based: `substring1`, `substr1`. - - * Arguments: - * `string` : a `string` to be extracted. - * `offset` : an `tinyint`/`smallint`/`integer`/`bigint` value as the starting offset of the substring in `string` - (starting at 0). If negative then counted from the end of the string. - * `length` : (Optional) an an `tinyint`/`smallint`/`integer`/`bigint` value as the length of the substring. - * Return Value: - * a `string` that represents the substring, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, or if the substring could not - be obtained because the starting offset is not within string bounds or `length` is negative. - * a `null` will be returned if: - * the first argument is any other non-string value. - * the second argument is not a `tinyint`, `smallint`, `integer`, or `bigint`. - * the third argument is not a `tinyint`, `smallint`, `integer`, or `bigint` if the argument is present. - - * Example: - - { "v1": substr("test string", 6, 3), "v2": substr1("test string", 6, 3) }; - - - * The expected result is: - - { "v1": "tri", "v2": "str" } - -The function has an alias `substring`. - -### trim ### - * Syntax: - - trim(string[, chars]); - - * Returns a new string with all leading characters that appear in `chars` removed. - By default, white space is the character to trim. - * Arguments: - * `string` : a `string` to be trimmed, - * `chars` : a `string` that contains characters that are used to trim. - * Return Value: - * a trimmed, new `string`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error. - - - * Example: - - trim("i like x-phone", "xphoen"); - - - * The expected result is: - - " like " - - -### upper ### - * Syntax: - - upper(string) - - * Converts a given string `string` to its uppercase form. - * Arguments: - * `string` : a `string` to be converted. - * Return Value: - * a `string` as the uppercase form of the given `string`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-string input value will cause a type error. - - * Example: - - upper("hello") - - - * The expected result is: - - "HELLO" - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/2_string_delta.md b/asterixdb/asterix-doc/src/main/markdown/builtins/2_string_delta.md deleted file mode 100644 index fcf1c20c37f..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/2_string_delta.md +++ /dev/null @@ -1,174 +0,0 @@ - - -### string_concat ### - * Syntax: - - string_concat(array) - - * Concatenates an array of strings `array` into a single string. - * Arguments: - * `array` : an `array` or `multiset` of `string`s (could be `null` or `missing`) to be concatenated. - * Return Value: - * the concatenated `string` value, - * `missing` if the argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * `missing` if any element in the input array is `missing`, - * `null` if any element in the input array is `null` but no element in the input array is `missing`, - * any other non-array input value or non-integer element in the input array will cause a type error. - - * Example: - - string_concat(["ASTERIX", " ", "ROCKS!"]); - - - * The expected result is: - - "ASTERIX ROCKS!" - - -### string_join ### - * Syntax: - - string_join(array, string) - - * Joins an array or multiset of strings `array` with the given separator `string` into a single string. - * Arguments: - * `array` : an `array` or `multiset` of strings (could be `null`) to be joined. - * `string` : a `string` to serve as the separator. - * Return Value: - * the joined `string`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * `missing` if the first argument array contains a `missing`, - * `null` if the first argument array contains a `null` but does not contain a `missing`, - * a type error will be raised if: - * the first argument is any other non-array value, or contains any other non-string value, - * or, the second argument is any other non-string value. - - * Example: - - string_join(["ASTERIX", "ROCKS~"], "!! "); - - - * The expected result is: - - "ASTERIX!! ROCKS~" - - -### string_to_codepoint ### - * Syntax: - - string_to_codepoint(string) - - * Converts the string `string` to its code_based representation. - * Arguments: - * `string` : a `string` that will be converted. - * Return Value: - * an `array` of the code points for the string `string`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-string input value will cause a type error. - - * Example: - - string_to_codepoint("Hello ASTERIX!"); - - - * The expected result is: - - [ 72, 101, 108, 108, 111, 32, 65, 83, 84, 69, 82, 73, 88, 33 ] - - -### codepoint_to_string ### - * Syntax: - - codepoint_to_string(array) - - * Converts the ordered code_based representation `array` to the corresponding string. - * Arguments: - * `array` : an `array` of integer code_points. - * Return Value: - * a `string` representation of `array`. - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * `missing` if any element in the input array is `missing`, - * `null` if any element in the input array is `null` but no element in the input array is `missing`, - * any other non-array input value or non-integer element in the input array will cause a type error. - - * Example: - - codepoint_to_string([72, 101, 108, 108, 111, 32, 65, 83, 84, 69, 82, 73, 88, 33]); - - - * The expected result is: - - "Hello ASTERIX!" - - -### substring_before ### - * Syntax: - - substring_before(string, string_pattern) - - * Returns the substring from the given string `string` before the given pattern `string_pattern`. - * Arguments: - * `string` : a `string` to be extracted. - * `string_pattern` : a `string` pattern to be searched. - * Return Value: - * a `string` that represents the substring, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error. - - * Example: - - substring_before(" like x-phone", "x-phone"); - - - * The expected result is: - - " like " - - -### substring_after ### - * Syntax: - - substring_after(string, string_pattern); - - * Returns the substring from the given string `string` after the given pattern `string_pattern`. - * Arguments: - * `string` : a `string` to be extracted. - * `string_pattern` : a `string` pattern to be searched. - * Return Value: - * a `string` that represents the substring, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error. - - - * Example: - - substring_after(" like x-phone", "xph"); - - - * The expected result is: - - "one" - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/3_binary.md b/asterixdb/asterix-doc/src/main/markdown/builtins/3_binary.md deleted file mode 100644 index 82a68be2a9e..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/3_binary.md +++ /dev/null @@ -1,143 +0,0 @@ - - -## Binary Functions ## -### parse_binary ### - * Syntax: - - parse_binary(string, encoding) - - * Creates a `binary` from an string encoded in `encoding` format. - * Arguments: - * `string` : an encoded `string`, - * `encoding` : a string notation specifies the encoding type of the given `string`. - Currently we support `hex` and `base64` format. - * Return Value: - * a `binary` that is decoded from the given `string`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error. - - * Example: - - [ parse_binary("ABCDEF0123456789","hex"), parse_binary("abcdef0123456789","HEX"), parse_binary('QXN0ZXJpeAE=',"base64") ]; - - * The expected result is: - - [ hex("ABCDEF0123456789"), hex("ABCDEF0123456789"), hex("4173746572697801") ] - -### print_binary ### - * Syntax: - - print_binary(binary, encoding) - - * Prints a `binary` to the required encoding `string` format. - * Arguments: - * `binary` : a `binary` data need to be printed. - * `encoding` : a string notation specifies the expected encoding type. - Currently we support `hex` and `base64` format. - * Return Value: - * a `string` that represents the encoded format of a `binary`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error. - - * Example: - - [ print_binary(hex("ABCDEF0123456789"), "base64"), print_binary(base64("q83vASNFZ4k="), "hex") ] - - * The expected result are: - - [ "q83vASNFZ4k=", "ABCDEF0123456789" ] - -### binary_length ### - * Syntax: - - binary_length(binary) - - * Returns the number of bytes storing the binary data. - * Arguments: - * `binary` : a `binary` value to be checked. - * Return Value: - * an `bigint` that represents the number of bytes, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-binary input value will cause a type error. - - * Example: - - binary_length(hex("00AA")) - - * The expected result is: - - 2 - -### sub_binary ### - * Syntax: - - sub_binary(binary, offset[, length]) - - * Returns the sub binary from the given `binary` based on the given start offset with the optional `length`. - * Arguments: - * `binary` : a `binary` to be extracted, - * `offset` : a `tinyint`, `smallint`, `integer`, or `bigint` value - as the starting offset of the sub binary in `binary` (starting at 0), - * `length` : (Optional) a `tinyint`, `smallint`, `integer`, or `bigint` value - as the length of the sub binary. - * Return Value: - * a `binary` that represents the sub binary, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-binary value, - * or, the second argument is any other non-integer value, - * or, the third argument is any other non-integer value, if it is present. - - * Example: - - sub_binary(hex("AABBCCDD"), 4); - - * The expected result is - - hex("DD") - -### binary_concat ### - * Syntax: - - binary_concat(array) - - * Concatenates a binary `array` or `multiset` into a single binary. - * Arguments: - * `array` : an `array` or `multiset` of binaries (could be `null` or `missing`) to be concatenated. - * Return Value : - * the concatenated `binary` value, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * `missing` if any element in the input array is `missing`, - * `null` if any element in the input array is `null` but no element in the input array is `missing`, - * any other non-array input value or non-binary element in the input array will cause a type error. - - * Example: - - binary_concat([hex("42"), hex(""), hex('42')]); - - * The expected result is - - hex("4242") - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/4_spatial.md b/asterixdb/asterix-doc/src/main/markdown/builtins/4_spatial.md deleted file mode 100644 index c5268447274..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/4_spatial.md +++ /dev/null @@ -1,326 +0,0 @@ - - -## Spatial Functions ## -### create_point ### - * Syntax: - - create_point(x, y) - - * Creates the primitive type `point` using an `x` and `y` value. - * Arguments: - * `x` : a `double` that represents the x-coordinate, - * `y` : a `double` that represents the y-coordinate. - * Return Value: - * a `point` representing the ordered pair (`x`, `y`), - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-double input value will cause a type error. - - * Example: - - { "point": create_point(30.0,70.0) }; - - - * The expected result is: - - { "point": point("30.0,70.0") } - - -### create_line ### - * Syntax: - - create_line(point1, point2) - - * Creates the primitive type `line` using `point1` and `point2`. - * Arguments: - * `point1` : a `point` that represents the start point of the line. - * `point2` : a `point` that represents the end point of the line. - * Return Value: - * a spatial `line` created using the points provided in `point1` and `point2`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-point input value will cause a type error. - - * Example: - - { "line": create_line(create_point(30.0,70.0), create_point(50.0,90.0)) }; - - - * The expected result is: - - { "line": line("30.0,70.0 50.0,90.0") } - - -### create_rectangle ### - * Syntax: - - create_rectangle(point1, point2) - - * Creates the primitive type `rectangle` using `point1` and `point2`. - * Arguments: - * `point1` : a `point` that represents the lower_left point of the rectangle. - * `point2` : a `point` that represents the upper_right point of the rectangle. - * Return Value: - * a spatial `rectangle` created using the points provided in `point1` and `point2`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-point input value will cause a type error. - - * Example: - - { "rectangle": create_rectangle(create_point(30.0,70.0), create_point(50.0,90.0)) }; - - - * The expected result is: - - { "rectangle": rectangle("30.0,70.0 50.0,90.0") } - - -### create_circle ### - * Syntax: - - create_circle(point, radius) - - * Creates the primitive type `circle` using `point` and `radius`. - * Arguments: - * `point` : a `point` that represents the center of the circle. - * `radius` : a `double` that represents the radius of the circle. - * Return Value: - * a spatial `circle` created using the center point and the radius provided in `point` and `radius`. - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-point value, - * or, the second argument is any other non-double value. - - * Example: - - { "circle": create_circle(create_point(30.0,70.0), 5.0) } - - - * The expected result is: - - { "circle": circle("30.0,70.0 5.0") } - - -### create_polygon ### - * Syntax: - - create_polygon(array) - - * Creates the primitive type `polygon` using the double values provided in the argument `array`. - Each two consecutive double values represent a point starting from the first double value in the array. - Note that at least six double values should be specified, meaning a total of three points. - * Arguments: - * `array` : an array of doubles representing the points of the polygon. - * Return Value: - * a `polygon`, represents a spatial simple polygon created using the points provided in `array`. - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * `missing` if any element in the input array is `missing`, - * `null` if any element in the input array is `null` but no element in the input array is `missing`, - * any other non-array input value or non-double element in the input array will cause a type error. - - - * Example: - - { "polygon": create_polygon([1.0,1.0,2.0,2.0,3.0,3.0,4.0,4.0]) }; - - - * The expected result is: - - { "polygon": polygon("1.0,1.0 2.0,2.0 3.0,3.0 4.0,4.0") } - - -### get_x/get_y ### - * Syntax: - - get_x(point) or get_y(point) - - * Returns the x or y coordinates of a point `point`. - * Arguments: - * `point` : a `point`. - * Return Value: - * a `double` representing the x or y coordinates of the point `point`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-point input value will cause a type error. - - * Example: - - { "x_coordinate": get_x(create_point(2.3,5.0)), "y_coordinate": get_y(create_point(2.3,5.0)) }; - - - * The expected result is: - - { "x_coordinate": 2.3, "y_coordinate": 5.0 } - - -### get_points ### - * Syntax: - - get_points(spatial_object) - - * Returns an ordered array of the points forming the spatial object `spatial_object`. - * Arguments: - * `spatial_object` : a `point`, `line`, `rectangle`, `circle`, or `polygon`. - * Return Value: - * an `array` of the points forming the spatial object `spatial_object`, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-spatial-object input value will cause a type error. - - * Example: - - get_points(create_polygon([1.0,1.0,2.0,2.0,3.0,3.0,4.0,4.0])) - - * The expected result is: - - [ point("1.0,1.0"), point("2.0,2.0"), point("3.0,3.0"), point("4.0,4.0") ] - - -### get_center/get_radius ### - * Syntax: - - get_center(circle_expression) or get_radius(circle_expression) - - * Returns the center and the radius of a circle `circle_expression`, respectively. - * Arguments: - * `circle_expression` : a `circle`. - * Return Value: - * a `point` or `double`, represent the center or radius of the circle `circle_expression`. - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-circle input value will cause a type error. - - * Example: - - { - "circle_radius": get_radius(create_circle(create_point(6.0,3.0), 1.0)), - "circle_center": get_center(create_circle(create_point(6.0,3.0), 1.0)) - }; - - - * The expected result is: - - { "circle_radius": 1.0, "circle_center": point("6.0,3.0") } - - - -### spatial_distance ### - * Syntax: - - spatial_distance(point1, point2) - - * Returns the Euclidean distance between `point1` and `point2`. - * Arguments: - * `point1` : a `point`. - * `point2` : a `point`. - * Return Value: - * a `double` as the Euclidean distance between `point1` and `point2`. - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-point input value will cause a type error. - - * Example: - - spatial_distance(point("47.44,80.65"), create_point(30.0,70.0)); - - - * The expected result is: - - 20.434678857275934 - -### spatial_area ### - * Syntax: - - spatial_area(spatial_2d_expression) - - * Returns the spatial area of `spatial_2d_expression`. - * Arguments: - * `spatial_2d_expression` : a `rectangle`, `circle`, or `polygon`. - * Return Value: - * a `double` representing the area of `spatial_2d_expression`. - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-2d-spatial-object will cause a type error. - - * Example: - - spatial_area(create_circle(create_point(0.0,0.0), 5.0)); - - - * The expected result is: - - 78.53981625 - - -### spatial_intersect ### - * Syntax: - - spatial_intersect(spatial_object1, spatial_object2) - - * Checks whether `@arg1` and `@arg2` spatially intersect each other. - * Arguments: - * `spatial_object1` : a `point`, `line`, `rectangle`, `circle`, or `polygon`. - * `spatial_object2` : a `point`, `line`, `rectangle`, `circle`, or `polygon`. - * Return Value: - * a `boolean` representing whether `spatial_object1` and `spatial_object2` spatially overlap with each other, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-spatial-object input value will cause a type error. - - * Example: - - spatial_intersect(point("39.28,70.48"), create_rectangle(create_point(30.0,70.0), create_point(40.0,80.0))); - - - * The expected result is: - - true - -### spatial_cell ### - * Syntax: - - spatial_cell(point1, point2, x_increment, y_increment) - - * Returns the grid cell that `point1` belongs to. - * Arguments: - * `point1` : a `point` representing the point of interest that its grid cell will be returned. - * `point2` : a `point` representing the origin of the grid. - * `x_increment` : a `double`, represents X increments. - * `y_increment` : a `double`, represents Y increments. - * Return Value: - * a `rectangle` representing the grid cell that `point1` belongs to, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first or second argument is any other non-point value, - * or, the second or third argument is any other non-double value. - - * Example: - - spatial_cell(point("39.28,70.48"), create_point(20.0,50.0), 5.5, 6.0); - - - * The expected result is: - - rectangle("36.5,68.0 42.0,74.0"); - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/5_similarity.md b/asterixdb/asterix-doc/src/main/markdown/builtins/5_similarity.md deleted file mode 100644 index cb3318fc04b..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/5_similarity.md +++ /dev/null @@ -1,176 +0,0 @@ - - -## Similarity Functions ## - -AsterixDB supports queries with different similarity functions, -including [edit distance](http://en.wikipedia.org/wiki/Levenshtein_distance) and -[Jaccard](https://en.wikipedia.org/wiki/Jaccard_index). - -### edit_distance ### - * Syntax: - - edit_distance(expression1, expression2) - - * Returns the edit distance of `expression1` and `expression2`. - * Arguments: - * `expression1` : a `string` or a homogeneous `array` of a comparable item type. - * `expression2` : The same type as `expression1`. - * Return Value: - * an `bigint` that represents the edit distance between `expression1` and `expression2`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-string input value will cause a type error. - * Note: an [n_gram index](similarity.html#UsingIndexesToSupportSimilarityQueries) can be utilized for this function. - * Example: - - edit_distance("SuzannaTillson", "Suzanna Tilson"); - - - * The expected result is: - - 2 - -### edit_distance_check ### -* Syntax: - - edit_distance_check(expression1, expression2, threshold) - -* Checks whether the edit distance of `expression1` and `expression2` is within a given threshold. - -* Arguments: - * `expression1` : a `string` or a homogeneous `array` of a comparable item type. - * `expression2` : The same type as `expression1`. - * `threshold` : a `bigint` that represents the distance threshold. -* Return Value: - * an `array` with two items: - * The first item contains a `boolean` value representing whether the edit distance of `expression1` and `expression2` is within the given threshold. - * The second item contains an `integer` that represents the edit distance of `expression1` and `expression2` if the first item is true. - * If the first item is false, then the second item is set to 2147483647. - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first or second argument is any other non-string value, - * or, the third argument is any other non-bigint value. -* Note: an [n_gram index](similarity.html#UsingIndexesToSupportSimilarityQueries) can be utilized for this function. -* Example: - - edit_distance_check("happy","hapr",2); - - -* The expected result is: - - [ true, 2 ] - -### edit_distance_contains ### -* Syntax: - - edit_distance_contains(expression1, expression2, threshold) - -* Checks whether `expression1` contains `expression2` with an [edit distance](http://en.wikipedia.org/wiki/Levenshtein_distance) within a given threshold. - -* Arguments: - * `expression1` : a `string` or a homogeneous `array` of a comparable item type. - * `expression2` : The same type as `expression1`. - * `threshold` : a `bigint` that represents the distance threshold. -* Return Value: - * an `array` with two items: - * The first item contains a `boolean` value representing whether `expression1` can contain `expression2`. - * The second item contains an `integer` that represents the required edit distance for `expression1` to contain - `expression2` if the first item is true. - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first or second argument is any other non-string value, - * or, the third argument is any other non-bigint value. -* Note: an [n_gram index](similarity.html#UsingIndexesToSupportSimilarityQueries) can be utilized for this function. -* Example: - - edit_distance_contains("happy","hapr",2); - - -* The expected result is: - - [ true, 1 ] - - - -### similarity_jaccard ### - * Syntax: - - similarity_jaccard(array1, array2) - - * Returns the [Jaccard similarity](http://en.wikipedia.org/wiki/Jaccard_index) of `array1` and `array2`. - * Arguments: - * `array1` : an `array` or `multiset`. - * `array2` : an `array` or `multiset`. - * Return Value: - * a `float` that represents the Jaccard similarity of `array1` and `array2`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * `missing` if any element in any input array is `missing`, - * `null` if any element in any input array is `null` but no element in the input array is `missing`, - * any other non-array input value or non-integer element in any input array will cause a type error. - - * Note: a [keyword index](similarity.html#UsingIndexesToSupportSimilarityQueries) can be utilized for this function. - * Example: - - similarity_jaccard([1,5,8,9], [1,5,9,10]); - - - * The expected result is: - - 0.6 - - -### similarity_jaccard_check ### - * Syntax: - - similarity_jaccard_check(array1, array2, threshold) - - * Checks whether `array1` and `array2` have a [Jaccard similarity](http://en.wikipedia.org/wiki/Jaccard_index) greater than or equal to threshold. Again, the “check” version of Jaccard is faster than the "non_check" version. - - * Arguments: - * `array1` : an `array` or `multiset`. - * `array2` : an `array` or `multiset`. - * `threshold` : a `double` that represents the similarity threshold. - * Return Value: - * an `array` with two items: - * The first item contains a `boolean` value representing whether `array1` and `array2` are similar. - * The second item contains a `float` that represents the Jaccard similarity of `array1` and `array2` - if it is greater than or equal to the threshold, or 0 otherwise. - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * `missing` if any element in any input array is `missing`, - * `null` if any element in any input array is `null` but no element in the input array is `missing`, - * a type error will be raised if: - * the first or second argument is any other non-array value, - * or, the third argument is any other non-double value. - - * Note: a [keyword index](similarity.html#UsingIndexesToSupportSimilarityQueries) can be utilized for this function. - * Example: - - similarity_jaccard_check([1,5,8,9], [1,5,9,10], 0.6); - - - * The expected result is: - - [ false, 0.0 ] - - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/6_tokenizing.md b/asterixdb/asterix-doc/src/main/markdown/builtins/6_tokenizing.md deleted file mode 100644 index 4783cc80a09..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/6_tokenizing.md +++ /dev/null @@ -1,45 +0,0 @@ - - -## Tokenizing Functions ## -### word_tokens ### - - - * Syntax: - - word_tokens(string) - - * Returns an array of word tokens of `string` using non_alphanumeric characters as delimiters. - * Arguments: - * `string` : a `string` that will be tokenized. - * Return Value: - * an `array` of `string` word tokens, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-string input value will cause a type error. - - * Example: - - word_tokens("I like the phone, awesome!"); - - - * The expected result is: - - [ "i", "like", "the", "phone", "awesome" ] - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/7_allens.md b/asterixdb/asterix-doc/src/main/markdown/builtins/7_allens.md deleted file mode 100644 index e84ec979334..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/7_allens.md +++ /dev/null @@ -1,275 +0,0 @@ - - -### interval_before, interval_after ### - - * Syntax: - - interval_before(interval1, interval2) - interval_after(interval1, interval2) - - * These two functions check whether an interval happens before/after another interval. - * Arguments: - * `interval1`, `interval2`: two intervals to be compared - * Return Value: - * a `boolean` value. Specifically, `interval_before(interval1, interval2)` is true if and - only if `interval1.end < interval2.start`, and `interval_after(interval1, interval2)` is true - if and only if `interval1.start > interval2.end`. - * `missing` if the argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-interval input value will cause a type error. - - * Examples: - - { - "interval_before": interval_before(interval(date("2000-01-01"), date("2005-01-01")), - interval(date("2005-05-01"), date("2012-09-09"))), - "interval_after": interval_after(interval(date("2005-05-01"), date("2012-09-09")), - interval(date("2000-01-01"), date("2005-01-01"))) - }; - - * The expected result is: - - { "interval_before": true, "interval_after": true } - - -### interval_covers, interval_covered_by ### - - * Syntax: - - interval_covers(interval1, interval2) - interval_covered_by(interval1, interval2) - - * These two functions check whether one interval covers the other interval. - * Arguments: - * `interval1`, `interval2`: two intervals to be compared - * Return Value: - * a `boolean` value. Specifically, `interval_covers(interval1, interval2)` is true if and only if - - interval1.start <= interval2.start AND interval1.end >= interval2.end - - `interval_covered_by(interval1, interval2)` is true if and only if - - interval2.start <= interval1.start AND interval2.end >= interval1.end - - * `missing` if the argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-interval input value will cause a type error. - - * Examples: - - { - "interval_covers": interval_covers(interval(date("2000-01-01"), date("2005-01-01")), - interval(date("2000-03-01"), date("2004-09-09"))), - "interval_covered_by": interval_covered_by(interval(date("2006-08-01"), date("2007-03-01")), - interval(date("2004-09-10"), date("2012-08-01"))) - }; - - * The expected result is: - - { "interval_covers": true, "interval_covered_by": true } - - -### interval_overlaps, interval_overlapped_by ### - - * Syntax: - - interval_overlaps(interval1, interval2) - interval_overlapped_by(interval1, interval2) - - * These functions check whether two intervals overlap with each other. - * Arguments: - * `interval1`, `interval2`: two intervals to be compared - * Return Value: - - * a `boolean` value. Specifically, `interval_overlaps(interval1, interval2)` is true if and only if - - interval1.start < interval2.start - AND interval2.end > interval1.end - AND interval1.end > interval2.start - - `interval_overlapped_by(interval1, interval2)` is true if and only if - - interval2.start < interval1.start - AND interval1.end > interval2.end - AND interval2.end > interval1.start - - * `missing` if the argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-interval input value will cause a type error. - - Note that `interval_overlaps` and `interval_overlapped_by` are following the Allen's relations on the definition of overlap. - - * Examples: - - { - "overlaps": interval_overlaps(interval(date("2000-01-01"), date("2005-01-01")), - interval(date("2004-05-01"), date("2012-09-09"))), - "overlapped_by": interval_overlapped_by(interval(date("2006-08-01"), date("2007-03-01")), - interval(date("2004-05-01"), date("2012-09-09")))) - }; - - * The expected result is: - - { "overlaps": true, "overlapped_by": true } - - -### interval_overlapping ### -Note that `interval_overlapping` is not an Allen's Relation, but syntactic sugar we added for the case that the intersect of two intervals is not empty. Basically this function returns true if any of these functions return true: `interval_overlaps`, `interval_overlapped_by`, `interval_covers`, or `interval_covered_by`. - - * Syntax: - - interval_overlapping(interval1, interval2) - - * This functions check whether two intervals share any points with each other. - * Arguments: - * `interval1`, `interval2`: two intervals to be compared - * Return Value: - * a `boolean` value. Specifically, `interval_overlapping(interval1, interval2)` is true if - - interval1.start < interval2.end - AND interval1.end > interval2.start - - * `missing` if the argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-interval input value will cause a type error. - - * Examples: - - { - "overlapping1": interval_overlapping(interval(date("2000-01-01"), date("2005-01-01")), - interval(date("2004-05-01"), date("2012-09-09"))), - "overlapping2": interval_overlapping(interval(date("2006-08-01"), date("2007-03-01")), - interval(date("2004-09-10"), date("2006-12-31"))) - }; - - * The expected result is: - - { "overlapping1": true, "overlapping2": true } - - -### interval_meets, interval_met_by ### - - * Syntax: - - interval_meets(interval1, interval2) - interval_met_by(interval1, interval2) - - * These two functions check whether an interval meets with another interval. - * Arguments: - * `interval1`, `interval2`: two intervals to be compared - * Return Value: - * a `boolean` value. Specifically, `interval_meets(interval1, interval2)` is true if and only if - `interval1.end = interval2.start`, and `interval_met_by(interval1, interval2)` is true if and only - if `interval1.start = interval2.end`. If any of the two inputs is `null`, `null` is returned. - * `missing` if the argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-interval input value will cause a type error. - - * Examples: - - { - "meets": interval_meets(interval(date("2000-01-01"), date("2005-01-01")), - interval(date("2005-01-01"), date("2012-09-09"))), - "metby": interval_met_by(interval(date("2006-08-01"), date("2007-03-01")), - interval(date("2004-09-10"), date("2006-08-01"))) - }; - - * The expected result is: - - { "meets": true, "metby": true } - - -### interval_starts, interval_started_by ### - - * Syntax: - - interval_starts(interval1, interval2) - interval_started_by(interval1, interval2) - - * These two functions check whether one interval starts with the other interval. - * Arguments: - * `interval1`, `interval2`: two intervals to be compared - * Return Value: - * a `boolean` value. Specifically, `interval_starts(interval1, interval2)` returns true if and only if - - interval1.start = interval2.start - AND interval1.end <= interval2.end - - `interval_started_by(interval1, interval2)` returns true if and only if - - interval1.start = interval2.start - AND interval2.end <= interval1.end - - * `missing` if the argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-interval input value will cause a type error. - - * Examples: - - { - "interval_starts": interval_starts(interval(date("2000-01-01"), date("2005-01-01")), - interval(date("2000-01-01"), date("2012-09-09"))), - "interval_started_by": interval_started_by(interval(date("2006-08-01"), date("2007-03-01")), - interval(date("2006-08-01"), date("2006-08-02"))) - }; - - * The expected result is: - - { "interval_starts": true, "interval_started_by": true } - - -### interval_ends, interval_ended_by ### - -* Syntax: - - interval_ends(interval1, interval2) - interval_ended_by(interval1, interval2) - - * These two functions check whether one interval ends with the other interval. - * Arguments: - * `interval1`, `interval2`: two intervals to be compared - * Return Value: - * a `boolean` value. Specifically, `interval_ends(interval1, interval2)` returns true if and only if - - interval1.end = interval2.end - AND interval1.start >= interval2.start - - `interval_ended_by(interval1, interval2)` returns true if and only if - - interval2.end = interval1.end - AND interval2.start >= interval1.start - - * `missing` if the argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-interval input value will cause a type error. - -* Examples: - - { - "interval_ends": interval_ends(interval(date("2000-01-01"), date("2005-01-01")), - interval(date("1998-01-01"), date("2005-01-01"))), - "interval_ended_by": interval_ended_by(interval(date("2006-08-01"), date("2007-03-01")), - interval(date("2006-09-10"), date("2007-03-01"))) - }; - -* The expected result is: - - { "interval_ends": true, "interval_ended_by": true } - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/7_temporal.md b/asterixdb/asterix-doc/src/main/markdown/builtins/7_temporal.md deleted file mode 100644 index ab8b7534c5f..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/7_temporal.md +++ /dev/null @@ -1,803 +0,0 @@ - - -## Temporal Functions ## - -### get_year/get_month/get_day/get_hour/get_minute/get_second/get_millisecond ### - * Syntax: - - get_year/get_month/get_day/get_hour/get_minute/get_second/get_millisecond(temporal_value) - - * Accessors for accessing fields in a temporal value - * Arguments: - * `temporal_value` : a temporal value represented as one of the following types: `date`, `datetime`, `time`, and `duration`. - * Return Value: - * an `bigint` value representing the field to be extracted, - * `missing` if the argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-interval input value will cause a type error. - - * Example: - - { - "year": get_year(date("2010-10-30")), - "month": get_month(datetime("1987-11-19T23:49:23.938")), - "day": get_day(date("2010-10-30")), - "hour": get_hour(time("12:23:34.930+07:00")), - "min": get_minute(duration("P3Y73M632DT49H743M3948.94S")), - "second": get_second(datetime("1987-11-19T23:49:23.938")), - "ms": get_millisecond(duration("P3Y73M632DT49H743M3948.94S")) - }; - - - * The expected result is: - - { "year": 2010, "month": 11, "day": 30, "hour": 5, "min": 28, "second": 23, "ms": 94 } - - -### adjust_datetime_for_timezone ### - * Syntax: - - adjust_datetime_for_timezone(datetime, string) - - * Adjusts the given datetime `datetime` by applying the timezone information `string`. - * Arguments: - * `datetime` : a `datetime` value to be adjusted. - * `string` : a `string` representing the timezone information. - * Return Value: - * a `string` value representing the new datetime after being adjusted by the timezone information, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-datetime value, - * or, the second argument is any other non-string value. - - * Example: - - adjust_datetime_for_timezone(datetime("2008-04-26T10:10:00"), "+08:00"); - - - * The expected result is: - - "2008-04-26T18:10:00.000+08:00" - - -### adjust_time_for_timezone ### - * Syntax: - - adjust_time_for_timezone(time, string) - - * Adjusts the given time `time` by applying the timezone information `string`. - * Arguments: - * `time` : a `time` value to be adjusted. - * `string` : a `string` representing the timezone information. - * Return Value: - * a `string` value representing the new time after being adjusted by the timezone information, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-time value, - * or, the second argument is any other non-string value. - - * Example: - - adjust_time_for_timezone(get_time_from_datetime(datetime("2008-04-26T10:10:00")), "+08:00"); - - - * The expected result is: - - "18:10:00.000+08:00" - - -### calendar_duration_from_datetime ### - * Syntax: - - calendar_duration_from_datetime(datetime, duration_value) - - * Gets a user_friendly representation of the duration `duration_value` based on the given datetime `datetime`. - * Arguments: - * `datetime` : a `datetime` value to be used as the reference time point. - * `duration_value` : a `duration` value to be converted. - * Return Value: - * a `duration` value with the duration as `duration_value` but with a user_friendly representation, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-datetime value, - * or, the second argument is any other non-duration input value. - - * Example: - - calendar_duration_from_datetime( - datetime("2016-03-26T10:10:00"), - datetime("2016-03-26T10:10:00") - datetime("2011-01-01T00:00:00") - ); - - * The expected result is: - - duration("P5Y2M24DT10H10M") - - -### get_year_month_duration/get_day_time_duration ### - * Syntax: - - get_year_month_duration/get_day_time_duration(duration_value) - - * Extracts the correct `duration` subtype from `duration_value`. - * Arguments: - * `duration_value` : a `duration` value to be converted. - * Return Value: - * a `year_month_duration` value or a `day_time_duration` value, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-duration input value will cause a type error. - - * Example: - - get_year_month_duration(duration("P12M50DT10H")); - - - * The expected result is: - - year_month_duration("P1Y") - -### months_from_year_month_duration/ms_from_day_time_duration ### -* Syntax: - - months_from_year_month_duration/ms_from_day_time_duration(duration_value) - -* Extracts the number of months or the number of milliseconds from the `duration` subtype. -* Arguments: - * `duration_value` : a `duration` of the correct subtype. -* Return Value: - * a `bigint` representing the number of months/milliseconds, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-duration input value will cause a type error. - -* Example: - - { - "months": months_from_year_month_duration(get_year_month_duration(duration("P5Y7MT50M"))), - "milliseconds": ms_from_day_time_duration(get_day_time_duration(duration("P5Y7MT50M"))) - }; - -* The expected result is: - - {"months": 67, "milliseconds": 3000000} - - -### duration_from_months/duration_from_ms ### -* Syntax: - - duration_from_months/duration_from_ms(number_value) - -* Creates a `duration` from `number_value`. -* Arguments: - * `number_value` : a `bigint` representing the number of months/milliseconds -* Return Value: - * a `duration` containing `number_value` value for months/milliseconds, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-duration input value will cause a type error. - -* Example: - - duration_from_months(8); - -* The expected result is: - - duration("P8M") - - -### duration_from_interval ### -* Syntax: - - duration_from_interval(interval_value) - -* Creates a `duration` from `interval_value`. -* Arguments: - * `interval_value` : an `interval` value -* Return Value: - * a `duration` representing the time in the `interval_value` - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-duration input value will cause a type error. - -* Example: - - { - "dr1" : duration_from_interval(interval(date("2010-10-30"), date("2010-12-21"))), - "dr2" : duration_from_interval(interval(datetime("2012-06-26T01:01:01.111"), datetime("2012-07-27T02:02:02.222"))), - "dr3" : duration_from_interval(interval(time("12:32:38"), time("20:29:20"))), - "dr4" : duration_from_interval(null) - }; - -* The expected result is: - - { - "dr1": day_time_duration("P52D"), - "dr2": day_time_duration("P31DT1H1M1.111S"), - "dr3": day_time_duration("PT7H56M42S"), - "dr4": null - } - - -### current_date ### - * Syntax: - - current_date() - - * Gets the current date. - * Arguments: None - * Return Value: - * a `date` value of the date when the function is called. - -### current_time ### - * Syntax: - - current_time() - - * Get the current time - * Arguments: None - * Return Value: - * a `time` value of the time when the function is called. - -### current_datetime ### - * Syntax: - - current_datetime() - - * Get the current datetime - * Arguments: None - * Return Value: - * a `datetime` value of the datetime when the function is called. - - -### get_date_from_datetime ### - * Syntax: - - get_date_from_datetime(datetime) - - * Gets the date value from the given datetime value `datetime`. - * Arguments: - * `datetime`: a `datetime` value to be extracted from. - * Return Value: - * a `date` value from the datetime, - * any other non-datetime input value will cause a type error. - -### get_time_from_datetime ### - * Syntax: - - get_time_from_datetime(datetime) - - * Get the time value from the given datetime value `datetime` - * Arguments: - * `datetime`: a `datetime` value to be extracted from. - * Return Value: - * a `time` value from the datetime. - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-datetime input value will cause a type error. - - * Example: - - get_time_from_datetime(datetime("2016-03-26T10:10:00")); - - * The expected result is: - - time("10:10:00.000Z") - - -### day_of_week ### -* Syntax: - - day_of_week(date) - -* Finds the day of the week for a given date (1_7) -* Arguments: - * `date`: a `date` value (Can also be a `datetime`) -* Return Value: - * an `tinyint` representing the day of the week (1_7), - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-date input value will cause a type error. - -* Example: - - day_of_week(datetime("2012-12-30T12:12:12.039Z")); - - -* The expected result is: - - 7 - - -### date_from_unix_time_in_days ### - * Syntax: - - date_from_unix_time_in_days(numeric_value) - - * Gets a date representing the time after `numeric_value` days since 1970_01_01. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint` value representing the number of days. - * Return Value: - * a `date` value as the time after `numeric_value` days since 1970-01-01, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - -### datetime_from_unix_time_in_ms ### - * Syntax: - - datetime_from_unix_time_in_ms(numeric_value) - - * Gets a datetime representing the time after `numeric_value` milliseconds since 1970_01_01T00:00:00Z. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint` value representing the number of milliseconds. - * Return Value: - * a `datetime` value as the time after `numeric_value` milliseconds since 1970-01-01T00:00:00Z, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - -### datetime_from_unix_time_in_secs ### - * Syntax: - - datetime_from_unix_time_in_secs(numeric_value) - - * Gets a datetime representing the time after `numeric_value` seconds since 1970_01_01T00:00:00Z. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint` value representing the number of seconds. - * Return Value: - * a `datetime` value as the time after `numeric_value` seconds since 1970_01_01T00:00:00Z, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - -### datetime_from_date_time ### -* Syntax: - -datetime_from_date_time(date,time) - -* Gets a datetime representing the combination of `date` and `time` - * Arguments: - * `date`: a `date` value - * `time` a `time` value -* Return Value: - * a `datetime` value by combining `date` and `time`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if - * the first argument is any other non-date value, - * or, the second argument is any other non-time value. - -### time_from_unix_time_in_ms ### - * Syntax: - - time_from_unix_time_in_ms(numeric_value) - - * Gets a time representing the time after `numeric_value` milliseconds since 00:00:00.000Z. - * Arguments: - * `numeric_value`: a `tinyint`/`smallint`/`integer`/`bigint` value representing the number of milliseconds. - * Return Value: - * a `time` value as the time after `numeric_value` milliseconds since 00:00:00.000Z, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-numeric input value will cause a type error. - - * Example: - - { - "date": date_from_unix_time_in_days(15800), - "datetime": datetime_from_unix_time_in_ms(1365139700000), - "time": time_from_unix_time_in_ms(3748) - }; - - - * The expected result is: - - { "date": date("2013-04-05"), "datetime": datetime("2013-04-05T05:28:20.000Z"), "time": time("00:00:03.748Z") } - - -### unix_time_from_date_in_days ### - * Syntax: - - unix_time_from_date_in_days(date_value) - - * Gets an integer value representing the number of days since 1970_01_01 for `date_value`. - * Arguments: - * `date_value`: a `date` value. - * Return Value: - * a `bigint` value representing the number of days, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-date input value will cause a type error. - - -### unix_time_from_datetime_in_ms ### - * Syntax: - - unix_time_from_datetime_in_ms(datetime_value) - - * Gets an integer value representing the time in milliseconds since 1970_01_01T00:00:00Z for `datetime_value`. - * Arguments: - * `datetime_value` : a `datetime` value. - * Return Value: - * a `bigint` value representing the number of milliseconds, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-datetime input value will cause a type error. - - -### unix_time_from_datetime_in_secs ### - * Syntax: - - unix_time_from_datetime_in_secs(datetime_value) - - * Gets an integer value representing the time in seconds since 1970_01_01T00:00:00Z for `datetime_value`. - * Arguments: - * `datetime_value` : a `datetime` value. - * Return Value: - * a `bigint` value representing the number of seconds, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-datetime input value will cause a type error. - - -### unix_time_from_time_in_ms ### - * Syntax: - - unix_time_from_time_in_ms(time_value) - - * Gets an integer value representing the time the milliseconds since 00:00:00.000Z for `time_value`. - * Arguments: - * `time_value` : a `time` value. - * Return Value: - * a `bigint` value representing the number of milliseconds, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-datetime input value will cause a type error. - - * Example: - - { - "date": date_from_unix_time_in_days(15800), - "datetime": datetime_from_unix_time_in_ms(1365139700000), - "time": time_from_unix_time_in_ms(3748) - } - - - * The expected result is: - - { "date": date("2013-04-05"), "datetime": datetime("2013-04-05T05:28:20.000Z"), "time": time("00:00:03.748Z") } - - -### parse_date/parse_time/parse_datetime ### -* Syntax: - -parse_date/parse_time/parse_datetime(date,formatting_expression) - -* Creates a `date/time/date_time` value by treating `date` with formatting `formatting_expression` -* Arguments: - * `date`: a `string` value representing the `date/time/datetime`. - * `formatting_expression` a `string` value providing the formatting for `date_expression`.Characters used to create date expression: - * `h` hours - * `m` minutes - * `s` seconds - * `n` milliseconds - * `a` am/pm - * `z` timezone - * `Y` year - * `M` month - * `D` day - * `W` weekday - * `_`, `'`, `/`, `.`, `,`, `T` seperators for both time and date -* Return Value: - * a `date/time/date_time` value corresponding to `date`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-date value, - * the second argument is any other non-string value. - -* Example: - - parse_time("30:30","m:s"); - -* The expected result is: - - time("00:30:30.000Z") - - -### print_date/print_time/print_datetime ### -* Syntax: - - print_date/print_time/print_datetime(date,formatting_expression) - -* Creates a `string` representing a `date/time/date_time` value of the `date` using the formatting `formatting_expression` -* Arguments: - * `date`: a `date/time/datetime` value. - * `formatting_expression` a `string` value providing the formatting for `date_expression`. Characters used to create date expression: - * `h` hours - * `m` minutes - * `s` seconds - * `n` milliseconds - * `a` am/pm - * `z` timezone - * `Y` year - * `M` month - * `D` day - * `W` weekday - * `_`, `'`, `/`, `.`, `,`, `T` seperators for both time and date -* Return Value: - * a `string` value corresponding to `date`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-date value, - * the second argument is any other non-string value. - -* Example: - - print_time(time("00:30:30.000Z"),"m:s"); - -* The expected result is: - - "30:30" - - -### get_interval_start, get_interval_end ### - * Syntax: - - get_interval_start/get_interval_end(interval) - - * Gets the start/end of the given interval. - * Arguments: - * `interval`: the interval to be accessed. - * Return Value: - * a `time`, `date`, or `datetime` (depending on the time instances of the interval) representing the starting - or ending time, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-interval value will cause a type error. - - * Example: - - { - "start": get_interval_start(interval_start_from_date("1984-01-01", "P1Y")), - "end": get_interval_end(interval_start_from_date("1984-01-01", "P1Y")) - }; - - - * The expected result is: - - { "start": date("1984_01_01"), "end": date("1985_01_01") } - - -### get_interval_start_date/get_interval_start_datetimeget_interval_start_time, get_interval_end_date/get_interval_end_datetime/get_interval_end_time ### - * Syntax: - - get_interval_start_date/get_interval_start_datetime/get_interval_start_time/get_interval_end_date/get_interval_end_datetime/get_interval_end_time(interval) - - * Gets the start/end of the given interval for the specific date/datetime/time type. - * Arguments: - * `interval`: the interval to be accessed. - * Return Value: - * a `time`, `date`, or `datetime` (depending on the function) representing the starting or ending time, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-interval value will cause a type error. - - * Example: - - { - "start1": get_interval_start_date(interval_start_from_date("1984-01-01", "P1Y")), - "end1": get_interval_end_date(interval_start_from_date("1984-01-01", "P1Y")), - "start2": get_interval_start_datetime(interval_start_from_datetime("1984-01-01T08:30:00.000", "P1Y1H")), - "end2": get_interval_end_datetime(interval_start_from_datetime("1984-01-01T08:30:00.000", "P1Y1H")), - "start3": get_interval_start_time(interval_start_from_time("08:30:00.000", "P1H")), - "end3": get_interval_end_time(interval_start_from_time("08:30:00.000", "P1H")) - }; - - - * The expected result is: - - { - "start1": date("1984-01-01"), - "end1": date("1985-01-01"), - "start2": datetime("1984-01-01T08:30:00.000Z"), - "end2": datetime("1985-01-01T09:30:00.000Z"), - "start3": time("08:30:00.000Z"), - "end3": time("09:30:00.000Z") - } - - -### get_overlapping_interval ### - * Syntax: - - get_overlapping_interval(interval1, interval2) - - * Gets the start/end of the given interval for the specific date/datetime/time type. - * Arguments: - * `interval1`: an `interval` value - * `interval2`: an `interval` value - * Return Value: - * an `interval` that is overlapping `interval1` and `interval2`. - If `interval1` and `interval2` do not overlap `null` is returned. Note each interval must be of the same type. - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-interval input value will cause a type error. - - * Example: - - { "overlap1": get_overlapping_interval(interval(time("11:23:39"), time("18:27:19")), interval(time("12:23:39"), time("23:18:00"))), - "overlap2": get_overlapping_interval(interval(time("12:23:39"), time("18:27:19")), interval(time("07:19:39"), time("09:18:00"))), - "overlap3": get_overlapping_interval(interval(date("1980-11-30"), date("1999-09-09")), interval(date("2013-01-01"), date("2014-01-01"))), - "overlap4": get_overlapping_interval(interval(date("1980-11-30"), date("2099-09-09")), interval(date("2013-01-01"), date("2014-01-01"))), - "overlap5": get_overlapping_interval(interval(datetime("1844-03-03T11:19:39"), datetime("2000-10-30T18:27:19")), interval(datetime("1989-03-04T12:23:39"), datetime("2009-10-10T23:18:00"))), - "overlap6": get_overlapping_interval(interval(datetime("1989-03-04T12:23:39"), datetime("2000-10-30T18:27:19")), interval(datetime("1844-03-03T11:19:39"), datetime("1888-10-10T23:18:00"))) - }; - - * The expected result is: - - { "overlap1": interval(time("12:23:39.000Z"), time("18:27:19.000Z")), - "overlap2": null, - "overlap3": null, - "overlap4": interval(date("2013-01-01"), date("2014_01_01")), - "overlap5": interval(datetime("1989-03-04T12:23:39.000Z"), datetime("2000-10-30T18:27:19.000Z")), - "overlap6": null - } - -### interval_bin ### - * Syntax: - - interval_bin(time_to_bin, time_bin_anchor, duration_bin_size) - - * Returns the `interval` value representing the bin containing the `time_to_bin` value. - * Arguments: - * `time_to_bin`: a date/time/datetime value representing the time to be binned. - * `time_bin_anchor`: a date/time/datetime value representing an anchor of a bin starts. The type of this argument should be the same as the first `time_to_bin` argument. - * `duration_bin_size`: the duration value representing the size of the bin, in the type of year_month_duration or day_time_duration. The type of this duration should be compatible with the type of `time_to_bin`, so that the arithmetic operation between `time_to_bin` and `duration_bin_size` is well_defined. Currently AsterixDB supports the following arithmetic operations: - * datetime +|_ year_month_duration - * datetime +|_ day_time_duration - * date +|_ year_month_duration - * date +|_ day_time_duration - * time +|_ day_time_duration - * Return Value: - * a `interval` value representing the bin containing the `time_to_bin` value. Note that the internal type of - this interval value should be the same as the `time_to_bin` type, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument or the second argument is any other non-date/non-time/non-datetime value, - * or, the second argument is any other non-year_month_duration/non-day_time_duration value. - - * Example: - - { - "bin1": interval_bin(date("2010-10-30"), date("1990-01-01"), year_month_duration("P1Y")), - "bin2": interval_bin(datetime("1987-11-19T23:49:23.938"), datetime("1990-01-01T00:00:00.000Z"), year_month_duration("P6M")), - "bin3": interval_bin(time("12:23:34.930+07:00"), time("00:00:00"), day_time_duration("PT1M")), - "bin4": interval_bin(datetime("1987-11-19T23:49:23.938"), datetime("2013-01-01T00:00:00.000"), day_time_duration("PT24H")) - }; - - * The expected result is: - - { - "bin1": interval(date("2010-01-01"),date("2011-01-01")), - "bin2": interval(datetime("1987-07-01T00:00:00.000Z"), datetime("1988-01-01T00:00:00.000Z")), - "bin3": interval(time("05:23:00.000Z"), time("05:24:00.000Z")), - "bin4": interval(datetime("1987-11-19T00:00:00.000Z"), datetime("1987-11-20T00:00:00.000Z")) - } - - -### interval_start_from_date/time/datetime ### - * Syntax: - - interval_start_from_date/time/datetime(date/time/datetime, duration) - - * Construct an `interval` value by the given starting `date`/`time`/`datetime` and the `duration` that the interval lasts. - * Arguments: - * `date/time/datetime`: a `string` representing a `date`, `time` or `datetime`, or a `date`/`time`/`datetime` value, representing the starting time point. - * `duration`: a `string` or `duration` value representing the duration of the interval. Note that duration cannot be negative value. - * Return Value: - * an `interval` value representing the interval starting from the given time point with the length of duration, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument or the second argument is any other non-date/non-time/non-datetime value, - * or, the second argument is any other non-duration value. - - * Example: - - { - "interval1": interval_start_from_date("1984-01-01", "P1Y"), - "interval2": interval_start_from_time(time("02:23:28.394"), "PT3H24M"), - "interval3": interval_start_from_datetime("1999-09-09T09:09:09.999", duration("P2M30D")) - }; - - * The expectecd result is: - - { - "interval1": interval(date("1984-01-01"), date("1985-01-01")), - "interval2": interval(time("02:23:28.394Z"), time("05:47:28.394Z")), - "interval3": interval(datetime("1999-09-09T09:09:09.999Z"), datetime("1999-12-09T09:09:09.999Z")) - } - - -### overlap_bins ### - * Return Value: - * a `interval` value representing the bin containing the `time_to_bin` value. Note that the internal type of this interval value should be the same as the `time_to_bin` type. - - * Syntax: - - overlap_bins(interval, time_bin_anchor, duration_bin_size) - - * Returns an ordered list of `interval` values representing each bin that is overlapping the `interval`. - * Arguments: - * `interval`: an `interval` value - * `time_bin_anchor`: a date/time/datetime value representing an anchor of a bin starts. The type of this argument should be the same as the first `time_to_bin` argument. - * `duration_bin_size`: the duration value representing the size of the bin, in the type of year_month_duration or day_time_duration. The type of this duration should be compatible with the type of `time_to_bin`, so that the arithmetic operation between `time_to_bin` and `duration_bin_size` is well_defined. Currently AsterixDB supports the following arithmetic operations: - * datetime +|_ year_month_duration - * datetime +|_ day_time_duration - * date +|_ year_month_duration - * date +|_ day_time_duration - * time +|_ day_time_duration - * Return Value: - * a ordered list of `interval` values representing each bin that is overlapping the `interval`. - Note that the internal type as `time_to_bin` and `duration_bin_size`. - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first arugment is any other non-interval value, - * or, the second argument is any other non-date/non-time/non-datetime value, - * or, the second argument is any other non-year_month_duration/non-day_time_duration value. - - * Example: - - { - "timebins": overlap_bins(interval(time("17:23:37"), time("18:30:21")), time("00:00:00"), day_time_duration("PT30M")), - "datebins": overlap_bins(interval(date("1984-03-17"), date("2013-08-22")), date("1990-01-01"), year_month_duration("P10Y")), - "datetimebins": overlap_bins(interval(datetime("1800-01-01T23:59:48.938"), datetime("2015-07-26T13:28:30.218")), - datetime("1900-01-01T00:00:00.000"), year_month_duration("P100Y")) - }; - - * The expected result is: - - { - "timebins": [ - interval(time("17:00:00.000Z"), time("17:30:00.000Z")), - interval(time("17:30:00.000Z"), time("18:00:00.000Z")), - interval(time("18:00:00.000Z"), time("18:30:00.000Z")), - interval(time("18:30:00.000Z"), time("19:00:00.000Z")) - ], - "datebins": [ - interval(date("1980-01-01"), date("1990-01-01")), - interval(date("1990-01-01"), date("2000-01-01")), - interval(date("2000-01-01"), date("2010-01-01")), - interval(date("2010-01-01"), date("2020-01-01")) - ], - "datetimebins": [ - interval(datetime("1800-01-01T00:00:00.000Z"), datetime("1900-01-01T00:00:00.000Z")), - interval(datetime("1900-01-01T00:00:00.000Z"), datetime("2000-01-01T00:00:00.000Z")), - interval(datetime("2000-01-01T00:00:00.000Z"), datetime("2100-01-01T00:00:00.000Z")) - ] - }; - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/8_record.md b/asterixdb/asterix-doc/src/main/markdown/builtins/8_record.md deleted file mode 100644 index 2bcdb3e16e7..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/8_record.md +++ /dev/null @@ -1,605 +0,0 @@ - - -## Object Functions ## - -### get_object_fields ### - * Syntax: - - get_object_fields(input_object) - - * Access the object field names, type and open status for a given object. - * Arguments: - * `input_object` : a object value. - * Return Value: - * an array of `object` values that include the field_name `string`, - field_type `string`, is_open `boolean` (used for debug purposes only: `true` if field is open and `false` otherwise), - and optional nested `orderedList` for the values of a nested object, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value, - * any other non-object input value will cause a type error. - - * Example: - - get_object_fields( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"}, - "related": ["Hivestrix", "Preglix", "Apache VXQuery"] - } - ); - - * The expected result is: - - [ - { "field-name": "id", "field-type": "INT64", "is-open": false }, - { "field-name": "project", "field-type": "STRING", "is-open": false }, - { "field-name": "address", "field-type": "RECORD", "is-open": false, - "nested": [ - { "field-name": "city", "field-type": "STRING", "is-open": false }, - { "field-name": "state", "field-type": "STRING", "is-open": false } - ] - }, - { "field-name": - "related", - "field-type": "ORDEREDLIST", - "is-open": false, - "list": [ - { "field-type": "STRING" }, - { "field-type": "STRING" }, - { "field-type": "STRING" } - ] - } - ] - - ] -### get_object_field_value ### - * Syntax: - - get_object_field_value(input_object, string) - - * Access the field name given in the `string_expression` from the `object_expression`. - * Arguments: - * `input_object` : a `object` value. - * `string` : a `string` representing the top level field name. - * Return Value: - * an `any` value saved in the designated field of the object, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-object value, - * or, the second argument is any other non-string value. - - * Example: - - get_object_field_value({ - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"}, - "related": ["Hivestrix", "Preglix", "Apache VXQuery"] - }, - "project" - ); - - * The expected result is: - - "AsterixDB" - -### object_remove_fields ### - * Syntax: - - object_remove_fields(input_object, field_names) - - * Remove indicated fields from a object given a list of field names. - * Arguments: - * `input_object`: a object value. - * `field_names`: an array of strings and/or array of array of strings. - - * Return Value: - * a new object value without the fields listed in the second argument, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-object value, - * or, the second argument is any other non-array value or recursively contains non-string items. - - - * Example: - - object_remove_fields( - { - "id":1, - "project":"AsterixDB", - "address":{"city":"Irvine", "state":"CA"}, - "related":["Hivestrix", "Preglix", "Apache VXQuery"] - }, - [["address", "city"], "related"] - ); - - * The expected result is: - - { - "id":1, - "project":"AsterixDB", - "address":{ "state": "CA" } - } - -### object_add_fields ### - * Syntax: - - object_add_fields(input_object, fields) - - * Add fields to a object given a list of field names. - * Arguments: - * `input_object` : a object value. - * `fields`: an array of field descriptor objects where each object has field_name and field_value. - * Return Value: - * a new object value with the new fields included, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * a type error will be raised if: - * the first argument is any other non-object value, - * the second argument is any other non-array value, or contains non-object items. - - - * Example: - - object_add_fields( - { - "id":1, - "project":"AsterixDB", - "address":{"city":"Irvine", "state":"CA"}, - "related":["Hivestrix", "Preglix", "Apache VXQuery"] - }, - [{"field-name":"employment_location", "field-value":create_point(30.0,70.0)}] - ); - - * The expected result is: - - { - "id":1, - "project":"AsterixDB", - "address":{"city":"Irvine", "state":"CA"}, - "related":["Hivestrix", "Preglix", "Apache VXQuery"] - "employment_location": point("30.0,70.0") - } - -### object_merge ### - * Syntax: - - object_merge(object1, object2) - - * Merge two different objects into a new object. - * Arguments: - * `object1` : a object value. - * `object2` : a object value. - * Return Value: - * a new object value with fields from both input objects. If a field’s names in both objects are the same, - an exception is issued, - * `missing` if any argument is a `missing` value, - * `null` if any argument is a `null` value but no argument is a `missing` value, - * any other non-object input value will cause a type error. - - - * Example: - - object_merge( - { - "id":1, - "project":"AsterixDB", - "address":{"city":"Irvine", "state":"CA"}, - "related":["Hivestrix", "Preglix", "Apache VXQuery"] - }, - { - "user_id": 22, - "employer": "UC Irvine", - "employment_type": "visitor" - } - ); - - * The expected result is: - - { - "employment_type": "visitor", - "address": { - "city": "Irvine", - "state": "CA" - }, - "related": [ - "Hivestrix", - "Preglix", - "Apache VXQuery" - ], - "user_id": 22, - "project": "AsterixDB", - "employer": "UC Irvine", - "id": 1 - } - -### object_length ### - * Syntax: - - object_length(input_object) - - * Returns number of top-level fields in the given object - * Arguments: - * `input_object` : an object value. - * Return Value: - * an integer that represents the number of top-level fields in the given object, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value or any other non-object value - - * Example: - - object_length( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"}, - } - ); - - * The expected result is: - - 3 - -### object_names ### - * Syntax: - - object_names(input_object) - - * Returns names of top-level fields in the given object - * Arguments: - * `input_object` : an object value. - * Return Value: - * an array with top-level field names of the given object, - * `missing` if the argument is a `missing` value, - * `null` if the argument is a `null` value or any other non-object value - - * Example: - - object_names( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"}, - } - ); - - * The expected result is: - - [ "id", "project", "address" ] - -### object_remove ### - * Syntax: - - object_remove(input_object, field_name) - - * Returns a new object that has the same fields as the input object except the field to be removed - * Arguments: - * `input_object` : an object value. - * `field_name` : a string field name. - * Return Value: - * A new object that has the same fields as `input_object` except the field `field_name`, - * `missing` if the argument `input_object` or `field_name` is missing, - * `null` if the argument `input_object` is `null` or any other non-object value, or the argument `field_name` - is `null` or any other non-string value. - - * Example: - - object_remove( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"} - } - , "address" - ); - - * The expected result is: - - { - "id": 1, - "project": "AsterixDB", - } - -### object_rename ### - * Syntax: - - object_rename(input_object, old_field, new_field) - - * Returns a new object that has the same fields as `input_object` with field `old_field` replaced by `new_field` - * Arguments: - * `input_object` : an object value. - * `old_field` : a string representing the old (original) field name inside the object `input_object`. - * `new_field` : a string representing the new field name to replace `old_field` inside the object `input_object`. - * Return Value: - * A new object that has the same fields as `input_object` with field `old_field` replaced by `new_field`, - * `missing` if any argument is a `missing` value, - * `null` if any argument is `null` or `input_object` is non-object value, or `old_field` is non-string value, or - `new_field` is any non-string value. - - * Example: - - object_rename( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"} - } - , "address" - , "location" - ); - - * The expected result is: - - { - "id": 1, - "project": "AsterixDB", - "location": {"city": "Irvine", "state": "CA"} - } - -### object_unwrap ### - * Syntax: - - object_unwrap(input_object) - - * Returns the value of the single name-value pair that appears in `input_object`. - * Arguments: - * `input_object` : an object value that consists of exactly one name-value pair. - * Return Value: - * The value of the single name-value pair that appears in `input_object`, - * `missing` if `input_object` is `missing`, - * `null` if `input_object` is null, or an empty object, or there is more than one name-value pair in `input_object`, - or any non-object value. - - * Example: - - object_unwrap( - { - "id": 1 - } - ); - - * The expected result is: - - { - 1 - } - -### object_replace ### - * Syntax: - - object_replace(input_object, old_value, new_value) - - * Returns a new object that has the same fields as `input_object` with all occurrences of value `old_value` replaced by - `new_value` - * Arguments: - * `input_object` : an object value. - * `old_value` : a primitive type value to be replaced by `new_value`. - * `new_value` : a value to replace `old_value`. - * Return Value: - * A new object that has the same fields as `input_object` with all occurrences of value `old_value` replaced by - `new_value`, - * `missing` if any argument is a `missing` value, - * `null` if `input_object` or `old_value` is null, - * a type error will be raised if: - * `old_value` is not a primitive type value. - - * Example: - - object_replace( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"} - } - , "AsterixDB" - , "Apache AsterixDB" - ); - - * The expected result is: - - { - "id": 1, - "project": "Apache AsterixDB", - "location": {"city": "Irvine", "state": "CA"} - } - -### object_add ### - * Syntax: - - object_add(input_object, field_name, field_value) - - * Returns a new object that has the same fields as `input_object` as well as the new field `field_name`. - * Arguments: - * `input_object` : an object value. - * `field_name` : a string representing a field name to be added. - * `field_value` : a value to be assigned to the new field `field_name`. - * Return Value: - * A new object that has the same fields as `input_object` as well as the new field `field_name`, - * `missing` if `input_object` or `field_name` is `missing`, - * `null` if `input_object` or `field_name` is `null`, or `input_object` is not an object, or `field_name` is not - a string, - * `input_object` if `field_name`already exists in `input_object` or `field_value` is missing. - - * Example: - - object_add( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"} - } - , "company" - , "Apache" - ); - - * The expected result is: - - { - "id": 1, - "project": "AsterixDB", - "location": {"city": "Irvine", "state": "CA"}, - "company": "Apache" - } - -### object_put ### - * Syntax: - - object_put(input_object, field_name, field_value) - - * Adds, modifies, or removes a field of an object. - * Arguments: - * `input_object` : an object value. - * `field_name` : a string representing a field name to be added. - * `field_value` : a value to be assigned to the new field `field_name`. - * Return Value: - * a new object that has the same fields as `input_object` as well as the new field `field_name`, or with updated - `field_name` value to `field_value` if `field_name` already exists in `input_object`, or with `field_name`removed - if `field_name` already exists in `input_object` and `field_value` is `missing`, - * `missing` if `input_object` or `field_name` is `missing`, - * `null` if `input_object` or `field_name` is `null`, or `input_object` is not an object, or `field_name` is not - not a string. - - * Example: - - object_put( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"} - } - , "project" - , "Apache AsterixDB" - ); - - * The expected result is: - - { - "id": 1, - "project": "Apache AsterixDB", - "location": {"city": "Irvine", "state": "CA"} - } - -### object_values ### - * Syntax: - - object_values(input_object) - - * Returns an array of the values of the fields in `input_object`. - * Arguments: - * `input_object` : an object value. - * Return Value: - * An array of the values of the fields in `input_object`, - * `missing` if `input_object` is `missing`, - * `null` if `input_object` is null or any non-object value. - - * Example: - - object_values( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"} - } - ); - - * The expected result is: - - [ - 1, - "AsterixDB", - {"city": "Irvine", "state": "CA"} - ] - -### object_pairs ### - * Syntax: - - object_pairs(input_object) - - * Returns an array of objects describing fields of `input_object`. - For each field of the `input_object` the returned array contains an object with two fields `name` and `value` - which are set to the `input_object`'s field name and value. - - * Arguments: - * `input_object` : an object value. - * Return Value: - * An array of the `name`/`value` pairs of the fields in `input_object`, - * `missing` if `input_object` is `missing`, - * `null` if `input_object` is null or any non-object value. - - * Example: - - object_pairs( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"} - } - ); - - * The expected result is: - - [ - { "name": "id", "value": 1 }, - { "name": "project", "value": "AsterixDB" }, - { "name": "address", "value": {"city": "Irvine", "state": "CA"} } - ] - -### pairs ### - * Syntax: - - pairs(input_object) - - * Returns an array of arrays describing fields of `input_object`, including nested fields. - For each field of the `input_object` the returned array contains an array with two elements. - The first element is the name and the second one is the value of the `input_object`'s field. - The input object is introspected recursively, so all fields of its nested objects are returned. - Nested objects contained in arrays and multisets are also processed by this function. - - * Arguments: - * `input_object` : an object value (or an array or a multiset) - * Return Value: - * An array of arrays with name, value pairs of the fields in `input_object`, including nested fields. - Each inner array has exactly two items: name and value of the `input_object`'s field. - * `missing` if `input_object` is `missing`, - * `null` if `input_object` is null or a value of a primitive data type. - - * Example: - - pairs( - { - "id": 1, - "project": "AsterixDB", - "address": {"city": "Irvine", "state": "CA"} - } - ); - - * The expected result is: - - [ - [ "id", 1 ], - [ "project", "AsterixDB" ], - [ "address", { "city": "Irvine", "state": "CA" } ], - [ "city", "Irvine" ], - [ "state", "CA" ] - ] - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/9_aggregate_aql.md b/asterixdb/asterix-doc/src/main/markdown/builtins/9_aggregate_aql.md deleted file mode 100644 index 4482df8e63c..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/9_aggregate_aql.md +++ /dev/null @@ -1,298 +0,0 @@ - - -## Aggregate Functions (Array Functions) ## - -This section contains detailed descriptions of each AQL aggregate function (i.e., array function). - - -### sql-count ### - * Syntax: - - sql-count(collection) - - * Gets the number of non-null and non-missing items in the given collection. - * Arguments: - * `collection` could be: - * an `array` or `multiset` to be counted, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `bigint` value representing the number of non-null and non-missing items in the given collection, - * `null` is returned if the input is `null` or `missing`, - * any other non-array and non-multiset input value will cause an error. - - * Example: - - sql-count( ['hello', 'world', 1, 2, 3, null, missing] ); - - - * The expected result is: - - 5 - - -### sql-avg ### - - * Syntax: - - sql-avg(num_collection) - - * Gets the average value of the non-null and non-missing numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the average of the non-null and non-missing numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - sql-avg( [1.2, 2.3, 3.4, 0, null] ); - - * The expected result is: - - 1.725 - - -### sql-sum ### - * Syntax: - - sql-sum(num_collection) - - * Gets the sum of non-null and non-missing items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the sum of the non-null and non-missing numbers in the given collection. - The returning type is decided by the item type with the highest - order in the numeric type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among - items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - sql-sum( [1.2, 2.3, 3.4, 0, null, missing] ); - - * The expected result is: - - 6.9 - - -### sql-sql_min ### - * Syntax: - - sql-min(num_collection) - - * Gets the min value of non-null and non-missing comparable items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset`, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the min value of non-null and non-missing values in the given collection. - The returning type is decided by the item type with the highest order in the - type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among numeric items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * multiple incomparable items in the input array or multiset will cause a type error, - * any other non-array and non-multiset input value will cause a type error. - - * Example: - - sql-min( [1.2, 2.3, 3.4, 0, null, missing] ); - - * The expected result is: - - 0.0 - - -### sql-max ### - * Syntax: - - sql-max(num_collection) - - * Gets the max value of the non-null and non-missing comparable items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset`, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the max value of non-null and non-missing numbers in the given collection. - The returning type is decided by the item type with the highest order in the - type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among numeric items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * multiple incomparable items in the input array or multiset will cause a type error, - * any other non-array and non-multiset input value will cause a type error. - - * Example: - - sql-max( [1.2, 2.3, 3.4, 0, null, missing] ); - - * The expected result is: - - 3.4 - - -### count ### - * Syntax: - - count(collection) - - * Gets the number of items in the given collection. - * Arguments: - * `collection` could be: - * an `array` or `multiset` containing the items to be counted, - * or a `null` value, - * or a `missing` value. - * Return Value: - * a `bigint` value representing the number of items in the given collection, - * `null` is returned if the input is `null` or `missing`. - - * Example: - - count( [1, 2, null, missing] ); - - * The expected result is: - - 4 - -### avg ### - * Syntax: - - avg(num_collection) - - * Gets the average value of the numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the average of the numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - avg( [100, 200, 300] ); - - * The expected result is: - - [ 200.0 ] - -### sum ### - * Syntax: - - sum(num_collection) - - * Gets the sum of the items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the sum of the numbers in the given collection. The returning type is decided by the item type with the highest - order in the numeric type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among - items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - sum( [100, 200, 300] ); - - * The expected result is: - - 600 - -### sql-min ### - * Syntax: - - min(num_collection) - - * Gets the min value of comparable items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset`, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the min value of the given collection. - The returning type is decided by the item type with the highest order in the type promotion order - (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among numeric items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * multiple incomparable items in the input array or multiset will cause a type error, - * any other non-array and non-multiset input value will cause a type error. - - * Example: - - min( [10.2, 100, 5] ); - - * The expected result is: - - 5.0 - - -### sql-max ### - * Syntax: - - max(num_collection) - - * Gets the max value of numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset`, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * The max value of the given collection. - The returning type is decided by the item type with the highest order in the type promotion order - (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among numeric items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * multiple incomparable items in the input array or multiset will cause a type error, - * any other non-array and non-multiset input value will cause a type error. - - * Example: - - max( [10.2, 100, 5] ); - - * The expected result is: - - 100.0 - diff --git a/asterixdb/asterix-doc/src/main/markdown/builtins/9_aggregate_sql.md b/asterixdb/asterix-doc/src/main/markdown/builtins/9_aggregate_sql.md deleted file mode 100644 index 93f6d9a595d..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/builtins/9_aggregate_sql.md +++ /dev/null @@ -1,623 +0,0 @@ - - -## Aggregate Functions (Array Functions) ## - -This section contains detailed descriptions of the built-in aggregate functions in the query language. - -The query language also supports standard SQL aggregate functions (e.g., `MIN`, `MAX`, `SUM`, `COUNT`, and `AVG`). -Note that these are not real functions in the query language, but just syntactic sugars over corresponding -builtin aggregate functions (e.g., `ARRAY_MIN`, `ARRAY_MAX`, -`ARRAY_SUM`, `ARRAY_COUNT`, and `ARRAY_AVG`). -Refer to [SQL-92 Aggregation Functions](manual.html#SQL-92_aggregation_functions) for details. - -The `DISTINCT` keyword may be used with built-in aggregate functions and standard SQL aggregate functions. -It may also be used with aggregate functions used as window functions. -It determines whether the function aggregates all values in the group, or distinct values only. -Refer to [Aggregation Functions](manual.html#Aggregation_functions) for details. - -Aggregate functions may be used as window functions when they are used with an OVER clause. -Refer to [OVER Clauses](manual.html#Over_clauses) for details. - -### array_count ### - * Syntax: - - array_count(collection) - - * Gets the number of non-null and non-missing items in the given collection. - * Arguments: - * `collection` could be: - * an `array` or `multiset` to be counted, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `bigint` value representing the number of non-null and non-missing items in the given collection, - * `null` is returned if the input is `null` or `missing`, - * any other non-array and non-multiset input value will cause an error. - - * Example: - - array_count( ['hello', 'world', 1, 2, 3, null, missing] ); - - - * The expected result is: - - 5 - - -### array_avg ### - - * Syntax: - - array_avg(num_collection) - - * Gets the average value of the non-null and non-missing numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the average of the non-null and non-missing numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - array_avg( [1.2, 2.3, 3.4, 0, null] ); - - * The expected result is: - - 1.725 - - -### array_sum ### - * Syntax: - - array_sum(num_collection) - - * Gets the sum of non-null and non-missing items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the sum of the non-null and non-missing numbers in the given collection. - The returning type is decided by the item type with the highest - order in the numeric type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among - items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - array_sum( [1.2, 2.3, 3.4, 0, null, missing] ); - - * The expected result is: - - 6.9 - - -### array_min ### - * Syntax: - - array_min(num_collection) - - * Gets the min value of non-null and non-missing comparable items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset`, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the min value of non-null and non-missing values in the given collection. - The returning type is decided by the item type with the highest order in the - type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among numeric items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * multiple incomparable items in the input array or multiset will cause a type error, - * any other non-array and non-multiset input value will cause a type error. - - * Example: - - array_min( [1.2, 2.3, 3.4, 0, null, missing] ); - - * The expected result is: - - 0.0 - - -### array_max ### - * Syntax: - - array_max(num_collection) - - * Gets the max value of the non-null and non-missing comparable items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset`, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the max value of non-null and non-missing numbers in the given collection. - The returning type is decided by the item type with the highest order in the - type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among numeric items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * multiple incomparable items in the input array or multiset will cause a type error, - * any other non-array and non-multiset input value will cause a type error. - - * Example: - - array_max( [1.2, 2.3, 3.4, 0, null, missing] ); - - * The expected result is: - - 3.4 - - -### array_stddev_samp ### - - * Syntax: - - array_stddev_samp(num_collection) - - * Gets the sample standard deviation value of the non-null and non-missing numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the sample standard deviation of the non-null and non-missing numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - array_stddev_samp( [1.2, 2.3, 3.4, 0, null] ); - - * The expected result is: - - 1.4591664287073858 - -### array_stddev_pop ### - - * Syntax: - - array_stddev_pop(num_collection) - - * Gets the population standard deviation value of the non-null and non-missing numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the population standard deviation of the non-null and non-missing numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - array_stddev_pop( [1.2, 2.3, 3.4, 0, null] ); - - * The expected result is: - - 1.2636751956100112 - -### array_var_samp ### - - * Syntax: - - array_var_samp(num_collection) - - * Gets the sample variance value of the non-null and non-missing numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the sample variance of the non-null and non-missing numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - array_var_samp( [1.2, 2.3, 3.4, 0, null] ); - - * The expected result is: - - 2.1291666666666664 - -### array_var_pop ### - - * Syntax: - - array_var_pop(num_collection) - - * Gets the population variance value of the non-null and non-missing numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the population variance of the non-null and non-missing numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - array_var_pop( [1.2, 2.3, 3.4, 0, null] ); - - * The expected result is: - - 1.5968749999999998 - -### array_skewness ### - - * Syntax: - - array_skewness(num_collection) - - * Gets the skewness value of the non-null and non-missing numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the skewness of the non-null and non-missing numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - array_skewness( [1.2, 2.3, 3.4, 0, null] ); - - * The expected result is: - - -0.04808451539164242 - -### array_kurtosis ### - - * Syntax: - - array_kurtosis(num_collection) - - * Gets the kurtosis value from the normal distribution of the non-null and non-missing numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the kurtosis from a normal distribution of the non-null and non-missing numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if the given collection does not contain any non-null and non-missing items, - * any other non-array and non-multiset input value will cause a type error, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - array_kurtosis( [1.2, 2.3, 3.4, 0, null] ); - - * The expected result is: - - -1.342049701096427 - -### strict_count ### - * Syntax: - - strict_count(collection) - - * Gets the number of items in the given collection. - * Arguments: - * `collection` could be: - * an `array` or `multiset` containing the items to be counted, - * or a `null` value, - * or a `missing` value. - * Return Value: - * a `bigint` value representing the number of items in the given collection, - * `null` is returned if the input is `null` or `missing`. - - * Example: - - strict_count( [1, 2, null, missing] ); - - * The expected result is: - - 4 - -### strict_avg ### - * Syntax: - - strict_avg(num_collection) - - * Gets the average value of the numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the average of the numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - strict_avg( [100, 200, 300] ); - - * The expected result is: - - 200.0 - -### strict_sum ### - * Syntax: - - strict_sum(num_collection) - - * Gets the sum of the items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the sum of the numbers in the given collection. The returning type is decided by the item type with the highest - order in the numeric type promotion order (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among - items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - strict_sum( [100, 200, 300] ); - - * The expected result is: - - 600 - -### strict_min ### - * Syntax: - - strict_min(num_collection) - - * Gets the min value of comparable items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset`, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * the min value of the given collection. - The returning type is decided by the item type with the highest order in the type promotion order - (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among numeric items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * multiple incomparable items in the input array or multiset will cause a type error, - * any other non-array and non-multiset input value will cause a type error. - - * Example: - - strict_min( [10.2, 100, 5] ); - - * The expected result is: - - 5.0 - - -### strict_max ### - * Syntax: - - strict_max(num_collection) - - * Gets the max value of numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset`, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * The max value of the given collection. - The returning type is decided by the item type with the highest order in the type promotion order - (`tinyint`-> `smallint`->`integer`->`bigint`->`float`->`double`) among numeric items. - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * multiple incomparable items in the input array or multiset will cause a type error, - * any other non-array and non-multiset input value will cause a type error. - - * Example: - - strict_max( [10.2, 100, 5] ); - - * The expected result is: - - 100.0 - -### strict_stddev_samp ### - * Syntax: - - strict_stddev_samp(num_collection) - - * Gets the sample standard deviation value of the numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the sample standard deviation of the numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - strict_stddev_samp( [100, 200, 300] ); - - * The expected result is: - - 100.0 - -### strict_stddev_pop ### - * Syntax: - - strict_stddev_pop(num_collection) - - * Gets the population standard deviation value of the numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the population standard deviation of the numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - strict_stddev_pop( [100, 200, 300] ); - - * The expected result is: - - 81.64965809277261 - -### strict_var_samp ### - * Syntax: - - strict_var_samp(num_collection) - - * Gets the sample variance value of the numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the sample variance of the numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - strict_var_samp( [100, 200, 300] ); - - * The expected result is: - - 10000.0 - -### strict_var_pop ### - * Syntax: - - strict_var_pop(num_collection) - - * Gets the population variance value of the numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the population variance of the numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - strict_var_pop( [100, 200, 300] ); - - * The expected result is: - - 6666.666666666667 - -### strict_skewness ### - * Syntax: - - strict_skewness(num_collection) - - * Gets the skewness value of the numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the skewness of the numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - strict_skewness( [100, 200, 300] ); - - * The expected result is: - - 0.0 - -### strict_kurtosis ### - * Syntax: - - strict_kurtosis(num_collection) - - * Gets the kurtosis value from the normal distribution of the numeric items in the given collection. - * Arguments: - * `num_collection` could be: - * an `array` or `multiset` containing numeric values, `null`s or `missing`s, - * or, a `null` value, - * or, a `missing` value. - * Return Value: - * a `double` value representing the kurtosis from a normal distribution of the numbers in the given collection, - * `null` is returned if the input is `null` or `missing`, - * `null` is returned if there is a `null` or `missing` in the input collection, - * any other non-numeric value in the input collection will cause a type error. - - * Example: - - strict_kurtosis( [100, 200, 300] ); - - * The expected result is: - - -1.5 - diff --git a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_composite.md b/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_composite.md deleted file mode 100644 index 92b037405d0..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_composite.md +++ /dev/null @@ -1,57 +0,0 @@ - - - -## Derived Types ## - -### Object ### -An `object` contains a set of fields, where each field is described by its name and type. An object type may be defined as either open or closed. Open objects (instances of open object types) are permitted to contain fields that are not part of the type definition, while closed objects do not permit their instances to carry extra fields. An example type definition for an object is: - - create type SoldierType as open { - name: string?, - rank: string, - serialno: int - }; - -Syntactically, object constructors are surrounded by curly braces "{...}". -Some examples of legitimate instances of the above type include: - - { "name": "Joe Blow", "rank": "Sergeant", "serialno": 1234567 } - { "rank": "Private", "serialno": 9876543 } - { "name": "Sally Forth", "rank": "Major", "serialno": 2345678, "gender": "F" } - -The first instance has all of the type's prescribed content. The second instance is missing the name field, which is fine because it is optional (due to the ?). The third instance has an extra field; that is fine because the type definition specifies that it is open (which is also true by default, if open is not specified). To more tightly control object content, specifying closed instead of open in the type definition for SoldierType would have made the third example instance an invalid instance of the type. - -### Array ### -An `array` is a container that holds a fixed number of values. Array constructors are denoted by brackets: "[...]". - -An example would be - - - ["alice", 123, "bob", null] - - -### Multiset ### -A `multiset` is a generalization of the concept of a set that, unlike a set, allows multiple instances of the multiset's elements. - Multiset constructors are denoted by two opening curly braces followed by data and two closing curly braces, like "{{...}}". - -An example would be - - - {{"hello", 9328, "world", [1, 2, null]}} diff --git a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_header.md b/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_header.md deleted file mode 100644 index cc66a3f7861..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_header.md +++ /dev/null @@ -1,55 +0,0 @@ - - -# The Asterix Data Model (ADM) # - -## Table of Contents ## - -* [Primitive Types](#PrimitiveTypes) - * [Boolean](#PrimitiveTypesBoolean) - * [String](#PrimitiveTypesString) - * [Tinyint / Smallint / Integer (Int) / Bigint](#PrimitiveTypesInt) - * [Float](#PrimitiveTypesFloat) - * [Double (Double Precision)](#PrimitiveTypesDouble) - * [Binary](#PrimitiveTypesBinary) - * [Point](#PrimitiveTypesPoint) - * [Line](#PrimitiveTypesLine) - * [Rectangle](#PrimitiveTypesRectangle) - * [Circle](#PrimitiveTypesCircle) - * [Polygon](#PrimitiveTypesPolygon) - * [Date](#PrimitiveTypesDate) - * [Time](#PrimitiveTypesTime) - * [Datetime (Timestamp)](#PrimitiveTypesDateTime) - * [Duration/Year_month_duration/Day_time_duration](#PrimitiveTypesDuration) - * [Interval](#PrimitiveTypesInterval) - * [UUID](#PrimitiveTypesUUID) -* [Incomplete Information Types](#IncompleteInformationTypes) - * [Null](#IncompleteInformationTypesNull) - * [Missing](#IncompleteInformationTypesMissing) -* [Derived Types](#DerivedTypes) - * [Object](#DerivedTypesObject) - * [Array](#DerivedTypesArray) - * [Multiset](#DerivedTypesMultiset) - -An instance of Asterix data model (ADM) can be a _*primitive type*_ (`boolean`, -`tinyint`, `smallint`, `integer`, `bigint`, `string`, `float`, `double`, `date`, -`time`, `datetime`, etc.), a _*special type*_ (`null` or `missing`), or a _*derived type*_. - -The type names are case-insensitive, e.g., both `BIGINT` and `bigint` are acceptable. - diff --git a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_incomplete.md b/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_incomplete.md deleted file mode 100644 index c65ed85d4dc..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_incomplete.md +++ /dev/null @@ -1,54 +0,0 @@ - - -## Incomplete Information Types ## - -### Null ### -`null` is a special value that is often used to represent an unknown value. -For example, a user might not be able to know the value of a field and let it be `null`. - - * Example: - - { "field": null }; - - - * The expected result is: - - { "field": null } - - -### Missing ### -`missing` indicates that a name-value pair is missing from an object. -If a missing name-value pair is accessed, an empty result value is returned by the query. - -As neither the data model nor the system enforces homogeneity for datasets or collections, -items in a dataset or collection can be of heterogeneous types and -so a field can be present in one object and `missing` in another. - - * Example: - - { "field": missing }; - - - * The expected result is: - - { } - -Since a field with value `missing` means the field is absent, we get an empty object. - diff --git a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_primitive_common.md b/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_primitive_common.md deleted file mode 100644 index 4c0b2e04ff1..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_primitive_common.md +++ /dev/null @@ -1,49 +0,0 @@ - - -## Primitive Types ## - -### Boolean ### -`boolean` data type can have one of the two values: _*true*_ or _*false*_. - - * Example: - - { "true": true, "false": false }; - - - * The expected result is: - - { "true": true, "false": false } - - -### String ### -`string` represents a sequence of characters. The total length of the sequence can be up to 2,147,483,648. - - * Example: - - { "v1": string("This is a string."), "v2": string("\"This is a quoted string\"") }; - - - * The expected result is: - - { "v1": "This is a string.", "v2": "\"This is a quoted string\"" } - - - - diff --git a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_primitive_delta.md b/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_primitive_delta.md deleted file mode 100644 index dc353817158..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/datamodel/datamodel_primitive_delta.md +++ /dev/null @@ -1,269 +0,0 @@ - - -### Tinyint / Smallint / Integer (Int) / Bigint ### -Integer types using 8, 16, 32, or 64 bits. The ranges of these types are: - -- `tinyint`: -128 to 127 -- `smallint`: -32768 to 32767 -- `integer`: -2147483648 to 2147483647 -- `bigint`: -9223372036854775808 to 9223372036854775807 - -`int` is an abbreviated alias for integer. - - * Example: - - { "tinyint": tiny("125"), "smallint": smallint("32765"), "integer": 294967295, "bigint": bigint("1700000000000000000")}; - - - * The expected result is: - - { "tinyint": 125, "smallint": 32765, "integer": 294967295, "bigint": 1700000000000000000 } - -### Float ### -`float` represents approximate numeric data values using 4 bytes. The range of a float value can be -from 2^(-149) to (2-2^(-23)·2^(127) for both positive and negative. Beyond these ranges will get `INF` or `-INF`. - - * Example: - - { "v1": float("NaN"), "v2": float("INF"), "v3": float("-INF"), "v4": float("-2013.5") }; - - - * The expected result is: - - { "v1": "NaN", "v2": "INF", "v3": "-INF", "v4": -2013.5 } - - -### Double (double precision) ### -`double` represents approximate numeric data values using 8 bytes. The range of a double value can be from (2^(-1022)) to (2-2^(-52))·2^(1023) -for both positive and negative. Beyond these ranges will get `INF` or `-INF`. - - * Example: - - { "v1": double("NaN"), "v2": double("INF"), "v3": double("-INF"), "v4": "-2013.593823748327284" }; - - - * The expected result is: - - { "v1": "NaN", "v2": "INF", "v3": "-INF", "v4": -2013.5938237483274 } - -`Double precision` is an alias of `double`. - -### Binary ### -`binary` represents a sequence of bytes. It can be constructed from a `hex` or a `base64` string sequence. -The total length of the byte sequence can be up to 2,147,483,648. - - * Example: - - { - "hex1" : hex("ABCDEF0123456789"), - "hex2": hex("abcdef0123456789"), - "base64_1" : base64("0123456789qwertyui+/"), - "base64_2" : base64('QXN0ZXJpeA==') - }; - - * The default output format is in `hex` format. Thus, the expected result is: - - { - "hex1": hex("ABCDEF0123456789"), - "hex2": hex("ABCDEF0123456789"), - "base64_1": hex("D35DB7E39EBBF3DAB07ABB72BA2FBF"), - "base64_2": hex("41737465726978") - } - - -### Point ### -`point` is the fundamental two-dimensional building block for spatial types. It consists of two `double` coordinates x and y. - - * Example: - - { "v1": point("80.10d, -10E5"), "v2": point("5.10E-10d, -10E5") }; - - - * The expected result is: - - { "v1": point("80.1,-1000000.0"), "v2": point("5.1E-10,-1000000.0") } - - -### Line ### -`line` consists of two points that represent the start and the end points of a line segment. - - * Example: - - { "v1": line("10.1234,11.1e-1 +10.2E-2,-11.22"), "v2": line("0.1234,-1.00e-10 +10.5E-2,-01.02") }; - - - * The expected result is: - - { "v1": line("10.1234,1.11 0.102,-11.22"), "v2": line("0.1234,-1.0E-10 0.105,-1.02") } - - -### Rectangle ### -`rectangle` consists of two points that represent the _*bottom left*_ and _*upper right*_ corners of a rectangle. - - * Example: - - { "v1": rectangle("5.1,11.8 87.6,15.6548"), "v2": rectangle("0.1234,-1.00e-10 5.5487,0.48765") }; - - - * The expected result is: - - { "v1": rectangle("5.1,11.8 87.6,15.6548"), "v2": rectangle("0.1234,-1.0E-10 5.5487,0.48765") } - - -### Circle ### -`circle` consists of one point that represents the center of the circle and a radius of type `double`. - - * Example: - - { "v1": circle("10.1234,11.1e-1 +10.2E-2"), "v2": circle("0.1234,-1.00e-10 +10.5E-2") }; - - - * The expected result is: - - { "v1": circle("10.1234,1.11 0.102"), "v2": circle("0.1234,-1.0E-10 0.105") } - - -### Polygon ### -`polygon` consists of _*n*_ points that represent the vertices of a _*simple closed*_ polygon. - - * Example: - - { - "v1": polygon("-1.2,+1.3e2 -2.14E+5,2.15 -3.5e+2,03.6 -4.6E-3,+4.81"), - "v2": polygon("-1.0,+10.5e2 -02.15E+50,2.5 -1.0,+3.3e3 -2.50E+05,20.15 +3.5e+2,03.6 -4.60E-3,+4.75 -2,+1.0e2 -2.00E+5,20.10 30.5,03.25 -4.33E-3,+4.75") - }; - - - * The expected result is: - - { - "v1": polygon("-1.2,130.0 -214000.0,2.15 -350.0,3.6 -0.0046,4.81"), - "v2": polygon("-1.0,1050.0 -2.15E50,2.5 -1.0,3300.0 -250000.0,20.15 350.0,3.6 -0.0046,4.75 -2.0,100.0 -200000.0,20.1 30.5,3.25 -0.00433,4.75") } - } - - -### Date ### -`date` represents a time point along the Gregorian calendar system specified by the year, month and day. ASTERIX supports the date from `-9999-01-01` to `9999-12-31`. - -A date value can be represented in two formats, extended format and basic format. - - * Extended format is represented as `[-]yyyy-mm-dd` for `year-month-day`. Each field should be padded if there are less digits than the format specified. - * Basic format is in the format of `[-]yyyymmdd`. - - * Example: - - { "v1": date("2013-01-01"), "v2": date("-19700101") }; - - - * The expected result is: - - { "v1": date("2013-01-01"), "v2": date("-1970-01-01") } - - -### Time ### -`time` type describes the time within the range of a day. It is represented by three fields: hour, minute and second. Millisecond field is optional as the fraction of the second field. Its extended format is as `hh:mm:ss[.mmm]` and the basic format is `hhmmss[mmm]`. The value domain is from `00:00:00.000` to `23:59:59.999`. - -Timezone field is optional for a time value. Timezone is represented as `[+|-]hh:mm` for extended format or `[+|-]hhmm` for basic format. Note that the sign designators cannot be omitted. `Z` can also be used to represent the UTC local time. If no timezone information is given, it is UTC by default. - - * Example: - - { "v1": time("12:12:12.039Z"), "v2": time("000000000-0800") }; - - - * The expected result is: - - { "v1": time("12:12:12.039Z"), "v2": time("08:00:00.000Z") } - - -### Datetime (Timestamp) ### -A `datetime` value is a combination of an `date` and `time`, representing a fixed time point along the Gregorian calendar system. The value is among `-9999-01-01 00:00:00.000` and `9999-12-31 23:59:59.999`. - -A `datetime` value is represented as a combination of the representation of its `date` part and `time` part, separated by a separator `T`. Either extended or basic format can be used, and the two parts should be the same format. - -Millisecond field and timezone field are optional, as specified in the `time` type. - - * Example: - - { "v1": datetime("2013-01-01T12:12:12.039Z"), "v2": datetime("-19700101T000000000-0800") }; - - - * The expected result is: - - { "v1": datetime("2013-01-01T12:12:12.039Z"), "v2": datetime("-1970-01-01T08:00:00.000Z") } - -`timestamp` is an alias of `datetime`. - -### Duration/Year_month_duration/Day_time_duration ### -`duration` represents a duration of time. A duration value is specified by integers on at least one of the following fields: year, month, day, hour, minute, second, and millisecond. - -A duration value is in the format of `[-]PnYnMnDTnHnMn.mmmS`. The millisecond part (as the fraction of the second field) is optional, and when no millisecond field is used, the decimal point should also be absent. - -Negative durations are also supported for the arithmetic operations between time instance types (`date`, `time` and `datetime`), and is used to roll the time back for the given duration. For example `date("2012-01-01") + duration("-P3D")` will return `date("2011-12-29")`. - -There are also two sub-duration types, namely `year_month_duration` and `day_time_duration`. -`year_month_duration` represents only the years and months of a duration, -while `day_time_duration` represents only the day to millisecond fields. -Different from the `duration` type, both these two subtypes are totally ordered, so they can be used for comparison and -index construction. - -Note that a canonical representation of the duration is always returned, regardless whether the duration is in the canonical representation or not from the user's input. More information about canonical representation can be found from [XPath dayTimeDuration Canonical Representation](http://www.w3.org/TR/xpath-functions/#canonical-dayTimeDuration) and [yearMonthDuration Canonical Representation](http://www.w3.org/TR/xpath-functions/#canonical-yearMonthDuration). - - * Example: - - { "v1": duration("P100Y12MT12M"), "v2": duration("-PT20.943S") }; - - - * The expected result is: - - { "v1": duration("P101YT12M"), "v2": duration("-PT20.943S") } - - -### Interval ### -`interval` represents inclusive-exclusive ranges of time. It is defined by two time point values with the same temporal type(`date`, `time` or `datetime`). - - * Example: - - { - "v1": interval(date("2013-01-01"), date("20130505")), - "v2": interval(time("00:01:01"), time("213901049+0800")), - "v3": interval(datetime("2013-01-01T00:01:01"), datetime("20130505T213901049+0800")) - }; - - - * The expected result is: - - { - "v1": interval(date("2013-01-01"), date("2013-05-05")), - "v2": interval(time("00:01:01.000Z"), time("13:39:01.049Z")), - "v3": interval(datetime("2013-01-01T00:01:01.000Z"), datetime("2013-05-05T13:39:01.049Z")) - } - -### UUID ### -`uuid` represents a UUID value, which stands for Universally unique identifier. It is defined by a canonical format using hexadecimal text with inserted hyphen characters. (E.g.: 5a28ce1e-6a74-4201-9e8f-683256e5706f). This type is generally used to store auto-generated primary key values. - - * Example: - - return { "v1":uuid("5c848e5c-6b6a-498f-8452-8847a2957421") } - - - * The expected result is: - - { "v1": uuid("5c848e5c-6b6a-498f-8452-8847a2957421") } - diff --git a/asterixdb/asterix-doc/src/main/markdown/sqlpp/0_toc.md b/asterixdb/asterix-doc/src/main/markdown/sqlpp/0_toc.md deleted file mode 100644 index e65ae9f5e3e..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/sqlpp/0_toc.md +++ /dev/null @@ -1,103 +0,0 @@ - - -# The Query Language - -* [1. Introduction](#Introduction) -* [2. Expressions](#Expressions) - * [Operator Expressions](#Operator_expressions) - * [Arithmetic Operators](#Arithmetic_operators) - * [Collection Operators](#Collection_operators) - * [Comparison Operators](#Comparison_operators) - * [Logical Operators](#Logical_operators) - * [Quantified Expressions](#Quantified_expressions) - * [Path Expressions](#Path_expressions) - * [Primary Expressions](#Primary_expressions) - * [Literals](#Literals) - * [Variable References](#Variable_references) - * [Parenthesized Expressions](#Parenthesized_expressions) - * [Function call Expressions](#Function_call_expressions) - * [Case Expressions](#Case_expressions) - * [Constructors](#Constructors) -* [3. Queries](#Queries) - * [Declarations](#Declarations) - * [SELECT Statements](#SELECT_statements) - * [SELECT Clauses](#Select_clauses) - * [Select Element/Value/Raw](#Select_element) - * [SQL-style Select](#SQL_select) - * [Select *](#Select_star) - * [Select Distinct](#Select_distinct) - * [Unnamed Projections](#Unnamed_projections) - * [Abbreviated Field Access Expressions](#Abbreviated_field_access_expressions) - * [UNNEST Clauses](#Unnest_clauses) - * [Inner Unnests](#Inner_unnests) - * [Left Outer Unnests](#Left_outer_unnests) - * [Expressing Joins Using Unnests](#Expressing_joins_using_unnests) - * [FROM clauses](#From_clauses) - * [Binding Expressions](#Binding_expressions) - * [Multiple From Terms](#Multiple_from_terms) - * [Expressing Joins Using From Terms](#Expressing_joins_using_from_terms) - * [Implicit Binding Variables](#Implicit_binding_variables) - * [JOIN Clauses](#Join_clauses) - * [Inner Joins](#Inner_joins) - * [Left Outer Joins](#Left_outer_joins) - * [GROUP BY Clauses](#Group_By_clauses) - * [Group Variables](#Group_variables) - * [Implicit Group Key Variables](#Implicit_group_key_variables) - * [Implicit Group Variables](#Implicit_group_variables) - * [Aggregation Functions](#Aggregation_functions) - * [SQL-92 Aggregation Functions](#SQL-92_aggregation_functions) - * [SQL-92 Compliant GROUP BY Aggregations](#SQL-92_compliant_gby) - * [Column Aliases](#Column_aliases) - * [WHERE Clauses and HAVING Clauses](#Where_having_clauses) - * [ORDER BY Clauses](#Order_By_clauses) - * [LIMIT Clauses](#Limit_clauses) - * [WITH Clauses](#With_clauses) - * [LET Clauses](#Let_clauses) - * [UNION ALL](#Union_all) - * [OVER Clauses](#Over_clauses) - * [Window Function Call](#Window_function_call) - * [Window Function Options](#Window_function_options) - * [Window Frame Variable](#Window_frame_variable) - * [Window Definition](#Window_definition) - * [Differences from SQL-92](#Vs_SQL-92) -* [4. Errors](#Errors) - * [Syntax Errors](#Syntax_errors) - * [Identifier Resolution Errors](#Identifier_resolution_errors) - * [Type Errors](#Type_errors) - * [Resource Errors](#Resource_errors) -* [5. DDL and DML Statements](#DDL_and_DML_statements) - * [Lifecycle Management Statements](#Lifecycle_management_statements) - * [Dataverses](#Dataverses) - * [Types](#Types) - * [Datasets](#Datasets) - * [Indices](#Indices) - * [Functions](#Functions) - * [Synonyms](#Synonyms) - * [Removal](#Removal) - * [Load Statement](#Load_statement) - * [Modification Statements](#Modification_statements) - * [Inserts](#Inserts) - * [Upserts](#Upserts) - * [Deletes](#Deletes) -* [Appendix 1. Reserved Keywords](#Reserved_keywords) -* [Appendix 2. Performance Tuning](#Performance_tuning) - * [Parallelism Parameter](#Parallelism_parameter) - * [Memory Parameters](#Memory_parameters) -* [Appendix 3. Variable Bindings and Name Resolution](#Variable_bindings_and_name_resolution) diff --git a/asterixdb/asterix-doc/src/main/markdown/sqlpp/1_intro.md b/asterixdb/asterix-doc/src/main/markdown/sqlpp/1_intro.md deleted file mode 100644 index 8590c2e5382..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/sqlpp/1_intro.md +++ /dev/null @@ -1,43 +0,0 @@ - - -# 1. Introduction - -This document is intended as a reference guide to the full syntax and semantics of -AsterixDB's query language, a SQL-based language for working with semistructured data. -The language is a derivative of SQL++, a declarative query language for JSON data which -is largely backwards compatible with SQL. -SQL++ originated from research in the FORWARD project at UC San Diego, and it has -much in common with SQL; some differences exist due to the different data models that -the two languages were designed to serve. -SQL was designed for interacting with the flat, schema-ified world of relational -databases, while SQL++ generalizes SQL to also handle nested data formats (like JSON) and -the schema-optional (or even schema-less) data models of modern NoSQL and BigData systems. - -In the context of Apache AsterixDB, the query language is intended for working with the Asterix Data Model -([ADM](../datamodel.html)), a data model based on a superset of JSON with an enriched and flexible type system. -New AsterixDB users are encouraged to read and work through the (much friendlier) guide -"[AsterixDB 101: An ADM and SQL++ Primer](primer-sqlpp.html)" before attempting to make use of this document. -In addition, readers are advised to read through the [Asterix Data Model (ADM) reference guide](../datamodel.html) -first as well, as an understanding of the data model is a prerequisite to understanding the query language. - -In what follows, we detail the features of the query language in a grammar-guided manner. -We list and briefly explain each of the productions in the query grammar, offering examples -(and results) for clarity. - diff --git a/asterixdb/asterix-doc/src/main/markdown/sqlpp/2_expr.md b/asterixdb/asterix-doc/src/main/markdown/sqlpp/2_expr.md deleted file mode 100644 index 37e7f79e36c..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/sqlpp/2_expr.md +++ /dev/null @@ -1,477 +0,0 @@ - - -The query language is a highly composable expression language. -Each expression in the query language returns zero or more data model instances. -There are three major kinds of expressions. -At the topmost level, an expression can be an OperatorExpression (similar to a mathematical expression) or a -QuantifiedExpression (which yields a boolean value). -Each will be detailed as we explore the full grammar of the language. - - Expression ::= OperatorExpression | QuantifiedExpression - -Note that in the following text, words enclosed in angle brackets denote keywords that are not case-sensitive. - - -## Operator Expressions - -Operators perform a specific operation on the input values or expressions. -The syntax of an operator expression is as follows: - - OperatorExpression ::= PathExpression - | Operator OperatorExpression - | OperatorExpression Operator (OperatorExpression)? - | OperatorExpression OperatorExpression OperatorExpression - -The language provides a full set of operators that you can use within its statements. -Here are the categories of operators: - -* [Arithmetic Operators](#Arithmetic_operators), to perform basic mathematical operations; -* [Collection Operators](#Collection_operators), to evaluate expressions on collections or objects; -* [Comparison Operators](#Comparison_operators), to compare two expressions; -* [Logical Operators](#Logical_operators), to combine operators using Boolean logic. - -The following table summarizes the precedence order (from higher to lower) of the major unary and binary operators: - -| Operator | Operation | -|-----------------------------------------------------------------------------|-----------| -| EXISTS, NOT EXISTS | Collection emptiness testing | -| ^ | Exponentiation | -| *, /, DIV, MOD (%) | Multiplication, division, modulo | -| +, - | Addition, subtraction | -| || | String concatenation | -| IS NULL, IS NOT NULL, IS MISSING, IS NOT MISSING,
IS UNKNOWN, IS NOT UNKNOWN, IS VALUED, IS NOT VALUED | Unknown value comparison | -| BETWEEN, NOT BETWEEN | Range comparison (inclusive on both sides) | -| =, !=, <>, <, >, <=, >=, LIKE, NOT LIKE, IN, NOT IN | Comparison | -| NOT | Logical negation | -| AND | Conjunction | -| OR | Disjunction | - -In general, if any operand evaluates to a `MISSING` value, the enclosing operator will return `MISSING`; -if none of operands evaluates to a `MISSING` value but there is an operand evaluates to a `NULL` value, -the enclosing operator will return `NULL`. However, there are a few exceptions listed in -[comparison operators](#Comparison_operators) and [logical operators](#Logical_operators). - -### Arithmetic Operators - -Arithmetic operators are used to exponentiate, add, subtract, multiply, and divide numeric values, or concatenate string -values. - -| Operator | Purpose | Example | -|--------------|-------------------------------------------------------------------------|------------| -| +, - | As unary operators, they denote a
positive or negative expression | SELECT VALUE -1; | -| +, - | As binary operators, they add or subtract | SELECT VALUE 1 + 2; | -| * | Multiply | SELECT VALUE 4 * 2; | -| / | Divide (returns a value of type `double` if both operands are integers)| SELECT VALUE 5 / 2; | -| DIV | Divide (returns an integer value if both operands are integers) | SELECT VALUE 5 DIV 2; | -| MOD (%) | Modulo | SELECT VALUE 5 % 2; | -| ^ | Exponentiation | SELECT VALUE 2^3; | -| || | String concatenation | SELECT VALUE "ab"||"c"||"d"; | - -### Collection Operators -Collection operators are used for membership tests (IN, NOT IN) or empty collection tests (EXISTS, NOT EXISTS). - -| Operator | Purpose | Example | -|------------|----------------------------------------------|------------| -| IN | Membership test | SELECT * FROM ChirpMessages cm
WHERE cm.user.lang IN ["en", "de"]; | -| NOT IN | Non-membership test | SELECT * FROM ChirpMessages cm
WHERE cm.user.lang NOT IN ["en"]; | -| EXISTS | Check whether a collection is not empty | SELECT * FROM ChirpMessages cm
WHERE EXISTS cm.referredTopics; | -| NOT EXISTS | Check whether a collection is empty | SELECT * FROM ChirpMessages cm
WHERE NOT EXISTS cm.referredTopics; | - -### Comparison Operators -Comparison operators are used to compare values. -The comparison operators fall into one of two sub-categories: missing value comparisons and regular value comparisons. -The query language (and JSON) has two ways of representing missing information in a object - the presence of the field -with a NULL for its value (as in SQL), and the absence of the field (which JSON permits). -For example, the first of the following objects represents Jack, whose friend is Jill. -In the other examples, Jake is friendless a la SQL, with a friend field that is NULL, while Joe is friendless in a more -natural (for JSON) way, i.e., by not having a friend field. - -##### Examples -{"name": "Jack", "friend": "Jill"} - -{"name": "Jake", "friend": NULL} - -{"name": "Joe"} - -The following table enumerates all of the query language's comparison operators. - -| Operator | Purpose | Example | -|----------------|------------------------------------------------|------------| -| IS NULL | Test if a value is NULL | SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NULL; | -| IS NOT NULL | Test if a value is not NULL | SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NOT NULL; | -| IS MISSING | Test if a value is MISSING | SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS MISSING; | -| IS NOT MISSING | Test if a value is not MISSING | SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NOT MISSING;| -| IS UNKNOWN | Test if a value is NULL or MISSING | SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS UNKNOWN; | -| IS NOT UNKNOWN | Test if a value is neither NULL nor MISSING | SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NOT UNKNOWN;| -| IS KNOWN (IS VALUED) | Test if a value is neither NULL nor MISSING | SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS KNOWN; | -| IS NOT KNOWN (IS NOT VALUED) | Test if a value is NULL or MISSING | SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NOT KNOWN; | -| BETWEEN | Test if a value is between a start value and
a end value. The comparison is inclusive
to both start and end values. | SELECT * FROM ChirpMessages cm
WHERE cm.chirpId BETWEEN 10 AND 20;| -| = | Equality test | SELECT * FROM ChirpMessages cm
WHERE cm.chirpId=10; | -| != | Inequality test | SELECT * FROM ChirpMessages cm
WHERE cm.chirpId!=10;| -| <> | Inequality test | SELECT * FROM ChirpMessages cm
WHERE cm.chirpId<>10;| -| < | Less than | SELECT * FROM ChirpMessages cm
WHERE cm.chirpId<10; | -| > | Greater than | SELECT * FROM ChirpMessages cm
WHERE cm.chirpId>10; | -| <= | Less than or equal to | SELECT * FROM ChirpMessages cm
WHERE cm.chirpId<=10; | -| >= | Greater than or equal to | SELECT * FROM ChirpMessages cm
WHERE cm.chirpId>=10; | -| LIKE | Test if the left side matches a
pattern defined on the right
side; in the pattern, "%" matches
any string while "_" matches
any character. | SELECT * FROM ChirpMessages cm
WHERE cm.user.name LIKE "%Giesen%";| -| NOT LIKE | Test if the left side does not
match a pattern defined on the right
side; in the pattern, "%" matches
any string while "_" matches
any character. | SELECT * FROM ChirpMessages cm
WHERE cm.user.name NOT LIKE "%Giesen%";| - -The following table summarizes how the missing value comparison operators work. - -| Operator | Non-NULL/Non-MISSING value | NULL | MISSING | -|----------|----------------|------|---------| -| IS NULL | FALSE | TRUE | MISSING | -| IS NOT NULL | TRUE | FALSE | MISSING | -| IS MISSING | FALSE | FALSE | TRUE | -| IS NOT MISSING | TRUE | TRUE | FALSE | -| IS UNKNOWN | FALSE | TRUE | TRUE | -| IS NOT UNKNOWN | TRUE | FALSE | FALSE| -| IS KNOWN (IS VALUED) | TRUE | FALSE | FALSE | -| IS NOT KNOWN (IS NOT VALUED) | FALSE | TRUE | TRUE | - -### Logical Operators -Logical operators perform logical `NOT`, `AND`, and `OR` operations over Boolean values (`TRUE` and `FALSE`) plus `NULL` and `MISSING`. - -| Operator | Purpose | Example | -|----------|-----------------------------------------------------------------------------|------------| -| NOT | Returns true if the following condition is false, otherwise returns false | SELECT VALUE NOT TRUE; | -| AND | Returns true if both branches are true, otherwise returns false | SELECT VALUE TRUE AND FALSE; | -| OR | Returns true if one branch is true, otherwise returns false | SELECT VALUE FALSE OR FALSE; | - -The following table is the truth table for `AND` and `OR`. - -| A | B | A AND B | A OR B | -|----|----|----------|--------| -| TRUE | TRUE | TRUE | TRUE | -| TRUE | FALSE | FALSE | TRUE | -| TRUE | NULL | NULL | TRUE | -| TRUE | MISSING | MISSING | TRUE | -| FALSE | FALSE | FALSE | FALSE | -| FALSE | NULL | FALSE | NULL | -| FALSE | MISSING | FALSE | MISSING | -| NULL | NULL | NULL | NULL | -| NULL | MISSING | MISSING | NULL | -| MISSING | MISSING | MISSING | MISSING | - -The following table demonstrates the results of `NOT` on all possible inputs. - -| A | NOT A | -|----|----| -| TRUE | FALSE | -| FALSE | TRUE | -| NULL | NULL | -| MISSING | MISSING | - - -## Quantified Expressions - - QuantifiedExpression ::= ( (|) | ) Variable Expression ( "," Variable "in" Expression )* - Expression ()? - -Quantified expressions are used for expressing existential or universal predicates involving the elements of a -collection. - -The following pair of examples illustrate the use of a quantified expression to test that every (or some) element in the -set [1, 2, 3] of integers is less than three. The first example yields `FALSE` and second example yields `TRUE`. - -It is useful to note that if the set were instead the empty set, the first expression would yield `TRUE` ("every" value in an -empty set satisfies the condition) while the second expression would yield `FALSE` (since there isn't "some" value, as there are -no values in the set, that satisfies the condition). - -A quantified expression will return a `NULL` (or `MISSING`) if the first expression in it evaluates to `NULL` (or `MISSING`). -A type error will be raised if the first expression in a quantified expression does not return a collection. - -##### Examples - - EVERY x IN [ 1, 2, 3 ] SATISFIES x < 3 - SOME x IN [ 1, 2, 3 ] SATISFIES x < 3 - - -## Path Expressions - - PathExpression ::= PrimaryExpression ( Field | Index )* - Field ::= "." Identifier - Index ::= "[" Expression (":" ( Expression )? )? "]" - -Components of complex types in the data model are accessed via path expressions. Path access can be applied to the -result of a query expression that yields an instance of a complex type, for example, an object or an array instance. - -For objects, path access is based on field names, and it accesses the field whose name was specified.
-For arrays, path access is based on (zero-based) array-style indexing. Array indexes can be used to retrieve either a -single element from an array, or a whole subset of an array. Accessing a single element is achieved by -providing a single index argument (zero-based element position), while obtaining a subset of an array is achieved by -providing the `start` and `end` (zero-based) index positions; the returned subset is from position `start` to position -`end - 1`; the `end` position argument is optional. Multisets have similar behavior to arrays, except for retrieving -arbitrary items as the order of items is not fixed in multisets. - -Attempts to access non-existent fields or out-of-bound array elements produce the special value `MISSING`. Type errors -will be raised for inappropriate use of a path expression, such as applying a field accessor to a numeric value. - -The following examples illustrate field access for an object, index-based element access or subset retrieval of an array, -and also a composition thereof. - -##### Examples - - ({"name": "MyABCs", "array": [ "a", "b", "c"]}).array - - (["a", "b", "c"])[2] - - ({"name": "MyABCs", "array": [ "a", "b", "c"]}).array[2] - - (["a", "b", "c"])[0:2] - - (["a", "b", "c"])[0:] - - -## Primary Expressions - - PrimaryExpr ::= Literal - | VariableReference - | ParameterReference - | ParenthesizedExpression - | FunctionCallExpression - | CaseExpression - | Constructor - -The most basic building block for any expression in the query language is PrimaryExpression. -This can be a simple literal (constant) value, a reference to a query variable that is in scope, a parenthesized -expression, a function call, or a newly constructed instance of the data model (such as a newly constructed object, -array, or multiset of data model instances). - -## Literals - - Literal ::= StringLiteral - | IntegerLiteral - | FloatLiteral - | DoubleLiteral - | - | - | - | - StringLiteral ::= "\"" ( - - | - | - | - | - | - | - | - | ~["\"","\\"])* - "\"" - | "\'"( - - | - | - | - | - | - | - | - | ~["\'","\\"])* - "\'" - ::= "\\\'" - ::= "\\\"" - ::= "\\\\" - ::= "\\/" - ::= "\\b" - ::= "\\f" - ::= "\\n" - ::= "\\r" - ::= "\\t" - - IntegerLiteral ::= - ::= ["0" - "9"]+ - FloatLiteral ::= ( "f" | "F" ) - | ( "." ( "f" | "F" ) )? - | "." ( "f" | "F" ) - DoubleLiteral ::= "." - | "." - -Literals (constants) in a query can be strings, integers, floating point values, double values, boolean constants, or -special constant values like `NULL` and `MISSING`. -The `NULL` value is like a `NULL` in SQL; it is used to represent an unknown field value. -The special value `MISSING` is only meaningful in the context of field accesses; it occurs when the accessed field -simply does not exist at all in a object being accessed. - -The following are some simple examples of literals. - -##### Examples - - 'a string' - "test string" - 42 - -Different from standard SQL, double quotes play the same role as single quotes and may be used for string literals in queries as well. - -### Variable References - - VariableReference ::= | - ::= ( | "_") ( | | "_" | "$")* - ::= ["A" - "Z", "a" - "z"] - DelimitedIdentifier ::= "`" ( - | - | - | - | - | - | - | - | ~["`","\\"])* - "`" - -A variable in a query can be bound to any legal data model value. -A variable reference refers to the value to which an in-scope variable is bound. -(E.g., a variable binding may originate from one of the `FROM`, `WITH` or `LET` clauses of a `SELECT` statement or from -an input parameter in the context of a function body.) -Backticks, for example, \`id\`, are used for delimited identifiers. -Delimiting is needed when a variable's desired name clashes with a keyword or includes characters not allowed in regular -identifiers. -More information on exactly how variable references are resolved can be found in the appendix section on Variable -Resolution. - -##### Examples - - tweet - id - `SELECT` - `my-function` - -### Parameter References - - ParameterReference ::= NamedParameterReference | PositionalParameterReference - NamedParameterReference ::= "$" ( | ) - PositionalParameterReference ::= ("$" ) | "?" - -A statement parameter is an external variable which value is provided through the [statement execution API](../api.html#queryservice). -An error will be raised if the parameter is not bound at the query execution time. -Positional parameter numbering starts at 1. -"?" parameters are interpreted as $1, .. $N in the order in which they appear in the statement. - -##### Examples - - $id - $1 - ? - -### Parenthesized Expressions - - ParenthesizedExpression ::= "(" Expression ")" | Subquery - -An expression can be parenthesized to control the precedence order or otherwise clarify a query. -For composability, a subquery is also an parenthesized expression. - -The following expression evaluates to the value 2. - -##### Example - - ( 1 + 1 ) - -### Function Call Expressions - - FunctionCallExpression ::= ( FunctionName "(" ( Expression ( "," Expression )* )? ")" ) | WindowFunctionCall - -Functions are included in the query language, like most languages, as a way to package useful functionality or to -componentize complicated or reusable computations. -A function call is a legal query expression that represents the value resulting from the evaluation of its body -expression with the given parameter bindings; the parameter value bindings can themselves be any expressions in the -query language. - -Note that Window functions, and aggregate functions used as window functions, have a more complex syntax. -Window function calls are described in the section on [OVER Clauses](#Over_clauses). - -The following example is a (built-in) function call expression whose value is 8. - -##### Example - - length('a string') - -## Case Expressions - - CaseExpression ::= SimpleCaseExpression | SearchedCaseExpression - SimpleCaseExpression ::= Expression ( Expression Expression )+ ( Expression )? - SearchedCaseExpression ::= ( Expression Expression )+ ( Expression )? - -In a simple `CASE` expression, the query evaluator searches for the first `WHEN` ... `THEN` pair in which the `WHEN` expression is equal to the expression following `CASE` and returns the expression following `THEN`. If none of the `WHEN` ... `THEN` pairs meet this condition, and an `ELSE` branch exists, it returns the `ELSE` expression. Otherwise, `NULL` is returned. - -In a searched CASE expression, the query evaluator searches from left to right until it finds a `WHEN` expression that is evaluated to `TRUE`, and then returns its corresponding `THEN` expression. If no condition is found to be `TRUE`, and an `ELSE` branch exists, it returns the `ELSE` expression. Otherwise, it returns `NULL`. - -The following example illustrates the form of a case expression. - -##### Example - - CASE (2 < 3) WHEN true THEN "yes" ELSE "no" END - - -### Constructors - - Constructor ::= ArrayConstructor | MultisetConstructor | ObjectConstructor - ArrayConstructor ::= "[" ( Expression ( "," Expression )* )? "]" - MultisetConstructor ::= "{{" ( Expression ( "," Expression )* )? "}}" - ObjectConstructor ::= "{" ( FieldBinding ( "," FieldBinding )* )? "}" - FieldBinding ::= Expression ( ":" Expression )? - -A major feature of the query language is its ability to construct new data model instances. This is accomplished using -its constructors for each of the model's complex object structures, namely arrays, multisets, and objects. -Arrays are like JSON arrays, while multisets have bag semantics. -Objects are built from fields that are field-name/field-value pairs, again like JSON. - -The following examples illustrate how to construct a new array with 4 items and a new object with 2 fields respectively. -Array elements can be homogeneous (as in the first example), -which is the common case, or they may be heterogeneous (as in the second example). The data values and field name values -used to construct arrays, multisets, and objects in constructors are all simply query expressions. Thus, the collection -elements, field names, and field values used in constructors can be simple literals or they can come from query variable -references or even arbitrarily complex query expressions (subqueries). -Type errors will be raised if the field names in an object are not strings, and -duplicate field errors will be raised if they are not distinct. - -##### Examples - - [ 'a', 'b', 'c', 'c' ] - - [ 42, "forty-two!", { "rank" : "Captain", "name": "America" }, 3.14159 ] - - { - 'project name': 'Hyracks', - 'project members': [ 'vinayakb', 'dtabass', 'chenli', 'tsotras', 'tillw' ] - } - - -If only one expression is specified instead of the field-name/field-value pair in an object constructor then this -expression is supposed to provide the field value. The field name is then automatically generated based on the -kind of the value expression: - - * If it is a variable reference expression then generated field name is the name of that variable. - * If it is a field access expression then generated field name is the last identifier in that expression. - * For all other cases, a compilation error will be raised. - -##### Example - - SELECT VALUE { user.alias, user.userSince } - FROM GleambookUsers user - WHERE user.id = 1; - -This query outputs: - - [ { - "alias": "Margarita", - "userSince": "2012-08-20T10:10:00" - } ] - diff --git a/asterixdb/asterix-doc/src/main/markdown/sqlpp/2_expr_title.md b/asterixdb/asterix-doc/src/main/markdown/sqlpp/2_expr_title.md deleted file mode 100644 index 8b8f337ed9b..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/sqlpp/2_expr_title.md +++ /dev/null @@ -1,20 +0,0 @@ - - -# 2. Expressions diff --git a/asterixdb/asterix-doc/src/main/markdown/sqlpp/3_declare_dataverse.md b/asterixdb/asterix-doc/src/main/markdown/sqlpp/3_declare_dataverse.md deleted file mode 100644 index d33d680183c..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/sqlpp/3_declare_dataverse.md +++ /dev/null @@ -1,33 +0,0 @@ - - -## Declarations - - DatabaseDeclaration ::= "USE" Identifier - -At the uppermost level, the world of data is organized into data namespaces called **dataverses**. -To set the default dataverse for statements, the USE statement is provided. - -As an example, the following statement sets the default dataverse to be "TinySocial". - -##### Example - - USE TinySocial; - - diff --git a/asterixdb/asterix-doc/src/main/markdown/sqlpp/3_declare_function.md b/asterixdb/asterix-doc/src/main/markdown/sqlpp/3_declare_function.md deleted file mode 100644 index 8e77de90e95..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/sqlpp/3_declare_function.md +++ /dev/null @@ -1,45 +0,0 @@ - - -When writing a complex query, it can sometimes be helpful to define one or more auxilliary functions -that each address a sub-piece of the overall query. -The declare function statement supports the creation of such helper functions. -In general, the function body (expression) can be any legal query expression. - - FunctionDeclaration ::= "DECLARE" "FUNCTION" Identifier ParameterList "{" Expression "}" - ParameterList ::= "(" ( ( "," )* )? ")" - -The following is a simple example of a temporary function definition and its use. - -##### Example - - DECLARE FUNCTION friendInfo(userId) { - (SELECT u.id, u.name, len(u.friendIds) AS friendCount - FROM GleambookUsers u - WHERE u.id = userId)[0] - }; - - SELECT VALUE friendInfo(2); - -For our sample data set, this returns: - - [ - { "id": 2, "name": "IsbelDull", "friendCount": 2 } - ] - diff --git a/asterixdb/asterix-doc/src/main/markdown/sqlpp/3_query.md b/asterixdb/asterix-doc/src/main/markdown/sqlpp/3_query.md deleted file mode 100644 index e19e2ecd891..00000000000 --- a/asterixdb/asterix-doc/src/main/markdown/sqlpp/3_query.md +++ /dev/null @@ -1,2097 +0,0 @@ - - -## SELECT Statements - -The following shows the (rich) grammar for the `SELECT` statement in the query language. - - SelectStatement ::= ( WithClause )? - SelectSetOperation (OrderbyClause )? ( LimitClause )? - SelectSetOperation ::= SelectBlock ( ( SelectBlock | Subquery ) )* - Subquery ::= "(" SelectStatement ")" - - SelectBlock ::= SelectClause - ( FromClause ( LetClause )?)? - ( WhereClause )? - ( GroupbyClause ( LetClause )? ( HavingClause )? )? - | - FromClause ( LetClause )? - ( WhereClause )? - ( GroupbyClause ( LetClause )? ( HavingClause )? )? - SelectClause - - SelectClause ::= ( | )? ( SelectRegular | SelectValue ) +SelectRegular ::= Projection ( "," Projection )* +SelectValue ::= ( | | ) Expression +Projection ::= ( Expression ( )? Identifier | "*" | Identifier "." "*" ) + +FromClause ::= FromTerm ( "," FromTerm )* +FromTerm ::= Expression (( )? Variable)? + ( ( JoinType )? ( JoinClause | UnnestClause ) )* + +JoinClause ::= Expression (( )? Variable)? Expression +UnnestClause ::= ( ) Expression + ( )? Variable ( Variable )? +JoinType ::= ( | ( )? ) + +WithClause ::= WithElement ( "," WithElement )* +LetClause ::= ( | ) LetElement ( "," LetElement )* +LetElement ::= Variable "=" Expression +WithElement ::= Variable Expression + +WhereClause ::= Expression + +GroupbyClause ::= Expression ( ( ()? Variable )? + ( "," Expression ( ()? Variable )? )* ) + ( Variable + ("(" VariableReference Identifier + ("," VariableReference Identifier )* ")")? + )? +HavingClause ::= Expression + +OrderbyClause ::= Expression ( | )? + ( "," Expression ( | )? )* +LimitClause ::= Expression ( Expression )? +--------------------------------------------------------------------------------------- + +In this section, we will make use of two stored collections of objects +(datasets), `GleambookUsers` and `GleambookMessages`, in a series of +running examples to explain `SELECT` queries. The contents of the +example collections are as follows: + +`GleambookUsers` collection (or, dataset): + +-------------------------------------------------- +[ { + "id":1, + "alias":"Margarita", + "name":"MargaritaStoddard", + "nickname":"Mags", + "userSince":"2012-08-20T10:10:00", + "friendIds":[2,3,6,10], + "employment":[{ + "organizationName":"Codetechno", + "start-date":"2006-08-06" + }, + { + "organizationName":"geomedia", + "start-date":"2010-06-17", + "end-date":"2010-01-26" + }], + "gender":"F" +}, +{ + "id":2, + "alias":"Isbel", + "name":"IsbelDull", + "nickname":"Izzy", + "userSince":"2011-01-22T10:10:00", + "friendIds":[1,4], + "employment":[{ + "organizationName":"Hexviafind", + "startDate":"2010-04-27" + }] +}, +{ + "id":3, + "alias":"Emory", + "name":"EmoryUnk", + "userSince":"2012-07-10T10:10:00", + "friendIds":[1,5,8,9], + "employment":[{ + "organizationName":"geomedia", + "startDate":"2010-06-17", + "endDate":"2010-01-26" + }] +} ] +-------------------------------------------------- + +`GleambookMessages` collection (or, dataset): + +----------------------------------------------------------------- +[ { + "messageId":2, + "authorId":1, + "inResponseTo":4, + "senderLocation":[41.66,80.87], + "message":" dislike x-phone its touch-screen is horrible" +}, +{ + "messageId":3, + "authorId":2, + "inResponseTo":4, + "senderLocation":[48.09,81.01], + "message":" like product-y the plan is amazing" +}, +{ + "messageId":4, + "authorId":1, + "inResponseTo":2, + "senderLocation":[37.73,97.04], + "message":" can't stand acast the network is horrible:(" +}, +{ + "messageId":6, + "authorId":2, + "inResponseTo":1, + "senderLocation":[31.5,75.56], + "message":" like product-z its platform is mind-blowing" +} +{ + "messageId":8, + "authorId":1, + "inResponseTo":11, + "senderLocation":[40.33,80.87], + "message":" like ccast the 3G is awesome:)" +}, +{ + "messageId":10, + "authorId":1, + "inResponseTo":12, + "senderLocation":[42.5,70.01], + "message":" can't stand product-w the touch-screen is terrible" +}, +{ + "messageId":11, + "authorId":1, + "inResponseTo":1, + "senderLocation":[38.97,77.49], + "message":" can't stand acast its plan is terrible" +} ] +----------------------------------------------------------------- + +[[select-clause]] +=== SELECT Clause + +The `SELECT` clause always returns a collection value as its result +(even if the result is empty or a singleton). + +[[select-elementvalueraw]] +==== Select Element/Value/Raw + +The `SELECT VALUE` clause returns an array or multiset that contains the +results of evaluating the `VALUE` expression, with one evaluation being +performed per "binding tuple" (i.e., per `FROM` clause item) satisfying +the statement's selection criteria. For historical reasons the query +language also allows the keywords `ELEMENT` or `RAW` to be used in place +of `VALUE` (not recommended). + +If there is no FROM clause, the expression after `VALUE` is evaluated +once with no binding tuples (except those inherited from an outer +environment). + +[[example]] +Example + +--------------- +SELECT VALUE 1; +--------------- + +This query returns: + +--- +[ + 1 +] +--- + +The following example shows a query that selects one user from the +GleambookUsers collection. + +[[example-1]] +Example + +------------------------ +SELECT VALUE user +FROM GleambookUsers user +WHERE user.id = 1; +------------------------ + +This query returns: + +--------------------------------------------- +[{ + "userSince": "2012-08-20T10:10:00.000Z", + "friendIds": [ + 2, + 3, + 6, + 10 + ], + "gender": "F", + "name": "MargaritaStoddard", + "nickname": "Mags", + "alias": "Margarita", + "id": 1, + "employment": [ + { + "organizationName": "Codetechno", + "start-date": "2006-08-06" + }, + { + "end-date": "2010-01-26", + "organizationName": "geomedia", + "start-date": "2010-06-17" + } + ] +} ] +--------------------------------------------- + +[[sql-style-select]] +==== SQL-style SELECT + +The traditional SQL-style `SELECT` syntax is also supported in the query +language. This syntax can also be reformulated in a `SELECT VALUE` based +manner. (E.g., `SELECT expA AS fldA, expB AS fldB` is syntactic sugar +for `SELECT VALUE { 'fldA': expA, 'fldB': expB }`.) Unlike in SQL, the +result of a query does not preserve the order of expressions in the +`SELECT` clause. + +[[example-2]] +Example + +------------------------------------------------- +SELECT user.alias user_alias, user.name user_name +FROM GleambookUsers user +WHERE user.id = 1; +------------------------------------------------- + +Returns: + +------------------------------------- +[ { + "user_name": "MargaritaStoddard", + "user_alias": "Margarita" +} ] +------------------------------------- + +[[Select_star]] +==== SELECT * + +`SELECT *` returns an object with a nested field for each input +tuple. Each field has as its field name the name of a binding variable +generated by either the `FROM` clause or `GROUP BY` clause in the +current enclosing `SELECT` statement, and its field value is the value +of that binding variable. + +Note that the result of `SELECT *` is different from the result of query +that selects all the fields of an object. + +[[example-3]] +Example + +------------------------- +SELECT * +FROM GleambookUsers user; +------------------------- + +Since `user` is the only binding variable generated in the `FROM` +clause, this query returns: + +------------------------------------------------- +[ { + "user": { + "userSince": "2012-08-20T10:10:00.000Z", + "friendIds": [ + 2, + 3, + 6, + 10 + ], + "gender": "F", + "name": "MargaritaStoddard", + "nickname": "Mags", + "alias": "Margarita", + "id": 1, + "employment": [ + { + "organizationName": "Codetechno", + "start-date": "2006-08-06" + }, + { + "end-date": "2010-01-26", + "organizationName": "geomedia", + "start-date": "2010-06-17" + } + ] + } +}, { + "user": { + "userSince": "2011-01-22T10:10:00.000Z", + "friendIds": [ + 1, + 4 + ], + "name": "IsbelDull", + "nickname": "Izzy", + "alias": "Isbel", + "id": 2, + "employment": [ + { + "organizationName": "Hexviafind", + "startDate": "2010-04-27" + } + ] + } +}, { + "user": { + "userSince": "2012-07-10T10:10:00.000Z", + "friendIds": [ + 1, + 5, + 8, + 9 + ], + "name": "EmoryUnk", + "alias": "Emory", + "id": 3, + "employment": [ + { + "organizationName": "geomedia", + "endDate": "2010-01-26", + "startDate": "2010-06-17" + } + ] + } +} ] +------------------------------------------------- + +[[example-4]] +Example + +------------------------------------------ +SELECT * +FROM GleambookUsers u, GleambookMessages m +WHERE m.authorId = u.id and u.id = 2; +------------------------------------------ + +This query does an inner join that we will discuss in +<>. Since both `u` and `m` +are binding variables generated in the `FROM` clause, this query +returns: + +----------------------------------------------------------------- +[ { + "u": { + "userSince": "2011-01-22T10:10:00", + "friendIds": [ + 1, + 4 + ], + "name": "IsbelDull", + "nickname": "Izzy", + "alias": "Isbel", + "id": 2, + "employment": [ + { + "organizationName": "Hexviafind", + "startDate": "2010-04-27" + } + ] + }, + "m": { + "senderLocation": [ + 31.5, + 75.56 + ], + "inResponseTo": 1, + "messageId": 6, + "authorId": 2, + "message": " like product-z its platform is mind-blowing" + } +}, { + "u": { + "userSince": "2011-01-22T10:10:00", + "friendIds": [ + 1, + 4 + ], + "name": "IsbelDull", + "nickname": "Izzy", + "alias": "Isbel", + "id": 2, + "employment": [ + { + "organizationName": "Hexviafind", + "startDate": "2010-04-27" + } + ] + }, + "m": { + "senderLocation": [ + 48.09, + 81.01 + ], + "inResponseTo": 4, + "messageId": 3, + "authorId": 2, + "message": " like product-y the plan is amazing" + } +} ] +----------------------------------------------------------------- + +[[select-variable.]] +==== SELECT _variable_.* + +Whereas `SELECT *` returns all the fields bound to all the variables +which are currently defined, the notation `SELECT c.*` returns all the +fields of the object bound to variable `c`. The variable `c` must be +bound to an object for this to work. + +[[example-5]] +Example + +------------------------- +SELECT user.* +FROM GleambookUsers user; +------------------------- + +Compare this query with the first example given under +<>. This query returns all users from the +`GleambookUsers` dataset, but the `user` variable name is omitted from +the results: + +----------------------------------------- +[ + { + "id": 1, + "alias": "Margarita", + "name": "MargaritaStoddard", + "nickname": "Mags", + "userSince": "2012-08-20T10:10:00", + "friendIds": [ + 2, + 3, + 6, + 10 + ], + "employment": [ + { + "organizationName": "Codetechno", + "start-date": "2006-08-06" + }, + { + "organizationName": "geomedia", + "start-date": "2010-06-17", + "end-date": "2010-01-26" + } + ], + "gender": "F" + }, + { + "id": 2, + "alias": "Isbel", + "name": "IsbelDull", + "nickname": "Izzy", + "userSince": "2011-01-22T10:10:00", + "friendIds": [ + 1, + 4 + ], + "employment": [ + { + "organizationName": "Hexviafind", + "startDate": "2010-04-27" + } + ] + }, + { + "id": 3, + "alias": "Emory", + "name": "EmoryUnk", + "userSince": "2012-07-10T10:10:00", + "friendIds": [ + 1, + 5, + 8, + 9 + ], + "employment": [ + { + "organizationName": "geomedia", + "startDate": "2010-06-17", + "endDate": "2010-01-26" + } + ] + } +] +----------------------------------------- + +[[select-distinct]] +==== SELECT DISTINCT + +The `DISTINCT` keyword is used to eliminate duplicate items in results. +The following example shows how it works. + +[[example-6]] +Example + +------------------------------------------- +SELECT DISTINCT * FROM [1, 2, 2, 3] AS foo; +------------------------------------------- + +This query returns: + +------------ +[ { + "foo": 1 +}, { + "foo": 2 +}, { + "foo": 3 +} ] +------------ + +[[example-7]] +Example + +--------------------------------------------------- +SELECT DISTINCT VALUE foo FROM [1, 2, 2, 3] AS foo; +--------------------------------------------------- + +This version of the query returns: + +--- +[ 1 +, 2 +, 3 + ] +--- + +[[unnamed-projections]] +==== Unnamed Projections + +Similar to standard SQL, the query language supports unnamed projections +(a.k.a, unnamed `SELECT` clause items), for which names are generated. +Name generation has three cases: + +* If a projection expression is a variable reference expression, its +generated name is the name of the variable. +* If a projection expression is a field access expression, its generated +name is the last identifier in the expression. +* For all other cases, the query processor will generate a unique name. + +[[example-8]] +Example + +---------------------------------------- +SELECT substr(user.name, 10), user.alias +FROM GleambookUsers user +WHERE user.id = 1; +---------------------------------------- + +This query outputs: + +------------------------- +[ { + "alias": "Margarita", + "$1": "Stoddard" +} ] +------------------------- + +In the result, `$1` is the generated name for `substr(user.name, 1)`, +while `alias` is the generated name for `user.alias`. + +[[abbreviated-field-access-expressions]] +==== Abbreviated Field Access Expressions + +As in standard SQL, field access expressions can be abbreviated (not +recommended!) when there is no ambiguity. In the next example, the +variable `user` is the only possible variable reference for fields `id`, +`name` and `alias` and thus could be omitted in the query. More +information on abbbreviated field access can be found in the appendix +section on Variable Resolution. + +[[example-9]] +Example + +--------------------------------------- +SELECT substr(name, 10) AS lname, alias +FROM GleambookUsers user +WHERE id = 1; +--------------------------------------- + +Outputs: + +------------------------ +[ { + "lname": "Stoddard", + "alias": "Margarita" +} ] +------------------------ + +[[unnest-clause]] +=== UNNEST Clause + +For each of its input tuples, the `UNNEST` clause flattens a +collection-valued expression into individual items, producing multiple +tuples, each of which is one of the expression's original input tuples +augmented with a flattened item from its collection. + +[[inner-unnest]] +==== Inner UNNEST + +The following example is a query that retrieves the names of the +organizations that a selected user has worked for. It uses the `UNNEST` +clause to unnest the nested collection `employment` in the user's +object. + +[[example-10]] +Example + +---------------------------------------------------- +SELECT u.id AS userId, e.organizationName AS orgName +FROM GleambookUsers u +UNNEST u.employment e +WHERE u.id = 1; +---------------------------------------------------- + +This query returns: + +---------------------------- +[ { + "orgName": "Codetechno", + "userId": 1 +}, { + "orgName": "geomedia", + "userId": 1 +} ] +---------------------------- + +Note that `UNNEST` has SQL's inner join semantics --- that is, if a user +has no employment history, no tuple corresponding to that user will be +emitted in the result. + +[[left-outer-unnest]] +==== Left Outer UNNEST + +As an alternative, the `LEFT OUTER UNNEST` clause offers SQL's left +outer join semantics. For example, no collection-valued field named +`hobbies` exists in the object for the user whose id is 1, but the +following query's result still includes user 1. + +[[example-11]] +Example + +------------------------------------------- +SELECT u.id AS userId, h.hobbyName AS hobby +FROM GleambookUsers u +LEFT OUTER UNNEST u.hobbies h +WHERE u.id = 1; +------------------------------------------- + +Returns: + +--------------- +[ { + "userId": 1 +} ] +--------------- + +Note that if `u.hobbies` is an empty collection or leads to a `MISSING` +(as above) or `NULL` value for a given input tuple, there is no +corresponding binding value for variable `h` for an input tuple. A +`MISSING` value will be generated for `h` so that the input tuple can +still be propagated. + +[[expressing-joins-using-unnest]] +==== Expressing Joins Using UNNEST + +The `UNNEST` clause is similar to SQL's `JOIN` clause except that it +allows its right argument to be correlated to its left argument, as in +the examples above --- i.e., think "correlated cross-product". The next +example shows this via a query that joins two data sets, GleambookUsers +and GleambookMessages, returning user/message pairs. The results contain +one object per pair, with result objects containing the user's name and +an entire message. The query can be thought of as saying "for each +Gleambook user, unnest the `GleambookMessages` collection and filter the +output with the condition `message.authorId = user.id`". + +[[example-12]] +Example + +-------------------------------------------- +SELECT u.name AS uname, m.message AS message +FROM GleambookUsers u +UNNEST GleambookMessages m +WHERE m.authorId = u.id; +-------------------------------------------- + +This returns: + +-------------------------------------------------------------------- +[ { + "uname": "MargaritaStoddard", + "message": " can't stand acast its plan is terrible" +}, { + "uname": "MargaritaStoddard", + "message": " dislike x-phone its touch-screen is horrible" +}, { + "uname": "MargaritaStoddard", + "message": " can't stand acast the network is horrible:(" +}, { + "uname": "MargaritaStoddard", + "message": " like ccast the 3G is awesome:)" +}, { + "uname": "MargaritaStoddard", + "message": " can't stand product-w the touch-screen is terrible" +}, { + "uname": "IsbelDull", + "message": " like product-z its platform is mind-blowing" +}, { + "uname": "IsbelDull", + "message": " like product-y the plan is amazing" +} ] +-------------------------------------------------------------------- + +Similarly, the above query can also be expressed as the `UNNEST`ing of a +correlated subquery: + +[[example-13]] +Example + +-------------------------------------------- +SELECT u.name AS uname, m.message AS message +FROM GleambookUsers u +UNNEST ( + SELECT VALUE msg + FROM GleambookMessages msg + WHERE msg.authorId = u.id +) AS m; +-------------------------------------------- + +[[from-clauses]] +=== FROM clauses + +A `FROM` clause is used for enumerating (i.e., conceptually iterating +over) the contents of collections, as in SQL. + +[[binding-expressions]] +==== Binding expressions + +In addition to stored collections, a `FROM` clause can iterate over any +intermediate collection returned by a valid query expression. In the +tuple stream generated by a `FROM` clause, the ordering of the input +tuples are not guaranteed to be preserved. + +[[example-14]] +Example + +------------------------ +SELECT VALUE foo +FROM [1, 2, 2, 3] AS foo +WHERE foo > 2; +------------------------ + +Returns: + +--- +[ + 3 +] +--- + +[[Multiple_from_terms]] +==== Multiple FROM Terms + +The query language permits correlations among `FROM` terms. +Specifically, a `FROM` binding expression can refer to variables defined +to its left in the given `FROM` clause. Thus, the first unnesting +example above could also be expressed as follows: + +[[example-15]] +Example + +---------------------------------------------------- +SELECT u.id AS userId, e.organizationName AS orgName +FROM GleambookUsers u, u.employment e +WHERE u.id = 1; +---------------------------------------------------- + +[[expressing-joins-using-from-terms]] +==== Expressing Joins Using FROM Terms + +Similarly, the join intentions of the other `UNNEST`-based join examples +above could be expressed as: + +[[example-16]] +Example + +-------------------------------------------- +SELECT u.name AS uname, m.message AS message +FROM GleambookUsers u, GleambookMessages m +WHERE m.authorId = u.id; +-------------------------------------------- + +[[example-17]] +Example + +-------------------------------------------- +SELECT u.name AS uname, m.message AS message +FROM GleambookUsers u, + ( + SELECT VALUE msg + FROM GleambookMessages msg + WHERE msg.authorId = u.id + ) AS m; +-------------------------------------------- + +Note that the first alternative is one of the SQL-92 approaches to +expressing a join. + +[[implicit-binding-variables]] +==== Implicit Binding Variables + +Similar to standard SQL, the query language supports implicit `FROM` +binding variables (i.e., aliases), for which a binding variable is +generated. Variable generation falls into three cases: + +* If the binding expression is a variable reference expression, the +generated variable's name will be the name of the referenced variable +itself. +* If the binding expression is a field access expression (or a fully +qualified name for a dataset), the generated variable's name will be the +last identifier (or the dataset name) in the expression. +* For all other cases, a compilation error will be raised. + +The next two examples show queries that do not provide binding variables +in their `FROM` clauses. + +[[example-18]] +Example + +----------------------------------------------------- +SELECT GleambookUsers.name, GleambookMessages.message +FROM GleambookUsers, GleambookMessages +WHERE GleambookMessages.authorId = GleambookUsers.id; +----------------------------------------------------- + +Returns: + +-------------------------------------------------------------------- +[ { + "name": "MargaritaStoddard", + "message": " like ccast the 3G is awesome:)" +}, { + "name": "MargaritaStoddard", + "message": " can't stand product-w the touch-screen is terrible" +}, { + "name": "MargaritaStoddard", + "message": " can't stand acast its plan is terrible" +}, { + "name": "MargaritaStoddard", + "message": " dislike x-phone its touch-screen is horrible" +}, { + "name": "MargaritaStoddard", + "message": " can't stand acast the network is horrible:(" +}, { + "name": "IsbelDull", + "message": " like product-y the plan is amazing" +}, { + "name": "IsbelDull", + "message": " like product-z its platform is mind-blowing" +} ] +-------------------------------------------------------------------- + +[[example-19]] +Example + +-------------------------------------------------------- +SELECT GleambookUsers.name, GleambookMessages.message +FROM GleambookUsers, + ( + SELECT VALUE GleambookMessages + FROM GleambookMessages + WHERE GleambookMessages.authorId = GleambookUsers.id + ); +-------------------------------------------------------- + +Returns: + +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ +Error: "Syntax error: Need an alias for the enclosed expression:\n(select element GleambookMessages\n from GleambookMessages as GleambookMessages\n where (GleambookMessages.authorId = GleambookUsers.id)\n )", + "query_from_user": "use TinySocial;\n\nSELECT GleambookUsers.name, GleambookMessages.message\n FROM GleambookUsers,\n (\n SELECT VALUE GleambookMessages\n FROM GleambookMessages\n WHERE GleambookMessages.authorId = GleambookUsers.id\n );" +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ + +More information on implicit binding variables can be found in the +appendix section on Variable Resolution. + +[[join-clauses]] +=== JOIN Clauses + +The join clause in the query language supports both inner joins and left +outer joins from standard SQL. + +[[inner-joins]] +==== Inner joins + +Using a `JOIN` clause, the inner join intent from the preceding examples +can also be expressed as follows: + +[[example-20]] +Example + +-------------------------------------------------------------------- +SELECT u.name AS uname, m.message AS message +FROM GleambookUsers u JOIN GleambookMessages m ON m.authorId = u.id; +-------------------------------------------------------------------- + +[[left-outer-joins]] +==== Left Outer Joins + +The query language supports SQL's notion of left outer join. The +following query is an example: + +------------------------------------------------------------------------------- +SELECT u.name AS uname, m.message AS message +FROM GleambookUsers u LEFT OUTER JOIN GleambookMessages m ON m.authorId = u.id; +------------------------------------------------------------------------------- + +Returns: + +-------------------------------------------------------------------- +[ { + "uname": "MargaritaStoddard", + "message": " like ccast the 3G is awesome:)" +}, { + "uname": "MargaritaStoddard", + "message": " can't stand product-w the touch-screen is terrible" +}, { + "uname": "MargaritaStoddard", + "message": " can't stand acast its plan is terrible" +}, { + "uname": "MargaritaStoddard", + "message": " dislike x-phone its touch-screen is horrible" +}, { + "uname": "MargaritaStoddard", + "message": " can't stand acast the network is horrible:(" +}, { + "uname": "IsbelDull", + "message": " like product-y the plan is amazing" +}, { + "uname": "IsbelDull", + "message": " like product-z its platform is mind-blowing" +}, { + "uname": "EmoryUnk" +} ] +-------------------------------------------------------------------- + +For non-matching left-side tuples, the query language produces `MISSING` +values for the right-side binding variables; that is why the last object +in the above result doesn't have a `message` field. Note that this is +slightly different from standard SQL, which instead would fill in `NULL` +values for the right-side fields. The reason for this difference is +that, for non-matches in its join results, the query language views +fields from the right-side as being "not there" (a.k.a. `MISSING`) +instead of as being "there but unknown" (i.e., `NULL`). + +The left-outer join query can also be expressed using +`LEFT OUTER UNNEST`: + +-------------------------------------------- +SELECT u.name AS uname, m.message AS message +FROM GleambookUsers u +LEFT OUTER UNNEST ( + SELECT VALUE message + FROM GleambookMessages message + WHERE message.authorId = u.id + ) m; +-------------------------------------------- + +In general, SQL-style join queries can also be expressed by `UNNEST` +clauses and left outer join queries can be expressed by +`LEFT OUTER UNNESTs`. + +[[variable-scope-in-join-clauses]] +==== Variable scope in JOIN clauses + +Variables defined by `JOIN` subclauses are not visible to other +subclauses in the same `FROM` clause. This also applies to the `FROM` +variable that starts the `JOIN` subclause. + +[[example-21]] +Example + +-------------------------------- +SELECT * FROM GleambookUsers u +JOIN (SELECT VALUE m + FROM GleambookMessages m + WHERE m.authorId = u.id) m +ON u.id = m.authorId; +-------------------------------- + +The variable `u` defined by the `FROM` clause is not visible inside the +`JOIN` subclause, so this query returns no results. + +[[group-by-clauses]] +=== GROUP BY Clauses + +The `GROUP BY` clause generalizes standard SQL's grouping and +aggregation semantics, but it also retains backward compatibility with +the standard (relational) SQL `GROUP BY` and aggregation features. + +[[group-variables]] +==== Group variables + +In a `GROUP BY` clause, in addition to the binding variable(s) defined +for the grouping key(s), the query language allows a user to define a +_group variable_ by using the clause's `GROUP AS` extension to denote +the resulting group. After grouping, then, the query's in-scope +variables include the grouping key's binding variables as well as this +group variable which will be bound to one collection value for each +group. This per-group collection (i.e., multiset) value will be a set of +nested objects in which each field of the object is the result of a +renamed variable defined in parentheses following the group variable's +name. The `GROUP AS` syntax is as follows: + +------------------------------------------------------------------------------------------------------------ + Variable ("(" VariableReference Identifier ("," VariableReference Identifier )* ")")? +------------------------------------------------------------------------------------------------------------ + +[[example-22]] +Example + +--------------------------------------------------------------- +SELECT * +FROM GleambookMessages message +GROUP BY message.authorId AS uid GROUP AS msgs(message AS msg); +--------------------------------------------------------------- + +This first example query returns: + +-------------------------------------------------------------------------------- +[ { + "msgs": [ + { + "msg": { + "senderLocation": [ + 38.97, + 77.49 + ], + "inResponseTo": 1, + "messageId": 11, + "authorId": 1, + "message": " can't stand acast its plan is terrible" + } + }, + { + "msg": { + "senderLocation": [ + 41.66, + 80.87 + ], + "inResponseTo": 4, + "messageId": 2, + "authorId": 1, + "message": " dislike x-phone its touch-screen is horrible" + } + }, + { + "msg": { + "senderLocation": [ + 37.73, + 97.04 + ], + "inResponseTo": 2, + "messageId": 4, + "authorId": 1, + "message": " can't stand acast the network is horrible:(" + } + }, + { + "msg": { + "senderLocation": [ + 40.33, + 80.87 + ], + "inResponseTo": 11, + "messageId": 8, + "authorId": 1, + "message": " like ccast the 3G is awesome:)" + } + }, + { + "msg": { + "senderLocation": [ + 42.5, + 70.01 + ], + "inResponseTo": 12, + "messageId": 10, + "authorId": 1, + "message": " can't stand product-w the touch-screen is terrible" + } + } + ], + "uid": 1 +}, { + "msgs": [ + { + "msg": { + "senderLocation": [ + 31.5, + 75.56 + ], + "inResponseTo": 1, + "messageId": 6, + "authorId": 2, + "message": " like product-z its platform is mind-blowing" + } + }, + { + "msg": { + "senderLocation": [ + 48.09, + 81.01 + ], + "inResponseTo": 4, + "messageId": 3, + "authorId": 2, + "message": " like product-y the plan is amazing" + } + } + ], + "uid": 2 +} ] +-------------------------------------------------------------------------------- + +As we can see from the above query result, each group in the example +query's output has an associated group variable value called `msgs` that +appears in the `SELECT *`'s result. This variable contains a collection +of objects associated with the group; each of the group's `message` +values appears in the `msg` field of the objects in the `msgs` +collection. + +The group variable in the query language makes more complex, composable, +nested subqueries over a group possible, which is important given the +language's more complex data model (relative to SQL). As a simple +example of this, as we really just want the messages associated with +each user, we might wish to avoid the "extra wrapping" of each message +as the `msg` field of an object. (That wrapping is useful in more +complex cases, but is essentially just in the way here.) We can use a +subquery in the `SELECT` clause to tunnel through the extra nesting and +produce the desired result. + +[[example-23]] +Example + +----------------------------------------------- +SELECT uid, (SELECT VALUE g.msg FROM g) AS msgs +FROM GleambookMessages gbm +GROUP BY gbm.authorId AS uid +GROUP AS g(gbm as msg); +----------------------------------------------- + +This variant of the example query returns: + +------------------------------------------------------------------------------- + [ { + "msgs": [ + { + "senderLocation": [ + 38.97, + 77.49 + ], + "inResponseTo": 1, + "messageId": 11, + "authorId": 1, + "message": " can't stand acast its plan is terrible" + }, + { + "senderLocation": [ + 41.66, + 80.87 + ], + "inResponseTo": 4, + "messageId": 2, + "authorId": 1, + "message": " dislike x-phone its touch-screen is horrible" + }, + { + "senderLocation": [ + 37.73, + 97.04 + ], + "inResponseTo": 2, + "messageId": 4, + "authorId": 1, + "message": " can't stand acast the network is horrible:(" + }, + { + "senderLocation": [ + 40.33, + 80.87 + ], + "inResponseTo": 11, + "messageId": 8, + "authorId": 1, + "message": " like ccast the 3G is awesome:)" + }, + { + "senderLocation": [ + 42.5, + 70.01 + ], + "inResponseTo": 12, + "messageId": 10, + "authorId": 1, + "message": " can't stand product-w the touch-screen is terrible" + } + ], + "uid": 1 + }, { + "msgs": [ + { + "senderLocation": [ + 31.5, + 75.56 + ], + "inResponseTo": 1, + "messageId": 6, + "authorId": 2, + "message": " like product-z its platform is mind-blowing" + }, + { + "senderLocation": [ + 48.09, + 81.01 + ], + "inResponseTo": 4, + "messageId": 3, + "authorId": 2, + "message": " like product-y the plan is amazing" + } + ], + "uid": 2 + } ] +------------------------------------------------------------------------------- + +The next example shows a more interesting case involving the use of a +subquery in the `SELECT` list. Here the subquery further processes the +groups. There is no renaming in the declaration of the group variable +`g` such that `g` only has one field `gbm` which comes from the `FROM` +clause. + +[[example-24]] +Example + +------------------------------------------ +SELECT uid, + (SELECT VALUE g.gbm + FROM g + WHERE g.gbm.message LIKE '% like%' + ORDER BY g.gbm.messageId + LIMIT 2) AS msgs +FROM GleambookMessages gbm +GROUP BY gbm.authorId AS uid +GROUP AS g; +------------------------------------------ + +This example query returns: + +--------------------------------------------------------------------- +[ { + "msgs": [ + { + "senderLocation": [ + 40.33, + 80.87 + ], + "inResponseTo": 11, + "messageId": 8, + "authorId": 1, + "message": " like ccast the 3G is awesome:)" + } + ], + "uid": 1 +}, { + "msgs": [ + { + "senderLocation": [ + 48.09, + 81.01 + ], + "inResponseTo": 4, + "messageId": 3, + "authorId": 2, + "message": " like product-y the plan is amazing" + }, + { + "senderLocation": [ + 31.5, + 75.56 + ], + "inResponseTo": 1, + "messageId": 6, + "authorId": 2, + "message": " like product-z its platform is mind-blowing" + } + ], + "uid": 2 +} ] +--------------------------------------------------------------------- + +[[implicit-grouping-key-variables]] +==== Implicit Grouping Key Variables + +In the query language syntax, providing named binding variables for +`GROUP BY` key expressions is optional. If a grouping key is missing a +user-provided binding variable, the underlying compiler will generate +one. Automatic grouping key variable naming falls into three cases, much +like the treatment of unnamed projections: + +* If the grouping key expression is a variable reference expression, the +generated variable gets the same name as the referred variable; +* If the grouping key expression is a field access expression, the +generated variable gets the same name as the last identifier in the +expression; +* For all other cases, the compiler generates a unique variable (but the +user query is unable to refer to this generated variable). + +The next example illustrates a query that doesn't provide binding +variables for its grouping key expressions. + +[[example-25]] +Example + +------------------------------------------ +SELECT authorId, + (SELECT VALUE g.gbm + FROM g + WHERE g.gbm.message LIKE '% like%' + ORDER BY g.gbm.messageId + LIMIT 2) AS msgs +FROM GleambookMessages gbm +GROUP BY gbm.authorId +GROUP AS g; +------------------------------------------ + +This query returns: + +--------------------------------------------------------------------- + [ { + "msgs": [ + { + "senderLocation": [ + 40.33, + 80.87 + ], + "inResponseTo": 11, + "messageId": 8, + "authorId": 1, + "message": " like ccast the 3G is awesome:)" + } + ], + "authorId": 1 +}, { + "msgs": [ + { + "senderLocation": [ + 48.09, + 81.01 + ], + "inResponseTo": 4, + "messageId": 3, + "authorId": 2, + "message": " like product-y the plan is amazing" + }, + { + "senderLocation": [ + 31.5, + 75.56 + ], + "inResponseTo": 1, + "messageId": 6, + "authorId": 2, + "message": " like product-z its platform is mind-blowing" + } + ], + "authorId": 2 +} ] +--------------------------------------------------------------------- + +Based on the three variable generation rules, the generated variable for +the grouping key expression `message.authorId` is `authorId` (which is +how it is referred to in the example's `SELECT` clause). + +[[Implicit_group_variables]] +==== Implicit Group Variables + +The group variable itself is also optional in the `GROUP BY` syntax. If +a user's query does not declare the name and structure of the group +variable using `GROUP AS`, the query compiler will generate a unique +group variable whose fields include all of the binding variables defined +in the `FROM` clause of the current enclosing `SELECT` statement. In +this case the user's query will not be able to refer to the generated +group variable, but is able to call SQL-92 aggregation functions as in +SQL-92. + +[[aggregation-functions]] +==== Aggregation Functions + +In the traditional SQL, which doesn't support nested data, grouping +always also involves the use of aggregation to compute properties of the +groups (for example, the average number of messages per user rather than +the actual set of messages per user). Each aggregation function in the +query language takes a collection (for example, the group of messages) +as its input and produces a scalar value as its output. These +aggregation functions, being truly functional in nature (unlike in SQL), +can be used anywhere in a query where an expression is allowed. The +following table catalogs the built-in aggregation functions of the query +language and also indicates how each one handles `NULL`/`MISSING` values +in the input collection or a completely empty input collection: + +[cols=",,,",options="header",] +|============================================================ +|Function |NULL |MISSING |Empty Collection +|STRICT_COUNT |counted |counted |0 +|STRICT_SUM |returns NULL |returns NULL |returns NULL +|STRICT_MAX |returns NULL |returns NULL |returns NULL +|STRICT_MIN |returns NULL |returns NULL |returns NULL +|STRICT_AVG |returns NULL |returns NULL |returns NULL +|STRICT_STDDEV_SAMP |returns NULL |returns NULL |returns NULL +|STRICT_STDDEV_POP |returns NULL |returns NULL |returns NULL +|STRICT_VAR_SAMP |returns NULL |returns NULL |returns NULL +|STRICT_VAR_POP |returns NULL |returns NULL |returns NULL +|STRICT_SKEWNESS |returns NULL |returns NULL |returns NULL +|STRICT_KURTOSIS |returns NULL |returns NULL |returns NULL +|ARRAY_COUNT |not counted |not counted |0 +|ARRAY_SUM |ignores NULL |ignores NULL |returns NULL +|ARRAY_MAX |ignores NULL |ignores NULL |returns NULL +|ARRAY_MIN |ignores NULL |ignores NULL |returns NULL +|ARRAY_AVG |ignores NULL |ignores NULL |returns NULL +|ARRAY_STDDEV_SAMP |ignores NULL |ignores NULL |returns NULL +|ARRAY_STDDEV_POP |ignores NULL |ignores NULL |returns NULL +|ARRAY_VAR_SAMP |ignores NULL |ignores NULL |returns NULL +|ARRAY_VAR_POP |ignores NULL |ignores NULL |returns NULL +|ARRAY_SKEWNESS |ignores NULL |ignores NULL |returns NULL +|ARRAY_KURTOSIS |ignores NULL |ignores NULL |returns NULL +|============================================================ + +Notice that the query language offers two versions for each of the +aggregate functions listed above. For each function, the STRICT version +handles `UNKNOWN` values in a semantically strict fashion, where unknown +values in the input result in unknown values in the output; and the +ARRAY version handles them in the ad hoc "just ignore the unknown +values" fashion that the SQL standard chose to adopt. + +[[example-26]] +Example + +------------------------------------------------------------- +ARRAY_AVG( + ( + SELECT VALUE ARRAY_COUNT(friendIds) FROM GleambookUsers + ) +); +------------------------------------------------------------- + +This example returns: + +------------------ +3.3333333333333335 +------------------ + +[[example-27]] +Example + +--------------------------------------------- +SELECT uid AS uid, ARRAY_COUNT(grp) AS msgCnt +FROM GleambookMessages message +GROUP BY message.authorId AS uid +GROUP AS grp(message AS msg); +--------------------------------------------- + +This query returns: + +--------------- +[ { + "uid": 1, + "msgCnt": 5 +}, { + "uid": 2, + "msgCnt": 2 +} ] +--------------- + +Notice how the query forms groups where each group involves a message +author and their messages. (SQL cannot do this because the grouped +intermediate result is non-1NF in nature.) The query then uses the +collection aggregate function ARRAY_COUNT to get the cardinality of each +group of messages. + +Each aggregation function in the query language supports the DISTINCT +modifier that removes duplicate values from the input collection. + +[[example-28]] +Example + +----------------------------------- +ARRAY_SUM(DISTINCT [1, 1, 2, 2, 3]) +----------------------------------- + +This query returns: + +- +6 +- + +[[sql-92-aggregation-functions]] +==== SQL-92 Aggregation Functions + +For compatibility with the traditional SQL aggregation functions, the +query language also offers SQL-92's aggregation function symbols +(`COUNT`, `SUM`, `MAX`, `MIN`, `AVG`, `ARRAY_AGG`, `STDDEV_SAMP`, +`STDDEV_POP`, `VAR_SAMP`, `VAR_POP`) as supported syntactic sugar. The +query compiler rewrites queries that utilize these function symbols into +queries that only use the collection aggregate functions of the query +language. The following example uses the SQL-92 syntax approach to +compute a result that is identical to that of the more explicit example +above: + +[[example-29]] +Example + +------------------------------ +SELECT uid, COUNT(*) AS msgCnt +FROM GleambookMessages msg +GROUP BY msg.authorId AS uid; +------------------------------ + +It is important to realize that `COUNT` is actually *not* a built-in +aggregation function. Rather, the `COUNT` query above is using a special +"sugared" function symbol that the query compiler will rewrite as +follows: + +--------------------------------------------------------------------------- +SELECT uid AS uid, ARRAY_COUNT( (SELECT VALUE 1 FROM `$1` as g) ) AS msgCnt +FROM GleambookMessages msg +GROUP BY msg.authorId AS uid +GROUP AS `$1`(msg AS msg); +--------------------------------------------------------------------------- + +The same sort of rewritings apply to the function symbols `SUM`, `MAX`, +`MIN`, `AVG`, `ARRAY_AGG`,`STDDEV_SAMP`, `STDDEV_POP`, `VAR_SAMP`, and +`VAR_POP`. In contrast to the collection aggregate functions of the +query language, these special SQL-92 function symbols can only be used +in the same way they are in standard SQL (i.e., with the same +restrictions). + +The DISTINCT modifier is also supported for these aggregate functions. + +The following table shows the SQL-92 functions supported by the query +language, their aliases where available, and their corresponding +built-in functions. + +[cols=",,",options="header",] +|========================================================= +|SQL-92 Function |Aliases |Corresponding Built-in Function +|COUNT | |ARRAY_COUNT +|SUM | |ARRAY_SUM +|MAX | |ARRAY_MAX +|MIN | |ARRAY_MIN +|AVG | |ARRAY_AVG +|ARRAY_AGG | |(none) +|STDDEV_SAMP |STDDEV |ARRAY_STDDEV_SAMP +|STDDEV_POP | |ARRAY_STDDEV_POP +|VAR_SAMP |VARIANCE, VARIANCE_SAMP |ARRAY_VAR_SAMP +|VAR_POP |VARIANCE_POP |ARRAY_VAR_POP +|========================================================= + +Note that the `ARRAY_AGG` function symbol is rewritten simply to return +the result of the generated subquery, without applying any built-in +function. + +[[sql-92-compliant-group-by-aggregations]] +==== SQL-92 Compliant GROUP BY Aggregations + +The query language provides full support for SQL-92 `GROUP BY` +aggregation queries. The following query is such an example: + +[[example-30]] +Example + +----------------------------- +SELECT msg.authorId, COUNT(*) +FROM GleambookMessages msg +GROUP BY msg.authorId; +----------------------------- + +This query outputs: + +------------------ +[ { + "authorId": 1, + "$1": 5 +}, { + "authorId": 2, + "$1": 2 +} ] +------------------ + +In principle, a `msg` reference in the query's `SELECT` clause would be +"sugarized" as a collection (as described in +<>). However, +since the SELECT expression `msg.authorId` is syntactically identical to +a GROUP BY key expression, it will be internally replaced by the +generated group key variable. The following is the equivalent rewritten +query that will be generated by the compiler for the query above: + +------------------------------------------------------------------------- +SELECT authorId AS authorId, ARRAY_COUNT( (SELECT g.msg FROM `$1` AS g) ) +FROM GleambookMessages msg +GROUP BY msg.authorId AS authorId +GROUP AS `$1`(msg AS msg); +------------------------------------------------------------------------- + +[[column-aliases]] +==== Column Aliases + +The query language also allows column aliases to be used as `ORDER BY` +keys. + +[[example-31]] +Example + +------------------------------------ +SELECT msg.authorId AS aid, COUNT(*) +FROM GleambookMessages msg +GROUP BY msg.authorId; +ORDER BY aid; +------------------------------------ + +This query returns: + +------------ +[ { + "$1": 5, + "aid": 1 +}, { + "$1": 2, + "aid": 2 +} ] +------------ + +[[where-clauses-and-having-clauses]] +=== WHERE Clauses and HAVING Clauses + +Both `WHERE` clauses and `HAVING` clauses are used to filter input data +based on a condition expression. Only tuples for which the condition +expression evaluates to `TRUE` are propagated. Note that if the +condition expression evaluates to `NULL` or `MISSING` the input tuple +will be discarded. + +[[Order_By_clauses]] +=== ORDER BY Clauses + +The `ORDER BY` clause is used to globally sort data in either ascending +order (i.e., `ASC`) or descending order (i.e., `DESC`). During ordering, +`MISSING` and `NULL` are treated as being smaller than any other value +if they are encountered in the ordering key(s). `MISSING` is treated as +smaller than `NULL` if both occur in the data being sorted. The ordering +of values of a given type is consistent with its type's <= ordering; the +ordering of values across types is implementation-defined but stable. +The following example returns all `GleambookUsers` in descending order +by their number of friends. + +[[example-32]] +Example + +-------------------------------------------- + SELECT VALUE user + FROM GleambookUsers AS user + ORDER BY ARRAY_COUNT(user.friendIds) DESC; +-------------------------------------------- + +This query returns: + +----------------------------------------------- + [ { + "userSince": "2012-08-20T10:10:00.000Z", + "friendIds": [ + 2, + 3, + 6, + 10 + ], + "gender": "F", + "name": "MargaritaStoddard", + "nickname": "Mags", + "alias": "Margarita", + "id": 1, + "employment": [ + { + "organizationName": "Codetechno", + "start-date": "2006-08-06" + }, + { + "end-date": "2010-01-26", + "organizationName": "geomedia", + "start-date": "2010-06-17" + } + ] + }, { + "userSince": "2012-07-10T10:10:00.000Z", + "friendIds": [ + 1, + 5, + 8, + 9 + ], + "name": "EmoryUnk", + "alias": "Emory", + "id": 3, + "employment": [ + { + "organizationName": "geomedia", + "endDate": "2010-01-26", + "startDate": "2010-06-17" + } + ] + }, { + "userSince": "2011-01-22T10:10:00.000Z", + "friendIds": [ + 1, + 4 + ], + "name": "IsbelDull", + "nickname": "Izzy", + "alias": "Isbel", + "id": 2, + "employment": [ + { + "organizationName": "Hexviafind", + "startDate": "2010-04-27" + } + ] + } ] +----------------------------------------------- + +[[limit-clauses]] +=== LIMIT Clauses + +The `LIMIT` clause is used to limit the result set to a specified +constant size. The use of the `LIMIT` clause is illustrated in the next +example. + +[[example-33]] +Example + +----------------------------------- + SELECT VALUE user + FROM GleambookUsers AS user + ORDER BY len(user.friendIds) DESC + LIMIT 1; +----------------------------------- + +This query returns: + +----------------------------------------------- + [ { + "userSince": "2012-08-20T10:10:00.000Z", + "friendIds": [ + 2, + 3, + 6, + 10 + ], + "gender": "F", + "name": "MargaritaStoddard", + "nickname": "Mags", + "alias": "Margarita", + "id": 1, + "employment": [ + { + "organizationName": "Codetechno", + "start-date": "2006-08-06" + }, + { + "end-date": "2010-01-26", + "organizationName": "geomedia", + "start-date": "2010-06-17" + } + ] + } ] +----------------------------------------------- + +[[with-clauses]] +=== WITH Clauses + +As in standard SQL, `WITH` clauses are available to improve the +modularity of a query. The next query shows an example. + +[[example-34]] +Example + +--------------------------------------------------- +WITH avgFriendCount AS ( + SELECT VALUE AVG(ARRAY_COUNT(user.friendIds)) + FROM GleambookUsers AS user +)[0] +SELECT VALUE user +FROM GleambookUsers user +WHERE ARRAY_COUNT(user.friendIds) > avgFriendCount; +--------------------------------------------------- + +This query returns: + +--------------------------------------------- +[ { + "userSince": "2012-08-20T10:10:00.000Z", + "friendIds": [ + 2, + 3, + 6, + 10 + ], + "gender": "F", + "name": "MargaritaStoddard", + "nickname": "Mags", + "alias": "Margarita", + "id": 1, + "employment": [ + { + "organizationName": "Codetechno", + "start-date": "2006-08-06" + }, + { + "end-date": "2010-01-26", + "organizationName": "geomedia", + "start-date": "2010-06-17" + } + ] +}, { + "userSince": "2012-07-10T10:10:00.000Z", + "friendIds": [ + 1, + 5, + 8, + 9 + ], + "name": "EmoryUnk", + "alias": "Emory", + "id": 3, + "employment": [ + { + "organizationName": "geomedia", + "endDate": "2010-01-26", + "startDate": "2010-06-17" + } + ] +} ] +--------------------------------------------- + +The query is equivalent to the following, more complex, inlined form of +the query: + +--------------------------------------------------- +SELECT * +FROM GleambookUsers user +WHERE ARRAY_COUNT(user.friendIds) > + ( SELECT VALUE AVG(ARRAY_COUNT(user.friendIds)) + FROM GleambookUsers AS user + ) [0]; +--------------------------------------------------- + +WITH can be particularly useful when a value needs to be used several +times in a query. + +Before proceeding further, notice that both the WITH query and its +equivalent inlined variant include the syntax "[0]" -- this is due to a +noteworthy difference between the query language and SQL-92. In SQL-92, +whenever a scalar value is expected and it is being produced by a query +expression, the SQL-92 query processor will evaluate the expression, +check that there is only one row and column in the result at runtime, +and then coerce the one-row/one-column tabular result into a scalar +value. A JSON query language, being designed to deal with nested data +and schema-less data, should not do this. Collection-valued data is +perfectly legal in most contexts, and its data is schema-less, so the +query processor rarely knows exactly what to expect where and such +automatic conversion would often not be desirable. Thus, in the queries +above, the use of "[0]" extracts the first (i.e., 0th) element of an +array-valued query expression's result; this is needed above, even +though the result is an array of one element, to extract the only +element in the singleton array and obtain the desired scalar for the +comparison. + +[[let-clauses]] +=== LET Clauses + +Similar to `WITH` clauses, `LET` clauses can be useful when a (complex) +expression is used several times within a query, allowing it to be +written once to make the query more concise. The next query shows an +example. + +[[example-35]] +Example + +-------------------------------------------- +SELECT u.name AS uname, messages AS messages +FROM GleambookUsers u +LET messages = (SELECT VALUE m + FROM GleambookMessages m + WHERE m.authorId = u.id) +WHERE EXISTS messages; +-------------------------------------------- + +This query lists `GleambookUsers` that have posted `GleambookMessages` +and shows all authored messages for each listed user. It returns: + +---------------------------------------------------------------------------- +[ { + "uname": "MargaritaStoddard", + "messages": [ + { + "senderLocation": [ + 38.97, + 77.49 + ], + "inResponseTo": 1, + "messageId": 11, + "authorId": 1, + "message": " can't stand acast its plan is terrible" + }, + { + "senderLocation": [ + 41.66, + 80.87 + ], + "inResponseTo": 4, + "messageId": 2, + "authorId": 1, + "message": " dislike x-phone its touch-screen is horrible" + }, + { + "senderLocation": [ + 37.73, + 97.04 + ], + "inResponseTo": 2, + "messageId": 4, + "authorId": 1, + "message": " can't stand acast the network is horrible:(" + }, + { + "senderLocation": [ + 40.33, + 80.87 + ], + "inResponseTo": 11, + "messageId": 8, + "authorId": 1, + "message": " like ccast the 3G is awesome:)" + }, + { + "senderLocation": [ + 42.5, + 70.01 + ], + "inResponseTo": 12, + "messageId": 10, + "authorId": 1, + "message": " can't stand product-w the touch-screen is terrible" + } + ] +}, { + "uname": "IsbelDull", + "messages": [ + { + "senderLocation": [ + 31.5, + 75.56 + ], + "inResponseTo": 1, + "messageId": 6, + "authorId": 2, + "message": " like product-z its platform is mind-blowing" + }, + { + "senderLocation": [ + 48.09, + 81.01 + ], + "inResponseTo": 4, + "messageId": 3, + "authorId": 2, + "message": " like product-y the plan is amazing" + } + ] +} ] +---------------------------------------------------------------------------- + +This query is equivalent to the following query that does not use the +`LET` clause: + +-------------------------------------------------- +SELECT u.name AS uname, ( SELECT VALUE m + FROM GleambookMessages m + WHERE m.authorId = u.id + ) AS messages +FROM GleambookUsers u +WHERE EXISTS ( SELECT VALUE m + FROM GleambookMessages m + WHERE m.authorId = u.id + ); +-------------------------------------------------- + +[[union-all]] +=== UNION ALL + +UNION ALL can be used to combine two input arrays or multisets into one. +As in SQL, there is no ordering guarantee on the contents of the output +stream. However, unlike SQL, the query language does not constrain what +the data looks like on the input streams; in particular, it allows +heterogeneity on the input and output streams. A type error will be +raised if one of the inputs is not a collection. The following odd but +legal query is an example: + +[[example-36]] +Example + +------------------------ +SELECT u.name AS uname +FROM GleambookUsers u +WHERE u.id = 2 + UNION ALL +SELECT VALUE m.message +FROM GleambookMessages m +WHERE authorId=2; +------------------------ + +This query returns: + +------------------------------------------------ +[ + " like product-z its platform is mind-blowing" + , { + "uname": "IsbelDull" +}, " like product-y the plan is amazing" + ] +------------------------------------------------ + +[[over-clauses]] +=== OVER Clauses + +All window functions must have an OVER clause to define the window +partitions, the order of tuples within those partitions, and the extent +of the window frame. Some window functions take additional window +options, which are specified by modifiers before the OVER clause. + +The query language has a dedicated set of window functions. Aggregate +functions can also be used as window functions, when they are used with +an OVER clause. + +[[window-function-call]] +==== Window Function Call + +------------------------------------------------------------------------- +WindowFunctionCall ::= WindowFunctionType "(" WindowFunctionArguments ")" +(WindowFunctionOptions)? (Variable )? "(" WindowDefinition ")" +------------------------------------------------------------------------- + +[[window-function-type]] +===== Window Function Type + +--------------------------------------------------------- +WindowFunctionType ::= AggregateFunction | WindowFunction +--------------------------------------------------------- + +Refer to the {aggregate-functions}[Aggregate Functions] +section for a list of aggregate functions. + +Refer to the {window-functions}[Window Functions] +section for a list of window functions. + +[[window-function-arguments]] +===== Window Function Arguments + +-------------------------------------------------------- +WindowFunctionArguments ::= ( ()? Expression | +(Expression ("," Expression ("," Expression)? )? )? ) +-------------------------------------------------------- + +Refer to the {aggregate-functions}[Aggregate Functions] +section or the {window-functions}[Window Functions] +section for details of the arguments for individual functions. + +[[window-function-options]] +==== Window Function Options + +--------------------------------------------------------- +WindowFunctionOptions ::= (NthValFrom)? (NullsTreatment)? +--------------------------------------------------------- + +Window function options cannot be used with +{aggregate-functions}[aggregate functions]. + +Window function options can only be used with some +{window-functions}[window functions], as described +below. + +[[nth-val-from]] +===== Nth Val From + +------------------------------------------ +NthValFrom ::= ( | ) +------------------------------------------ + +The *nth val from* modifier determines whether the computation begins at +the first or last tuple in the window. + +This modifier can only be used with the `nth_value()` function. + +This modifier is optional. If omitted, the default setting is +`FROM FIRST`. + +[[nulls-treatment]] +===== Nulls Treatment + +--------------------------------------------------- +NullsTreatment ::= ( | ) +--------------------------------------------------- + +The *nulls treatment* modifier determines whether NULL values are +included in the computation, or ignored. MISSING values are treated the +same way as NULL values. + +This modifier can only be used with the `first_value()`, `last_value()`, +`nth_value()`, `lag()`, and `lead()` functions. + +This modifier is optional. If omitted, the default setting is +`RESPECT NULLS`. + +[[window-frame-variable]] +==== Window Frame Variable + +The AS keyword enables you to specify an alias for the window frame +contents. It introduces a variable which will be bound to the contents +of the frame. When using a built-in +{aggregate-functions}[aggregate function] as a window +function, the function’s argument must be a subquery which refers to +this alias, for example: + +---------------------------------------------------------------------- +SELECT ARRAY_COUNT(DISTINCT (FROM alias SELECT VALUE alias.src.field)) +OVER alias AS (PARTITION BY … ORDER BY …) +FROM source AS src +---------------------------------------------------------------------- + +The alias is not necessary when using a +{window-functions}[window function], or when using a +standard SQL aggregate function with the OVER clause. + +[[standard-sql-aggregate-functions-with-the-over-clause]] +===== Standard SQL Aggregate Functions with the OVER Clause + +A standard SQL aggregate function with an OVER clause is rewritten by +the query compiler using a built-in aggregate function over a frame +variable. For example, the following query with the `sum()` function: + +-------------------------------------------------- +SELECT SUM(field) OVER (PARTITION BY … ORDER BY …) +FROM source AS src +-------------------------------------------------- + +Is rewritten as the following query using the `array_sum()` function: + +------------------------------------------------------------- +SELECT ARRAY_SUM( (SELECT VALUE alias.src.field FROM alias) ) + OVER alias AS (PARTITION BY … ORDER BY …) +FROM source AS src +------------------------------------------------------------- + +This is similar to the way that standard SQL aggregate functions are +rewritten as built-in aggregate functions in the presence of the GROUP +BY clause. + +[[window-definition]] +==== Window Definition + +---------------------------------------------------------------- +WindowDefinition ::= (WindowPartitionClause)? (WindowOrderClause +(WindowFrameClause (WindowFrameExclusion)? )? )? +---------------------------------------------------------------- + +The *window definition* specifies the partitioning, ordering, and +framing for window functions. + +[[window-partition-clause]] +===== Window Partition Clause + +----------------------------------------------------------------------- +WindowPartitionClause ::= Expression ("," Expression)* +----------------------------------------------------------------------- + +The *window partition clause* divides the tuples into logical partitions +using one or more expressions. + +This clause may be used with any +{window-functions}[window function], or any +{aggregate-functions}[aggregate function] used as a +window function. + +This clause is optional. If omitted, all tuples are united in a single +partition. + +[[Window_order_clause]] +===== Window Order Clause + +------------------------------------------------------------------- +WindowOrderClause ::= OrderingTerm ("," OrderingTerm)* +------------------------------------------------------------------- + +The *window order clause* determines how tuples are ordered within each +partition. The window function works on tuples in the order specified by +this clause. + +This clause may be used with any +{window-functions}[window function], or any +{aggregate-functions}[aggregate function] used as a +window function. + +This clause is optional. If omitted, all tuples are considered peers, +i.e. their order is tied. When tuples in the window partition are tied, +each window function behaves differently. + +* The `row_number()` function returns a distinct number for each tuple. +If tuples are tied, the results may be unpredictable. +* The `rank()`, `dense_rank()`, `percent_rank()`, and `cume_dist()` +functions return the same result for each tuple. +* For other functions, if the <> is +defined by `ROWS`, the results may be unpredictable. If the window frame +is defined by `RANGE` or `GROUPS`, the results are same for each tuple. + +This clause may have multiple <>. To +reduce the number of ties, add additional <>. + +[[note]] +Note + +This clause does not guarantee the overall order of the query results. +To guarantee the order of the final results, use the query ORDER BY +clause. + +[[Ordering_term]] +===== Ordering Term + +----------------------------------------------- +OrderingTerm ::= Expression ( | )? +----------------------------------------------- + +The *ordering term* specifies an ordering expression and collation. + +This clause has the same syntax and semantics as the ordering term for +queries. Refer to the <> section +for details. + +[[Window_frame_clause]] +===== Window Frame Clause + +----------------------------------------------------------------------- +WindowFrameClause ::= ( | | ) WindowFrameExtent +----------------------------------------------------------------------- + +The *window frame clause* defines the window frame. + +This clause can be used with all +{aggregate-functions}[aggregate functions] and some +{window-functions}[window functions] — refer to the +descriptions of individual functions for more details. + +This clause is allowed only when the <> is present. + +This clause is optional. + +* If this clause is omitted and there is no +<>, the window frame is the +entire partition. +* If this clause is omitted but there is a +<>, the window frame becomes +all tuples in the partition preceding the current tuple and its peers — +the same as `RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW`. + +The window frame can be defined in the following ways: + +* `ROWS`: Counts the exact number of tuples within the frame. If window +ordering doesn’t result in unique ordering, the function may produce +unpredictable results. You can add a unique expression or more window +ordering expressions to produce unique ordering. +* `RANGE`: Looks for a value offset within the frame. The function +produces deterministic results. +* `GROUPS`: Counts all groups of tied rows within the frame. The +function produces deterministic results. + +[[note-1]] +Note + +If this clause uses `RANGE` with either `Expression PRECEDING` or +`Expression FOLLOWING`, the <> must have only a single ordering term. + +The ordering term expression must evaluate to a number. + +If these conditions are not met, the window frame will be empty, which +means the window function will return its default value: in most cases +this is NULL, except for `strict_count()` or `array_count()`, whose +default value is 0. + +This restriction does not apply when the window frame uses `ROWS` or +`GROUPS`. + +[[tip]] +Tip + +The `RANGE` window frame is commonly used to define window frames based +on date or time. + +If you want to use `RANGE` with either `Expression PRECEDING` or +`Expression FOLLOWING`, and you want to use an ordering expression based +on date or time, the expression in `Expression PRECEDING` or +`Expression FOLLOWING` must use a data type that can be added to the +ordering expression. + +[[window-frame-extent]] +===== Window Frame Extent + +------------------------------------------------------------------------------------------ +WindowFrameExtent ::= ( ( | Expression ) | ) | + + ( | | Expression ( | ) ) + + ( | | Expression ( | ) ) +------------------------------------------------------------------------------------------ + +The *window frame extent clause* specifies the start point and end point +of the window frame. The expression before `AND` is the start point and +the expression after `AND` is the end point. If `BETWEEN` is omitted, +you can only specify the start point; the end point becomes +`CURRENT ROW`. + +The window frame end point can’t be before the start point. If this +clause violates this restriction explicitly, an error will result. If it +violates this restriction implicitly, the window frame will be empty, +which means the window function will return its default value: in most +cases this is NULL, except for `strict_count()` or `array_count()`, +whose default value is 0. + +Window frame extents that result in an explicit violation are: + +* `BETWEEN CURRENT ROW AND Expression PRECEDING` +* `BETWEEN Expression FOLLOWING AND Expression PRECEDING` +* `BETWEEN Expression FOLLOWING AND CURRENT ROW` + +Window frame extents that result in an implicit violation are: + +* `BETWEEN UNBOUNDED PRECEDING AND Expression PRECEDING` — if +`Expression` is too high, some tuples may generate an empty window +frame. +* `BETWEEN Expression PRECEDING AND Expression PRECEDING` — if the +second `Expression` is greater than or equal to the first `Expression`, +all result sets will generate an empty window frame. +* `BETWEEN Expression FOLLOWING AND Expression FOLLOWING` — if the first +`Expression` is greater than or equal to the second `Expression`, all +result sets will generate an empty window frame. +* `BETWEEN Expression FOLLOWING AND UNBOUNDED FOLLOWING` — if +`Expression` is too high, some tuples may generate an empty window +frame. +* If the <> is +present, any window frame specification may result in empty window +frame. + +The `Expression` must be a positive constant or an expression that +evaluates as a positive number. For `ROWS` or `GROUPS`, the `Expression` +must be an integer. + +[[Window_frame_exclusion]] +===== Window Frame Exclusion + +------------------------------------------------------------------------- +WindowFrameExclusion ::= ( | | | + ) +------------------------------------------------------------------------- + +The *window frame exclusion clause* enables you to exclude specified +tuples from the window frame. + +This clause can be used with all +{aggregate-functions}[aggregate functions] and some +{window-functions}[window functions] — refer to the +descriptions of individual functions for more details. + +This clause is allowed only when the <> is present. + +This clause is optional. If this clause is omitted, the default is no +exclusion — the same as `EXCLUDE NO OTHERS`. + +* `EXCLUDE CURRENT ROW`: If the current tuple is still part of the +window frame, it is removed from the window frame. +* `EXCLUDE GROUP`: The current tuple and any peers of the current tuple +are removed from the window frame. +* `EXCLUDE TIES`: Any peers of the current tuple, but not the current +tuple itself, are removed from the window frame. +* `EXCLUDE NO OTHERS`: No additional tuples are removed from the window +frame. + +If the current tuple is already removed from the window frame, then it +remains removed from the window frame. + +[[subqueries]] +=== Subqueries + +In the query language, an arbitrary subquery can appear anywhere that an +expression can appear. Unlike SQL-92, as was just alluded to, the +subqueries in a SELECT list or a boolean predicate need not return +singleton, single-column relations. Instead, they may return arbitrary +collections. For example, the following query is a variant of the prior +group-by query examples; it retrieves an array of up to two "dislike" +messages per user. + +[[example-37]] +Example + +--------------------------------------------------------------- +SELECT uid, + (SELECT VALUE m.msg + FROM msgs m + WHERE m.msg.message LIKE '%dislike%' + ORDER BY m.msg.messageId + LIMIT 2) AS msgs +FROM GleambookMessages message +GROUP BY message.authorId AS uid GROUP AS msgs(message AS msg); +--------------------------------------------------------------- + +For our sample data set, this query returns: + +---------------------------------------------------------------------- +[ { + "msgs": [ + { + "senderLocation": [ + 41.66, + 80.87 + ], + "inResponseTo": 4, + "messageId": 2, + "authorId": 1, + "message": " dislike x-phone its touch-screen is horrible" + } + ], + "uid": 1 +}, { + "msgs": [ + + ], + "uid": 2 +} ] +---------------------------------------------------------------------- + +Note that a subquery, like a top-level `SELECT` statment, always returns +a collection -- regardless of where within a query the subquery occurs +-- and again, its result is never automatically cast into a scalar. + +[[differences-from-sql-92]] +=== Differences from SQL-92 + +The query language offers the following additional features beyond +SQL-92: + +* Fully composable and functional: A subquery can iterate over any +intermediate collection and can appear anywhere in a query. +* Schema-free: The query language does not assume the existence of a +static schema for any data that it processes. +* Correlated FROM terms: A right-side FROM term expression can refer to +variables defined by FROM terms on its left. +* Powerful GROUP BY: In addition to a set of aggregate functions as in +standard SQL, the groups created by the `GROUP BY` clause are directly +usable in nested queries and/or to obtain nested results. +* Generalized SELECT clause: A SELECT clause can return any type of +collection, while in SQL-92, a `SELECT` clause has to return a +(homogeneous) collection of objects. + +The following matrix is a quick "SQL-92 compatibility cheat sheet" for +the query language. + +[cols=",,,",options="header",] +|======================================================================= +|Feature |The query language |SQL-92 |Why different? +|SELECT * |Returns nested objects |Returns flattened concatenated +objects |Nested collections are 1st class citizens + +|SELECT list |order not preserved |order preserved |Fields in a JSON +object are not ordered + +|Subquery |Returns a collection |The returned collection is cast into a +scalar value if the subquery appears in a SELECT list or on one side of +a comparison or as input to a function |Nested collections are 1st class +citizens + +|LEFT OUTER JOIN |Fills in `MISSING`(s) for non-matches |Fills in +`NULL`(s) for non-matches |"Absence" is more appropriate than "unknown" +here + +|UNION ALL |Allows heterogeneous inputs and output |Input streams must +be UNION-compatible and output field names are drawn from the first +input stream |Heterogenity and nested collections are common + +|IN constant_expr |The constant expression has to be an array or +multiset, i.e., [..,..,...] |The constant collection can be represented +as comma-separated items in a paren pair |Nested collections are 1st +class citizens + +|String literal |Double quotes or single quotes |Single quotes only +|Double quoted strings are pervasive + +|Delimited identifiers |Backticks |Double quotes |Double quoted strings +are pervasive +|======================================================================= + +The following SQL-92 features are not implemented yet. However, the +query language does not conflict with these features: + +* CROSS JOIN, NATURAL JOIN, UNION JOIN +* RIGHT and FULL OUTER JOIN +* INTERSECT, EXCEPT, UNION with set semantics +* CAST expression +* COALESCE expression +* ALL and SOME predicates for linking to subqueries +* UNIQUE predicate (tests a collection for duplicates) +* MATCH predicate (tests for referential integrity) +* Row and Table constructors +* Preserved order for expressions in a SELECT list + diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/3_query_title.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/3_query_title.adoc new file mode 100644 index 00000000000..bc3d1551736 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/3_query_title.adoc @@ -0,0 +1,10 @@ +[[queries]] +== 3. Queries + +A query can be any legal expression or `SELECT` statement. A query +always ends with a semicolon. + +-------------------------------------------- +Query ::= (Expression | SelectStatement) ";" +-------------------------------------------- + diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/4_error.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/4_error.adoc new file mode 100644 index 00000000000..103175a69e4 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/4_error.adoc @@ -0,0 +1,127 @@ +A query can potentially result in one of the following errors: + +* syntax error, +* identifier resolution error, +* type error, +* resource error. + +If the query processor runs into any error, it will terminate the +ongoing processing of the query and immediately return an error message +to the client. + +[[syntax-errors]] +=== Syntax Errors + +A valid query must satisfy the grammar rules of the query language. +Otherwise, a syntax error will be raised. + +[[example]] +Example + +------------------- +SELECT * +GleambookUsers user +------------------- + +Since the query misses a `FROM` keyword before the dataset +`GleambookUsers`, we will get a syntax error as follows: + +--------------------------------------------------------------------------------------------------------- +Syntax error: In line 2 >>GleambookUsers user;<< Encountered \"GleambookUsers\" at column 1. +--------------------------------------------------------------------------------------------------------- + +[[example-1]] +Example + +------------------------ +SELECT * +FROM GleambookUsers user +WHERE type="advertiser"; +------------------------ + +Since "type" is a reserved keyword in the query parser, we will get a +syntax error as follows: + +-------------------------------------------------------------------------------------------------- +Error: Syntax error: In line 3 >>WHERE type="advertiser";<< Encountered 'type' "type" at column 7. +==> WHERE type="advertiser"; +-------------------------------------------------------------------------------------------------- + +[[identifier-resolution-errors]] +=== Identifier Resolution Errors + +Referring to an undefined identifier can cause an error if the +identifier cannot be successfully resolved as a valid field access. + +[[example-2]] +Example + +------------------------ +SELECT * +FROM GleambookUser user; +------------------------ + +If we have a typo as above in "GleambookUsers" that misses the dataset +name's ending "s", we will get an identifier resolution error as +follows: + +--------------------------------------------------------------------------------------------------- +Error: Cannot find dataset GleambookUser in dataverse Default nor an alias with name GleambookUser! +--------------------------------------------------------------------------------------------------- + +[[example-3]] +Example + +-------------------------------------------------------------------- +SELECT name, message +FROM GleambookUsers u JOIN GleambookMessages m ON m.authorId = u.id; +-------------------------------------------------------------------- + +If the compiler cannot figure out how to resolve an unqualified field +name, which will occur if there is more than one variable in scope +(e.g., `GleambookUsers u` and `GleambookMessages m` as above), we will +get an identifier resolution error as follows: + +----------------------------------------------------------------------------- +Error: Cannot resolve ambiguous alias reference for undefined identifier name +----------------------------------------------------------------------------- + +[[type-errors]] +=== Type Errors + +The query compiler does type checks based on its available type +information. In addition, the query runtime also reports type errors if +a data model instance it processes does not satisfy the type +requirement. + +[[example-4]] +Example + +----------- +abs("123"); +----------- + +Since function `abs` can only process numeric input values, we will get +a type error as follows: + +------------------------------------------------------------------------------------------------------------------------------------------------------------------------- +Error: Type mismatch: function abs expects its 1st input parameter to be of type tinyint, smallint, integer, bigint, float or double, but the actual input type is string +------------------------------------------------------------------------------------------------------------------------------------------------------------------------- + +[[resource-errors]] +=== Resource Errors + +A query can potentially exhaust system resources, such as the number of +open files and disk spaces. For instance, the following two resource +errors could be potentially be seen when running the system: + +------------------------------ +Error: no space left on device +Error: too many open files +------------------------------ + +The "no space left on device" issue usually can be fixed by cleaning up +disk spaces and reserving more disk spaces for the system. The "too many +open files" issue usually can be fixed by a system administrator, +following the instructions +https://easyengine.io/tutorials/linux/increase-open-files-limit/[here]. diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/4_error_title.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/4_error_title.adoc new file mode 100644 index 00000000000..6a44d815138 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/4_error_title.adoc @@ -0,0 +1,2 @@ +[[errors]] +== 4. Errors diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_dataset_index.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_dataset_index.adoc new file mode 100644 index 00000000000..77ba3496f2f --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_dataset_index.adoc @@ -0,0 +1,405 @@ +[[lifecycle-management-statements]] +=== Lifecycle Management Statements + +--------------------------------------------------------------------- +CreateStatement ::= "CREATE" ( DatabaseSpecification + | TypeSpecification + | DatasetSpecification + | IndexSpecification + | SynonymSpecification + | FunctionSpecification ) + +QualifiedName ::= Identifier ( "." Identifier )? +DoubleQualifiedName ::= Identifier "." Identifier ( "." Identifier )? +--------------------------------------------------------------------- + +The CREATE statement is used for creating dataverses as well as other +persistent artifacts in a dataverse. It can be used to create new +dataverses, datatypes, datasets, indexes, and user-defined query +functions. + +[[dataverses]] +==== Dataverses + +------------------------------------------------------------ +DatabaseSpecification ::= "DATAVERSE" Identifier IfNotExists +------------------------------------------------------------ + +The CREATE DATAVERSE statement is used to create new dataverses. To ease +the authoring of reusable query scripts, an optional IF NOT EXISTS +clause is included to allow creation to be requested either +unconditionally or only if the dataverse does not already exist. If this +clause is absent, an error is returned if a dataverse with the indicated +name already exists. + +The following example creates a new dataverse named TinySocial if one +does not already exist. + +[[example]] +Example + +------------------------------------------ +CREATE DATAVERSE TinySocial IF NOT EXISTS; +------------------------------------------ + +[[types]] +==== Types + +--------------------------------------------------------------------------------------------- +TypeSpecification ::= "TYPE" FunctionOrTypeName IfNotExists "AS" ObjectTypeDef +FunctionOrTypeName ::= QualifiedName +IfNotExists ::= ( )? +TypeExpr ::= ObjectTypeDef | TypeReference | ArrayTypeDef | MultisetTypeDef +ObjectTypeDef ::= ( | )? "{" ( ObjectField ( "," ObjectField )* )? "}" +ObjectField ::= Identifier ":" ( TypeExpr ) ( "?" )? +NestedField ::= Identifier ( "." Identifier )* +IndexField ::= NestedField ( ":" TypeReference )? +TypeReference ::= Identifier +ArrayTypeDef ::= "[" ( TypeExpr ) "]" +MultisetTypeDef ::= "{{" ( TypeExpr ) "}}" +--------------------------------------------------------------------------------------------- + +The CREATE TYPE statement is used to create a new named datatype. This +type can then be used to create stored collections or utilized when +defining one or more other datatypes. Much more information about the +data model is available in the link:../datamodel.html[data model +reference guide]. A new type can be a object type, a renaming of another +type, an array type, or a multiset type. A object type can be defined as +being either open or closed. Instances of a closed object type are not +permitted to contain fields other than those specified in the create +type statement. Instances of an open object type may carry additional +fields, and open is the default for new types if neither option is +specified. + +The following example creates a new object type called GleambookUser +type. Since it is defined as (defaulting to) being an open type, +instances will be permitted to contain more than what is specified in +the type definition. The first four fields are essentially traditional +typed name/value pairs (much like SQL fields). The friendIds field is a +multiset of integers. The employment field is an array of instances of +another named object type, EmploymentType. + +[[example-1]] +Example + +---------------------------------- +CREATE TYPE GleambookUserType AS { + id: int, + alias: string, + name: string, + userSince: datetime, + friendIds: {{ int }}, + employment: [ EmploymentType ] +}; +---------------------------------- + +The next example creates a new object type, closed this time, called +MyUserTupleType. Instances of this closed type will not be permitted to +have extra fields, although the alias field is marked as optional and +may thus be NULL or MISSING in legal instances of the type. Note that +the type of the id field in the example is UUID. This field type can be +used if you want to have this field be an autogenerated-PK field. (Refer +to the Datasets section later for more details on such fields.) + +[[example-2]] +Example + +--------------------------------------- +CREATE TYPE MyUserTupleType AS CLOSED { + id: uuid, + alias: string?, + name: string +}; +--------------------------------------- + +[[datasets]] +==== Datasets + +------------------------------------------------------------------------------------------------------------------- +DatasetSpecification ::= ( )? QualifiedName "(" QualifiedName ")" IfNotExists + PrimaryKey ( Identifier )? ( Properties )? + ( "USING" "COMPACTION" "POLICY" CompactionPolicy ( Configuration )? )? + ( Identifier )? + | + QualifiedName "(" QualifiedName ")" IfNotExists AdapterName + Configuration ( Properties )? + ( CompactionPolicy ( Configuration )? )? +AdapterName ::= Identifier +Configuration ::= "(" ( KeyValuePair ( "," KeyValuePair )* )? ")" +KeyValuePair ::= "(" StringLiteral "=" StringLiteral ")" +Properties ::= ( "(" Property ( "," Property )* ")" )? +Property ::= Identifier "=" ( StringLiteral | IntegerLiteral ) +FunctionSignature ::= FunctionOrTypeName "@" IntegerLiteral +PrimaryKey ::= NestedField ( "," NestedField )* ( )? +CompactionPolicy ::= Identifier +------------------------------------------------------------------------------------------------------------------- + +The CREATE DATASET statement is used to create a new dataset. Datasets +are named, multisets of object type instances; they are where data lives +persistently and are the usual targets for queries. Datasets are typed, +and the system ensures that their contents conform to their type +definitions. An Internal dataset (the default kind) is a dataset whose +content lives within and is managed by the system. It is required to +have a specified unique primary key field which uniquely identifies the +contained objects. (The primary key is also used in secondary indexes to +identify the indexed primary data objects.) + +Internal datasets contain several advanced options that can be specified +when appropriate. One such option is that random primary key (UUID) +values can be auto-generated by declaring the field to be UUID and +putting "AUTOGENERATED" after the "PRIMARY KEY" identifier. In this +case, unlike other non-optional fields, a value for the auto-generated +PK field should not be provided at insertion time by the user since each +object's primary key field value will be auto-generated by the system. + +Another advanced option, when creating an Internal dataset, is to +specify the merge policy to control which of the underlying LSM storage +components to be merged. (The system supports Log-Structured Merge tree +based physical storage for Internal datasets.) Currently the system +supports four different component merging policies that can be chosen +per dataset: no-merge, constant, prefix, and correlated-prefix. The +no-merge policy simply never merges disk components. The constant policy +merges disk components when the number of components reaches a constant +number k that can be configured by the user. The prefix policy relies on +both component sizes and the number of components to decide which +components to merge. It works by first trying to identify the smallest +ordered (oldest to newest) sequence of components such that the sequence +does not contain a single component that exceeds some threshold size M +and that either the sum of the component's sizes exceeds M or the number +of components in the sequence exceeds another threshold C. If such a +sequence exists, the components in the sequence are merged together to +form a single component. Finally, the correlated-prefix policy is +similar to the prefix policy, but it delegates the decision of merging +the disk components of all the indexes in a dataset to the primary +index. When the correlated-prefix policy decides that the primary index +needs to be merged (using the same decision criteria as for the prefix +policy), then it will issue successive merge requests on behalf of all +other indexes associated with the same dataset. The system's default +policy is the prefix policy except when there is a filter on a dataset, +where the preferred policy for filters is the correlated-prefix. + +Another advanced option shown in the syntax above, related to +performance and mentioned above, is that a *filter* can optionally be +created on a field to further optimize range queries with predicates on +the filter's field. Filters allow some range queries to avoid searching +all LSM components when the query conditions match the filter. (Refer to +link:../filters.html[Filter-Based LSM Index Acceleration] for more +information about filters.) + +An External dataset, in contrast to an Internal dataset, has data stored +outside of the system's control. Files living in HDFS or in the local +filesystem(s) of a cluster's nodes are currently supported. External +dataset support allows queries to treat foreign data as though it were +stored in the system, making it possible to query "legacy" file data +(for example, Hive data) without having to physically import it. When +defining an External dataset, an appropriate adapter type must be +selected for the desired external data. (See the +link:../externaldata.html[Guide to External Data] for more information +on the available adapters.) + +The following example creates an Internal dataset for storing +FacefookUserType objects. It specifies that their id field is their +primary key. + +[[example-3]] +===== Example + +------------------------------------------------------------------------- +CREATE INTERNAL DATASET GleambookUsers(GleambookUserType) PRIMARY KEY id; +------------------------------------------------------------------------- + +The next example creates another Internal dataset (the default kind when +no dataset kind is specified) for storing MyUserTupleType objects. It +specifies that the id field should be used as the primary key for the +dataset. It also specifies that the id field is an auto-generated field, +meaning that a randomly generated UUID value should be assigned to each +incoming object by the system. (A user should therefore not attempt to +provide a value for this field.) Note that the id field's declared type +must be UUID in this case. + +[[example-4]] +===== Example + +--------------------------------------------------------------------- +CREATE DATASET MyUsers(MyUserTupleType) PRIMARY KEY id AUTOGENERATED; +--------------------------------------------------------------------- + +The next example creates an External dataset for querying LineItemType +objects. The choice of the `hdfs` adapter means that this dataset's data +actually resides in HDFS. The example CREATE statement also provides +parameters used by the hdfs adapter: the URL and path needed to locate +the data in HDFS and a description of the data format. + +[[example-5]] +===== Example + +----------------------------------------------------------- +CREATE EXTERNAL DATASET LineItem(LineItemType) USING hdfs ( + ("hdfs"="hdfs://HOST:PORT"), + ("path"="HDFS_PATH"), + ("input-format"="text-input-format"), + ("format"="delimited-text"), + ("delimiter"="|")); +----------------------------------------------------------- + +[[indices]] +==== Indices + +----------------------------------------------------------------------------------------------------- +IndexSpecification ::= ( Identifier IfNotExists QualifiedName + "(" ( IndexField ) ( "," IndexField )* ")" ( IndexType)? ()?) + | + Identifier? IfNotExists QualifiedName ( )? +IndexType ::= | | | "(" IntegerLiteral ")" +----------------------------------------------------------------------------------------------------- + +The CREATE INDEX statement creates a secondary index on one or more +fields of a specified dataset. Supported index types include `BTREE` for +totally ordered datatypes, `RTREE` for spatial data, and `KEYWORD` and +`NGRAM` for textual (string) data. An index can be created on a nested +field (or fields) by providing a valid path expression as an index field +identifier. + +An indexed field is not required to be part of the datatype associated +with a dataset if the dataset's datatype is declared as open *and* if +the field's type is provided along with its name and if the `ENFORCED` +keyword is specified at the end of the index definition. `ENFORCING` an +open field introduces a check that makes sure that the actual type of +the indexed field (if the optional field exists in the object) always +matches this specified (open) field type. + +The following example creates a btree index called gbAuthorIdx on the +authorId field of the GleambookMessages dataset. This index can be +useful for accelerating exact-match queries, range search queries, and +joins involving the author-id field. + +[[example-6]] +===== Example + +------------------------------------------------------------------- +CREATE INDEX gbAuthorIdx ON GleambookMessages(authorId) TYPE BTREE; +------------------------------------------------------------------- + +The following example creates an open btree index called gbSendTimeIdx +on the (non-declared) `sendTime` field of the GleambookMessages dataset +having datetime type. This index can be useful for accelerating +exact-match queries, range search queries, and joins involving the +`sendTime` field. The index is enforced so that records that do not have +the `sendTime` field or have a mismatched type on the field cannot be +inserted into the dataset. + +[[example-7]] +===== Example + +----------------------------------------------------------------------------------------- +CREATE INDEX gbSendTimeIdx ON GleambookMessages(sendTime: datetime?) TYPE BTREE ENFORCED; +----------------------------------------------------------------------------------------- + +The following example creates an open btree index called gbReadTimeIdx +on the (non-declared) `readTime` field of the GleambookMessages dataset +having datetime type. This index can be useful for accelerating +exact-match queries, range search queries, and joins involving the +`readTime` field. The index is not enforced so that records that do not +have the `readTime` field or have a mismatched type on the field can +still be inserted into the dataset. + +[[example-8]] +===== Example + +--------------------------------------------------------------------- +CREATE INDEX gbReadTimeIdx ON GleambookMessages(readTime: datetime?); +--------------------------------------------------------------------- + +The following example creates a btree index called crpUserScrNameIdx on +screenName, a nested field residing within a object-valued user field in +the ChirpMessages dataset. This index can be useful for accelerating +exact-match queries, range search queries, and joins involving the +nested screenName field. Such nested fields must be singular, i.e., one +cannot index through (or on) an array-valued field. + +[[example-9]] +===== Example + +---------------------------------------------------------------------------- +CREATE INDEX crpUserScrNameIdx ON ChirpMessages(user.screenName) TYPE BTREE; +---------------------------------------------------------------------------- + +The following example creates an rtree index called gbSenderLocIdx on +the sender-location field of the GleambookMessages dataset. This index +can be useful for accelerating queries that use the +link:functions.html#spatial-intersect[`spatial-intersect` function] in a +predicate involving the sender-location field. + +[[example-10]] +===== Example + +--------------------------------------------------------------------------------- +CREATE INDEX gbSenderLocIndex ON GleambookMessages("sender-location") TYPE RTREE; +--------------------------------------------------------------------------------- + +The following example creates a 3-gram index called fbUserIdx on the +name field of the GleambookUsers dataset. This index can be used to +accelerate some similarity or substring maching queries on the name +field. For details refer to the document on +link:similarity.html#NGram_Index[similarity queries]. + +[[example-11]] +===== Example + +------------------------------------------------------------- +CREATE INDEX fbUserIdx ON GleambookUsers(name) TYPE NGRAM(3); +------------------------------------------------------------- + +The following example creates a keyword index called fbMessageIdx on the +message field of the GleambookMessages dataset. This keyword index can +be used to optimize queries with token-based similarity predicates on +the message field. For details refer to the document on +link:similarity.html#Keyword_Index[similarity queries]. + +[[example-12]] +===== Example + +--------------------------------------------------------------------- +CREATE INDEX fbMessageIdx ON GleambookMessages(message) TYPE KEYWORD; +--------------------------------------------------------------------- + +The following example creates a special secondary index which holds only +the primary keys. This index is useful for speeding up aggregation +queries which involve only primary keys. The name of the index is +optional. If the name is not specified, the system will generate one. +When the user would like to drop this index, the metadata can be queried +to find the system-generated name. + +[[example-13]] +===== Example + +---------------------------------------------------- +CREATE PRIMARY INDEX gb_pk_idx ON GleambookMessages; +---------------------------------------------------- + +An example query that can be accelerated using the primary-key index: + +--------------------------------------- +SELECT COUNT(*) FROM GleambookMessages; +--------------------------------------- + +To look up the the above primary-key index, issue the following query: + +----------------------------------------------------------------------------- +SELECT VALUE i +FROM Metadata.`Index` i +WHERE i.DataverseName = "TinySocial" AND i.DatasetName = "GleambookMessages"; +----------------------------------------------------------------------------- + +The query returns: + +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ +[ { "DataverseName": "TinySocial", "DatasetName": "GleambookMessages", "IndexName": "GleambookMessages", "IndexStructure": "BTREE", "SearchKey": [ [ "messageId" ] ], "IsPrimary": true, "Timestamp": "Wed Nov 07 17:25:11 PST 2018", "PendingOp": 0 } +, { "DataverseName": "TinySocial", "DatasetName": "GleambookMessages", "IndexName": "gb_pk_idx", "IndexStructure": "BTREE", "SearchKey": [ ], "IsPrimary": false, "Timestamp": "Wed Nov 07 17:25:11 PST 2018", "PendingOp": 0 } + ] +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ + +Remember that `CREATE PRIMARY INDEX` creates a secondary index. That is +the reason the `IsPrimary` field is false. The primary-key index can be +identified by the fact that the `SearchKey` field is empty since it only +contains primary key fields. diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_dml.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_dml.adoc new file mode 100644 index 00000000000..6a096f5f340 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_dml.adoc @@ -0,0 +1,115 @@ +[[modification-statements]] +=== Modification statements + +[[inserts]] +==== INSERTs + +------------------------------------------------------- +InsertStatement ::= QualifiedName Query +------------------------------------------------------- + +The INSERT statement is used to insert new data into a dataset. The data +to be inserted comes from a query expression. This expression can be as +simple as a constant expression, or in general it can be any legal +query. In case the dataset has an auto-generated primary key, when +performing an INSERT operation, the system allows the user to manually +add the auto-generated key field in the INSERT statement, or skip that +field and the system will automatically generate it and add it. However, +it is important to note that if the a record already exists in the +dataset with the auto-generated key provided by the user, then that +operation is going to fail. As a general rule, insertion will fail if +the dataset already has data with the primary key value(s) being +inserted. + +Inserts are processed transactionally by the system. The transactional +scope of each insert transaction is the insertion of a single object +plus its affiliated secondary index entries (if any). If the query part +of an insert returns a single object, then the INSERT statement will be +a single, atomic transaction. If the query part returns multiple +objects, each object being inserted will be treated as a separate +tranaction. + +The target dataset name may be a synonym introduced by CREATE SYNONYM +statement. + +The following example illustrates a query-based insertion. + +[[example]] +Example + +------------------------------------------------------------------ +INSERT INTO UsersCopy (SELECT VALUE user FROM GleambookUsers user) +------------------------------------------------------------------ + +[[upserts]] +==== UPSERTs + +------------------------------------------------------- +UpsertStatement ::= QualifiedName Query +------------------------------------------------------- + +The UPSERT statement syntactically mirrors the INSERT statement +discussed above. The difference lies in its semantics, which for UPSERT +are "add or replace" instead of the INSERT "add if not present, else +error" semantics. Whereas an INSERT can fail if another object already +exists with the specified key, the analogous UPSERT will replace the +previous object's value with that of the new object in such cases. Like +the INSERT statement, the system allows the user to manually provide the +auto-generated key for datasets with an auto-generated key as its +primary key. This operation will insert the record if no record with +that key already exists, but if a record with the key already exists, +then the operation will be converted to a replace/update operation. + +The target dataset name may be a synonym introduced by CREATE SYNONYM +statement. + +The following example illustrates a query-based upsert operation. + +[[example-1]] +Example + +------------------------------------------------------------------ +UPSERT INTO UsersCopy (SELECT VALUE user FROM GleambookUsers user) +------------------------------------------------------------------ + +*Editor's note: Upserts currently work in AQL but are not yet enabled +(at the moment) in the current query language. + +[[deletes]] +==== DELETEs + +------------------------------------------------------------------------------------------------- +DeleteStatement ::= QualifiedName ( ( )? Variable )? ( Expression )? +------------------------------------------------------------------------------------------------- + +The DELETE statement is used to delete data from a target dataset. The +data to be deleted is identified by a boolean expression involving the +variable bound to the target dataset in the DELETE statement. + +Deletes are processed transactionally by the system. The transactional +scope of each delete transaction is the deletion of a single object plus +its affiliated secondary index entries (if any). If the boolean +expression for a delete identifies a single object, then the DELETE +statement itself will be a single, atomic transaction. If the expression +identifies multiple objects, then each object deleted will be handled as +a separate transaction. + +The target dataset name may be a synonym introduced by CREATE SYNONYM +statement. + +The following examples illustrate single-object deletions. + +[[example-2]] +Example + +-------------------------------------------------- +DELETE FROM GleambookUsers user WHERE user.id = 8; +-------------------------------------------------- + +[[example-3]] +Example + +---------------------------------------- +DELETE FROM GleambookUsers WHERE id = 5; +---------------------------------------- + diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_function_removal.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_function_removal.adoc new file mode 100644 index 00000000000..d02c5156c6b --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_function_removal.adoc @@ -0,0 +1,132 @@ +[[functions]] +==== Functions + +The CREATE FUNCTION statement creates a *named* function that can then +be used and reused in queries. The body of a function can be any query +expression involving the function's parameters. + +---------------------------------------------------------------------------------------------------- +FunctionSpecification ::= "FUNCTION" FunctionOrTypeName IfNotExists ParameterList "{" Expression "}" +---------------------------------------------------------------------------------------------------- + +The following is an example of a CREATE FUNCTION statement which is +similar to our earlier DECLARE FUNCTION example. It differs from that +example in that it results in a function that is persistently registered +by name in the specified dataverse (the current dataverse being used, if +not otherwise specified). + +[[example]] +Example + +--------------------------------------------------------- +CREATE FUNCTION friendInfo(userId) { + (SELECT u.id, u.name, len(u.friendIds) AS friendCount + FROM GleambookUsers u + WHERE u.id = userId)[0] + }; +--------------------------------------------------------- + +[[synonyms]] +==== Synonyms + +-------------------------------------------------------------------------------- +SynonymSpecification ::= "SYNONYM" QualifiedName "FOR" QualifiedName IfNotExists +-------------------------------------------------------------------------------- + +The CREATE SYNONYM statement creates a synonym for a given dataset. This +synonym may be used used instead of the dataset name in SELECT, INSERT, +UPSERT, DELETE, and LOAD statements. The target dataset does not need to +exist when the synonym is created. + +[[example-1]] +Example + +---------------------------------------------------------------- +CREATE DATASET GleambookUsers(GleambookUserType) PRIMARY KEY id; + +CREATE SYNONYM GleambookUsersSynonym FOR GleambookUsers; + +SELECT * FROM GleambookUsersSynonym; +---------------------------------------------------------------- + +More information on how synonyms are resolved can be found in the +appendix section on Variable Resolution. + +[[removal]] +==== Removal + +------------------------------------------------------------------------ +DropStatement ::= "DROP" ( "DATAVERSE" Identifier IfExists + | "TYPE" FunctionOrTypeName IfExists + | "DATASET" QualifiedName IfExists + | "INDEX" DoubleQualifiedName IfExists + | "SYNONYM" QualifiedName IfExists + | "FUNCTION" FunctionSignature IfExists ) +IfExists ::= ( "IF" "EXISTS" )? +------------------------------------------------------------------------ + +The DROP statement is the inverse of the CREATE statement. It can be +used to drop dataverses, datatypes, datasets, indexes, functions, and +synonyms. + +The following examples illustrate some uses of the DROP statement. + +[[example-2]] +Example + +---------------------------------------------- +DROP DATASET GleambookUsers IF EXISTS; + +DROP INDEX GleambookMessages.gbSenderLocIndex; + +DROP TYPE TinySocial2.GleambookUserType; + +DROP FUNCTION friendInfo@1; + +DROP SYNONYM GleambookUsersSynonym; + +DROP DATAVERSE TinySocial; +---------------------------------------------- + +When an artifact is dropped, it will be droppped from the current +dataverse if none is specified (see the DROP DATASET example above) or +from the specified dataverse (see the DROP TYPE example above) if one is +specified by fully qualifying the artifact name in the DROP statement. +When specifying an index to drop, the index name must be qualified by +the dataset that it indexes. When specifying a function to drop, since +the query language allows functions to be overloaded by their number of +arguments, the identifying name of the function to be dropped must +explicitly include that information. (`friendInfo@1` above denotes the +1-argument function named friendInfo in the current dataverse.) + +[[load-statement]] +==== Load Statement + +----------------------------------------------------------------------------------------------------- +LoadStatement ::= QualifiedName AdapterName Configuration ( )? +----------------------------------------------------------------------------------------------------- + +The LOAD statement is used to initially populate a dataset via bulk +loading of data from an external file. An appropriate adapter must be +selected to handle the nature of the desired external data. The LOAD +statement accepts the same adapters and the same parameters as discussed +earlier for External datasets. (See the link:externaldata.html[guide to +external data] for more information on the available adapters.) If a +dataset has an auto-generated primary key field, the file to be imported +should not include that field in it. + +The target dataset name may be a synonym introduced by CREATE SYNONYM +statement. + +The following example shows how to bulk load the GleambookUsers dataset +from an external file containing data that has been prepared in ADM +(Asterix Data Model) format. + +[[example-3]] +Example + +--------------------------------------------------------------------------------------- + LOAD DATASET GleambookUsers USING localfs + (("path"="127.0.0.1:///Users/bignosqlfan/tinysocialnew/gbu.adm"),("format"="adm")); +--------------------------------------------------------------------------------------- + diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_head.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_head.adoc new file mode 100644 index 00000000000..c7853d51eef --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/5_ddl_head.adoc @@ -0,0 +1,21 @@ +[[ddl-and-dml-statements]] +== 5. DDL and DML statements + +------------------------------------------------------ +Statement ::= ( ( SingleStatement )? ( ";" )+ )* +SingleStatement ::= DatabaseDeclaration + | FunctionDeclaration + | CreateStatement + | DropStatement + | LoadStatement + | SetStatement + | InsertStatement + | DeleteStatement + | Query +------------------------------------------------------ + +In addition to queries, an implementation of the query language needs to +support statements for data definition and manipulation purposes as well +as controlling the context to be used in evaluating query expressions. +This section details the DDL and DML statements supported in the query +language as realized today in Apache AsterixDB. diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_1_keywords.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_1_keywords.adoc new file mode 100644 index 00000000000..079b0202892 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_1_keywords.adoc @@ -0,0 +1,23 @@ +All reserved keywords are listed in the following table: + +[cols=",,,,,",] +|=============================================================== +|AND |ANY |APPLY |AS |ASC |AT +|AUTOGENERATED |BETWEEN |BTREE |BY |CASE |CLOSED +|CREATE |COMPACTION |COMPACT |CONNECT |CORRELATE |DATASET +|COLLECTION |DATAVERSE |DECLARE |DEFINITION |DECLARE |DEFINITION +|DELETE |DESC |DISCONNECT |DISTINCT |DROP |ELEMENT +|ELEMENT |EXPLAIN |ELSE |ENFORCED |END |EVERY +|EXCEPT |EXIST |EXTERNAL |FEED |FILTER |FLATTEN +|FOR |FROM |FULL |FUNCTION |GROUP |HAVING +|HINTS |IF |INTO |IN |INDEX |INGESTION +|INNER |INSERT |INTERNAL |INTERSECT |IS |JOIN +|KEYWORD |LEFT |LETTING |LET |LIKE |LIMIT +|LOAD |NODEGROUP |NGRAM |NOT |OFFSET |ON +|OPEN |OR |ORDER |OUTER |OUTPUT |OVER +|PATH |POLICY |PRE-SORTED |PRIMARY |RAW |REFRESH +|RETURN |RTREE |RUN |SATISFIES |SECONDARY |SELECT +|SET |SOME |TEMPORARY |THEN |TYPE |UNKNOWN +|UNNEST |UPDATE |USE |USING |VALUE |WHEN +|WHERE |WITH |WRITE | | | +|=============================================================== diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_1_title.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_1_title.adoc new file mode 100644 index 00000000000..6b4e0d4dedb --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_1_title.adoc @@ -0,0 +1,2 @@ +[[appendix-1.-reserved-keywords]] +== Appendix 1. Reserved keywords diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_index_only.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_index_only.adoc new file mode 100644 index 00000000000..bceb6e7ed96 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_index_only.adoc @@ -0,0 +1,29 @@ +[[controlling-index-only-plan-parameter]] +=== Controlling Index-Only-Plan Parameter + +By default, the system tries to build an index-only plan whenever +utilizing a secondary index is possible. For example, if a SELECT or +JOIN query can utilize an enforced B+Tree or R-Tree index on a field, +the optimizer checks whether a secondary-index search alone can generate +the result that the query asks for. It mainly checks two conditions: (1) +predicates used in WHERE only uses the primary key field and/or +secondary key field and (2) the result does not return any other fields. +If these two conditions hold, it builds an index-only plan. Since an +index-only plan only searches a secondary-index to answer a query, it is +faster than a non-index-only plan that needs to search the primary +index. However, this index-only plan can be turned off per query by +setting the following parameter. + +* *noindexonly*: if this is set to true, the index-only-plan will not be +applied; the default value is false. + +[[example]] +Example + +-------------------------------------------------------------------------------------------- +SET noindexonly 'true'; + +SELECT m.message AS message +FROM GleambookMessages m where m.message = " love product-b its shortcut-menu is awesome:)"; +-------------------------------------------------------------------------------------------- + diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_parallel_sort.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_parallel_sort.adoc new file mode 100644 index 00000000000..f90fb49de58 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_parallel_sort.adoc @@ -0,0 +1,31 @@ +[[parallel-sort-parameter]] +=== Parallel Sort Parameter + +The following parameter enables you to activate or deactivate full +parallel sort for order-by operations. + +When full parallel sort is inactive (`false`), each existing data +partition is sorted (in parallel), and then all data partitions are +merged into a single node. + +When full parallel sort is active (`true`), the data is first sampled, +and then repartitioned so that each partition contains data that is +greater than the previous partition. The data in each partition is then +sorted (in parallel), but the sorted partitions are not merged into a +single node. + +* *compiler.sort.parallel*: A boolean specifying whether full parallel +sort is active (`true`) or inactive (`false`). The default value is +`true`. + +[[example]] +Example + +------------------------------------------- +SET `compiler.sort.parallel` "true"; + +SELECT VALUE user +FROM GleambookUsers AS user +ORDER BY ARRAY_LENGTH(user.friendIds) DESC; +------------------------------------------- + diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_parameters.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_parameters.adoc new file mode 100644 index 00000000000..5dd11fdbee7 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_parameters.adoc @@ -0,0 +1,97 @@ +The SET statement can be used to override some cluster-wide +configuration parameters for a specific request: + +--------------------------------- +SET +--------------------------------- + +As parameter identifiers are qualified names (containing a '.') they +have to be escaped using backticks (``). Note that changing query +parameters will not affect query correctness but only impact performance +characteristics, such as response time and throughput. + +[[parallelism-parameter]] +=== Parallelism Parameter + +The system can execute each request using multiple cores on multiple +machines (a.k.a., partitioned parallelism) in a cluster. A user can +manually specify the maximum execution parallelism for a request to +scale it up and down using the following parameter: + +* *compiler.parallelism*: the maximum number of CPU cores can be used to +process a query. There are three cases of the value _p_ for +compiler.parallelism: +** _p_ < 0 or _p_ > the total number of cores in a cluster: the system +will use all available cores in the cluster; +** _p_ = 0 (the default): the system will use the storage parallelism +(the number of partitions of stored datasets) as the maximum parallelism +for query processing; +** all other cases: the system will use the user-specified number as the +maximum number of CPU cores to use for executing the query. + +[[example]] +Example + +-------------------------------------------------------------------- +SET `compiler.parallelism` "16"; + +SELECT u.name AS uname, m.message AS message +FROM GleambookUsers u JOIN GleambookMessages m ON m.authorId = u.id; +-------------------------------------------------------------------- + +[[memory-parameters]] +=== Memory Parameters + +In the system, each blocking runtime operator such as join, group-by and +order-by works within a fixed memory budget, and can gracefully spill to +disks if the memory budget is smaller than the amount of data they have +to hold. A user can manually configure the memory budget of those +operators within a query. The supported configurable memory parameters +are: + +* *compiler.groupmemory*: the memory budget that each parallel group-by +operator instance can use; 32MB is the default budget. +* *compiler.sortmemory*: the memory budget that each parallel sort +operator instance can use; 32MB is the default budget. +* *compiler.joinmemory*: the memory budget that each parallel hash join +operator instance can use; 32MB is the default budget. +* *compiler.windowmemory*: the memory budget that each parallel window +aggregate operator instance can use; 32MB is the default budget. + +For each memory budget value, you can use a 64-bit integer value with a +1024-based binary unit suffix (for example, B, KB, MB, GB). If there is +no user-provided suffix, "B" is the default suffix. See the following +examples. + +[[example-1]] +Example + +---------------------------------- +SET `compiler.groupmemory` "64MB"; + +SELECT msg.authorId, COUNT(*) +FROM GleambookMessages msg +GROUP BY msg.authorId; +---------------------------------- + +[[example-2]] +Example + +------------------------------------------- +SET `compiler.sortmemory` "67108864"; + +SELECT VALUE user +FROM GleambookUsers AS user +ORDER BY ARRAY_LENGTH(user.friendIds) DESC; +------------------------------------------- + +[[example-3]] +Example + +-------------------------------------------------------------------- +SET `compiler.joinmemory` "132000KB"; + +SELECT u.name AS uname, m.message AS message +FROM GleambookUsers u JOIN GleambookMessages m ON m.authorId = u.id; +-------------------------------------------------------------------- + diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_title.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_title.adoc new file mode 100644 index 00000000000..b1f1ceb8555 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_2_title.adoc @@ -0,0 +1,2 @@ +[[appendix-2.-performance-tuning]] +== Appendix 2. Performance Tuning diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_3_resolution.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_3_resolution.adoc new file mode 100644 index 00000000000..7920ad6fb54 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_3_resolution.adoc @@ -0,0 +1,352 @@ +In this Appendix, we'll look at how variables are bound and how names +are resolved. Names can appear in every clause of a query. Sometimes a +name consists of just a single identifier, e.g., `region` or `revenue`. +More often a name will consist of two identifiers separated by a dot, +e.g., `customer.address`. Occasionally a name may have more than two +identifiers, e.g., `policy.owner.address.zipcode`. _Resolving_ a name +means determining exactly what the (possibly multi-part) name refers to. +It is necessary to have well-defined rules for how to resolve a name in +cases of ambiguity. (In the absence of schemas, such cases arise more +commonly, and also differently, than they do in SQL.) + +The basic job of each clause in a query block is to bind variables. Each +clause sees the variables bound by previous clauses and may bind +additional variables. Names are always resolved with respect to the +variables that are bound ("in scope") at the place where the name use in +question occurs. It is possible that the name resolution process will +fail, which may lead to an empty result or an error message. + +One important bit of background: When the system is reading a query and +resolving its names, it has a list of all the available dataverses and +datasets. As a result, it knows whether `a.b` is a valid name for +dataset `b` in dataverse `a`. However, the system does not in general +have knowledge of the schemas of the data inside the datasets; remember +that this is a much more open world. As a result, in general the system +cannot know whether any object in a particular dataset will have a field +named `c`. These assumptions affect how errors are handled. If you try +to access dataset `a.b` and no dataset by that name exists, you will get +an error and your query will not run. However, if you try to access a +field `c` in a collection of objects, your query will run and return +`missing` for each object that doesn't have a field named `c` – this is +because it’s possible that some object (someday) could have such a +field. + +[[binding-variables]] +=== Binding Variables + +Variables can be bound in the following ways: + +1. WITH and LET clauses bind a variable to the result of an expression +in a straightforward way ++ +Examples: ++ +`WITH cheap_parts AS (SELECT partno FROM parts WHERE price < 100)` binds +the variable `cheap_parts` to the result of the subquery. ++ +`LET pay = salary + bonus` binds the variable `pay` to the result of +evaluating the expression `salary + bonus`. +2. FROM, GROUP BY, and SELECT clauses have optional AS subclauses that +contain an expression and a name (called an _iteration variable_ in a +FROM clause, or an alias in GROUP BY or SELECT.) ++ +Examples: ++ +`FROM customer AS c, order AS o` ++ +`GROUP BY salary + bonus AS total_pay` ++ +`SELECT MAX(price) AS highest_price` ++ +An AS subclause always binds the name (as a variable) to the result of +the expression (or, in the case of a FROM clause, to the _individual +members_ of the collection identified by the expression.) ++ +It's always a good practice to use the keyword AS when defining an alias +or iteration variable. However, as in SQL, the syntax allows the keyword +AS to be omitted. For example, the FROM clause above could have been +written like this: ++ +`FROM customer c, order o` ++ +Omitting the keyword AS does not affect the binding of variables. The +FROM clause in this example binds variables c and o whether the keyword +AS is used or not. ++ +In certain cases, a variable is automatically bound even if no alias or +variable-name is specified. Whenever an expression could have been +followed by an AS subclause, if the expression consists of a simple name +or a path expression, that expression binds a variable whose name is the +same as the simple name or the last step in the path expression. Here +are some examples: ++ +`FROM customer, order` binds iteration variables named `customer` and +`order` ++ +`GROUP BY address.zipcode` binds a variable named `zipcode` ++ +`SELECT item[0].price` binds a variable named `price` ++ +Note that a FROM clause iterates over a collection (usually a dataset), +binding a variable to each member of the collection in turn. The name of +the collection remains in scope, but it is not a variable. For example, +consider this FROM clause used in a self-join: ++ +`FROM customer AS c1, customer AS c2` ++ +This FROM clause joins the customer dataset to itself, binding the +iteration variables c1 and c2 to objects in the left-hand-side and +right-hand-side of the join, respectively. After the FROM clause, c1 and +c2 are in scope as variables, and customer remains accessible as a +dataset name but not as a variable. +3. Special rules for GROUP BY: +1. If a GROUP BY clause specifies an expression that has no explicit +alias, it binds a pseudo-variable that is lexicographically identical to +the expression itself. For example: ++ +`GROUP BY salary + bonus` binds a pseudo-variable named +`salary + bonus`. ++ +This rule allows subsequent clauses to refer to the grouping expression +(salary + bonus) even though its constituent variables (salary and +bonus) are no longer in scope. For example, the following query is +valid: ++ +------------------------------------------- +FROM employee +GROUP BY salary + bonus +HAVING salary + bonus > 1000 +SELECT salary + bonus, COUNT(*) AS how_many +------------------------------------------- ++ +While it might have been more elegant to explicitly require an alias in +cases like this, the pseudo-variable rule is retained for SQL +compatibility. Note that the expression `salary + bonus` is not +_actually_ evaluated in the HAVING and SELECT clauses (and could not be +since `salary` and `bonus` are no longer individually in scope). +Instead, the expression `salary + bonus` is treated as a reference to +the pseudo-variable defined in the GROUP BY clause. +2. A GROUP BY clause may be followed by a GROUP AS clause that binds a +variable to the group. The purpose of this variable is to make the +individual objects inside the group visible to subqueries that may need +to iterate over them. ++ +The GROUP AS variable is bound to a multiset of objects. Each object +represents one of the members of the group. Since the group may have +been formed from a join, each of the member-objects contains a nested +object for each variable bound by the nearest FROM clause (and its LET +subclause, if any). These nested objects, in turn, contain the actual +fields of the group-member. To understand this process, consider the +following query fragment: ++ +------------------------------- +FROM parts AS p, suppliers AS s +WHERE p.suppno = s.suppno +GROUP BY p.color GROUP AS g +------------------------------- ++ +Suppose that the objects in `parts` have fields `partno`, `color`, and +`suppno`. Suppose that the objects in suppliers have fields `suppno` and +`location`. ++ +Then, for each group formed by the GROUP BY, the variable g will be +bound to a multiset with the following structure: ++ +------------------------------------------------------------ +[ { "p": { "partno": "p1", "color": "red", "suppno": "s1" }, + "s": { "suppno": "s1", "location": "Denver" } }, + { "p": { "partno": "p2", "color": "red", "suppno": "s2" }, + "s": { "suppno": "s2", "location": "Atlanta" } }, + ... +] +------------------------------------------------------------ + +[[scoping]] +=== Scoping + +In general, the variables that are in scope at a particular position are +those variables that were bound earlier in the current query block, in +outer (enclosing) query blocks, or in a WITH clause at the beginning of +the query. More specific rules follow. + +The clauses in a query block are conceptually processed in the following +order: + +* FROM (followed by LET subclause, if any) +* WHERE +* GROUP BY (followed by LET subclause, if any) +* HAVING +* SELECT or SELECT VALUE +* ORDER BY +* OFFSET +* LIMIT + +During processing of each clause, the variables that are in scope are +those variables that are bound in the following places: + +1. In earlier clauses of the same query block (as defined by the +ordering given above). ++ +Example: `FROM orders AS o SELECT o.date` The variable `o` in the SELECT +clause is bound, in turn, to each object in the dataset `orders`. +2. In outer query blocks in which the current query block is nested. In +case of duplication, the innermost binding wins. +3. In the WITH clause (if any) at the beginning of the query. + +However, in a query block where a GROUP BY clause is present: + +1. In clauses processed before GROUP BY, scoping rules are the same as +though no GROUP BY were present. +2. In clauses processed after GROUP BY, the variables bound in the +nearest FROM-clause (and its LET subclause, if any) are removed from +scope and replaced by the variables bound in the GROUP BY clause (and +its LET subclause, if any). However, this replacement does not apply +inside the arguments of the five SQL special aggregating functions (MIN, +MAX, AVG, SUM, and COUNT). These functions still need to see the +individual data items over which they are computing an aggregation. For +example, after `FROM employee AS e GROUP BY deptno`, it would not be +valid to reference `e.salary`, but `AVG(e.salary)` would be valid. + +Special case: In an expression inside a FROM clause, a variable is in +scope if it was bound in an earlier expression in the same FROM clause. +Example: + +------------------------------ +FROM orders AS o, o.items AS i +------------------------------ + +The reason for this special case is to support iteration over nested +collections. + +Note that, since the SELECT clause comes _after_ the WHERE and GROUP BY +clauses in conceptual processing order, any variables defined in SELECT +are not visible in WHERE or GROUP BY. Therefore the following query will +not return what might be the expected result (since in the WHERE clause, +`pay` will be interpreted as a field in the `emp` object rather than as +the computed value `salary + bonus`): + +---------------------------------- +SELECT name, salary + bonus AS pay +FROM emp +WHERE pay > 1000 +ORDER BY pay +---------------------------------- + +The likely intent of the query above can be accomplished as follows: + +---------------------------- +FROM emp AS e +LET pay = e.salary + e.bonus +WHERE pay > 1000 +SELECT e.name, pay +ORDER BY pay +---------------------------- + +Note that variables defined by `JOIN` subclauses are not visible to +other subclauses in the same `FROM` clause. This also applies to the +`FROM` variable that starts the `JOIN` subclause. + +[[resolving-names]] +=== Resolving Names + +The process of name resolution begins with the leftmost identifier in +the name. The rules for resolving the leftmost identifier are: + +. _In a FROM clause_: Names in a FROM clause identify the collections +over which the query block will iterate. These collections may be stored +datasets or may be the results of nested query blocks. A stored dataset +may be in a named dataverse or in the default dataverse. Thus, if the +two-part name `a.b` is in a FROM clause, a might represent a dataverse +and `b` might represent a dataset in that dataverse. Another example of +a two-part name in a FROM clause is `FROM orders AS o, o.items AS i`. In +`o.items`, `o` represents an order object bound earlier in the FROM +clause, and items represents the items object inside that order. ++ +The rules for resolving the leftmost identifier in a FROM clause +(including a JOIN subclause), or in the expression following IN in a +quantified predicate, are as follows: + + .. If the identifier matches a variable-name that is in scope, it +resolves to the binding of that variable. (Note that in the case of a +subquery, an in-scope variable might have been bound in an outer query +block; this is called a correlated subquery.) + .. Otherwise, if the identifier is the first part of a two-part name +like `a.b`, the name is treated as `dataverse.dataset`. If the +identifier stands alone as a one-part name, it is treated as the name of +a dataset in the default dataverse. If the designated dataset exists +then the identifier is resolved to that dataset, otherwise if a synonym +with given name exists then the identifier is resolved to the target +dataset of that synonym (potentially recursively if this synonym points +to another synonym). An error will result if the designated dataset or a +synonym with this name does not exist. ++ +Datasets take precedence over synonyms, so if both a dataset and a +synonym have the same name then the resolution is to the dataset. + +. _Elsewhere in a query block_: In clauses other than FROM, a name +typically identifies a field of some object. For example, if the +expression `a.b` is in a SELECT or WHERE clause, it's likely that `a` +represents an object and `b` represents a field in that object. ++ +The rules for resolving the leftmost identifier in clauses other than +the ones listed in Rule 1 are: + + .. If the identifier matches a variable-name that is in scope, it +resolves to the binding of that variable. (In the case of a correlated +subquery, the in-scope variable might have been bound in an outer query +block.) + .. (The "Single Variable Rule"): Otherwise, if the FROM clause in the +current query block binds exactly one variable, the identifier is +treated as a field access on the object bound to that variable. For +example, in the query `FROM customer SELECT address`, the identifier +address is treated as a field in the object bound to the variable +customer. At runtime, if the object bound to customer has no `address` +field, the `address` expression will return `missing`. If the FROM +clause in the current query block binds multiple variables, name +resolution fails with an "ambiguous name" error. If there's no FROM +clause in the current query block, name resolution fails with an +"undefined identifier" error. Note that the Single Variable Rule +searches for bound variables only in the current query block, not in +outer (containing) blocks. The purpose of this rule is to permit the +compiler to resolve field-references unambiguously without relying on +any schema information. Also note that variables defined by LET clauses +do not participate in the resolution process performed by this rule. ++ +Exception: In a query that has a GROUP BY clause, the Single Variable +Rule does not apply in any clauses that occur after the GROUP BY +because, in these clauses, the variables bound by the FROM clause are no +longer in scope. In clauses after GROUP BY, only Rule 2.1 applies. + +. In an ORDER BY clause following a UNION ALL expression: ++ +The leftmost identifier is treated as a field-access on the objects that +are generated by the UNION ALL. For example: ++ +--------------- +query-block-1 +UNION ALL +query-block-2 +ORDER BY salary +--------------- ++ +In the result of this query, objects that have a foo field will be +ordered by the value of this field; objects that have no foo field will +appear at at the beginning of the query result (in ascending order) or +at the end (in descending order.) + +. _In a standalone expression_: If a query consists of a standalone +expression then identifiers inside that expression are resolved +according to Rule 1. For example, if the whole query is +`ARRAY_COUNT(a.b)` then `a.b` will be treated as dataset `b` contained +in dataverse `a`. Note that this rule only applies to identifiers which +are located directly inside a standalone expression. Identifiers inside +SELECT statements in a standalone expression are still resolved +according to Rules 1-3. For example, if the whole query is +`ARRAY_SUM( (FROM employee AS e SELECT VALUE salary) )` then `salary` is +resolved as `e.salary` following the "Single Variable Rule" (Rule 2.2). + +. Once the leftmost identifier has been resolved, the following dots +and identifiers in the name (if any) are treated as a path expression +that navigates to a field nested inside that object. The name resolves +to the field at the end of the path. If this field does not exist, the +value `missing` is returned. diff --git a/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_3_title.adoc b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_3_title.adoc new file mode 100644 index 00000000000..8ed20df51c3 --- /dev/null +++ b/asterixdb/asterix-doc/src/shared/modules/sqlpp/partials/appendix_3_title.adoc @@ -0,0 +1,2 @@ +[[appendix-3.-variable-bindings-and-name-resolution]] +== Appendix 3. Variable Bindings and Name Resolution diff --git a/asterixdb/asterix-doc/src/site/asciidoc/aql/builtins.adoc b/asterixdb/asterix-doc/src/site/asciidoc/aql/builtins.adoc new file mode 100644 index 00000000000..244f3096037 --- /dev/null +++ b/asterixdb/asterix-doc/src/site/asciidoc/aql/builtins.adoc @@ -0,0 +1,41 @@ += Builtin Functions +:includedir: ../../shared/modules/builtins/partials +:toc: +:toclevels: 1 + +:data-model: xref:../datamodel.adoc +:primitive-types: xref:../datamodel.adoc#PrimitiveTypes +:over-clauses: xref:manual.adoc#Over_clauses +:window-partition-clause: xref:manual.adoc#Window_partition_clause +:window-order-clause: xref:manual.adoc#Window_order_clause +:window-frame-clause: xref:manual.adoc#Window_frame_clause +:nulls-treatment: xref:manual.adoc#Nulls_treatment +:nth-val-from: xref:manual.adoc#Nth_val_from +:select-statements: xref:manual.adoc#SELECT_statements +:sql-92-aggregation-functions: xref:manual.adoc#SQL-92_aggregation_functions +:aggregation-functions: xref:manual.adoc#Aggregation_functions +:aggregate-functions: xref:builtins.adoc#AggregateFunctions + +:n_gram: true +:upper-name: ASTERIXDB +:camel-name: AsterixDB +:title-name: Asterixdb +:lower-name: asterixdb + +include::{includedir}/0_toc_common.adoc[] +include::{includedir}/1_numeric_common.adoc[] +include::{includedir}/1_numeric_delta.adoc[] +include::{includedir}/2_string_common.adoc[] +include::{includedir}/2_string_delta.adoc[] +include::{includedir}/3_binary.adoc[] +include::{includedir}/4_spatial.adoc[] +include::{includedir}/5_similarity.adoc[] +include::{includedir}/6_tokenizing.adoc[] +include::{includedir}/7_temporal.adoc[] +include::{includedir}/7_allens.adoc[] +include::{includedir}/8_record.adoc[] +include::{includedir}/9_aggregate_sql.adoc[] +include::{includedir}/10_comparison.adoc[] +include::{includedir}/11_type.adoc[] +include::{includedir}/13_conditional.adoc[] +include::{includedir}/12_misc.adoc[] diff --git a/asterixdb/asterix-doc/src/site/asciidoc/datamodel.adoc b/asterixdb/asterix-doc/src/site/asciidoc/datamodel.adoc new file mode 100644 index 00000000000..3704c6d5141 --- /dev/null +++ b/asterixdb/asterix-doc/src/site/asciidoc/datamodel.adoc @@ -0,0 +1,36 @@ +//// +Licensed to the Apache Software Foundation (ASF) under one +or more contributor license agreements. See the NOTICE file +distributed with this work for additional information +regarding copyright ownership. The ASF licenses this file +to you under the Apache License, Version 2.0 (the +"License"); you may not use this file except in compliance +with the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, +software distributed under the License is distributed on an +"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +KIND, either express or implied. See the License for the +specific language governing permissions and limitations +under the License. +//// + += The Asterix Data Model (ADM) +:includedir: ../../shared/modules/datamodel/partials +:toc: +:toclevels: 2 + +An instance of Asterix data model (ADM) can be a __primitive type__ +(`boolean`, `tinyint`, `smallint`, `integer`, `bigint`, `string`, +`float`, `double`, `date`, `time`, `datetime`, etc.), a __special type__ +(`null` or `missing`), or a __derived type__. + +The type names are case-insensitive, e.g., both `BIGINT` and `bigint` +are acceptable. + +include::{includedir}/datamodel_primitive_common.adoc[] +include::{includedir}/datamodel_primitive_delta.adoc[] +include::{includedir}/datamodel_incomplete.adoc[] +include::{includedir}/datamodel_composite.adoc[] diff --git a/asterixdb/asterix-doc/src/site/asciidoc/sqlpp/builtins.adoc b/asterixdb/asterix-doc/src/site/asciidoc/sqlpp/builtins.adoc new file mode 100644 index 00000000000..02f80554680 --- /dev/null +++ b/asterixdb/asterix-doc/src/site/asciidoc/sqlpp/builtins.adoc @@ -0,0 +1,43 @@ += Builtin Functions +:includedir: ../../shared/modules/builtins/partials +:toc: +:toclevels: 1 + +:data-model: xref:../datamodel.adoc +:primitive-types: xref:../datamodel.adoc#PrimitiveTypes +:over-clauses: xref:manual.adoc#Over_clauses +:window-partition-clause: xref:manual.adoc#Window_partition_clause +:window-order-clause: xref:manual.adoc#Window_order_clause +:window-frame-clause: xref:manual.adoc#Window_frame_clause +:nulls-treatment: xref:manual.adoc#Nulls_treatment +:nth-val-from: xref:manual.adoc#Nth_val_from +:select-statements: xref:manual.adoc#SELECT_statements +:sql-92-aggregation-functions: xref:manual.adoc#SQL-92_aggregation_functions +:aggregation-functions: xref:manual.adoc#Aggregation_functions +:aggregate-functions: xref:builtins.adoc#AggregateFunctions + +:n_gram: true +:upper-name: ASTERIXDB +:camel-name: AsterixDB +:title-name: Asterixdb +:lower-name: asterixdb + +include::{includedir}/0_toc_common.adoc[] +include::{includedir}/1_numeric_common.adoc[] +include::{includedir}/1_numeric_delta.adoc[] +include::{includedir}/2_string_common.adoc[] +include::{includedir}/2_string_delta.adoc[] +include::{includedir}/3_binary.adoc[] +include::{includedir}/4_spatial.adoc[] +include::{includedir}/5_similarity.adoc[] +include::{includedir}/6_tokenizing.adoc[] +include::{includedir}/7_temporal.adoc[] +include::{includedir}/7_allens.adoc[] +include::{includedir}/8_record.adoc[] +include::{includedir}/9_aggregate_sql.adoc[] +include::{includedir}/10_comparison.adoc[] +include::{includedir}/11_type.adoc[] +include::{includedir}/13_conditional.adoc[] +include::{includedir}/12_misc.adoc[] +include::{includedir}/15_bitwise.adoc[] +include::{includedir}/14_window.adoc[] diff --git a/asterixdb/asterix-doc/src/site/asciidoc/sqlpp/manual.adoc b/asterixdb/asterix-doc/src/site/asciidoc/sqlpp/manual.adoc new file mode 100644 index 00000000000..0272b607626 --- /dev/null +++ b/asterixdb/asterix-doc/src/site/asciidoc/sqlpp/manual.adoc @@ -0,0 +1,31 @@ += The Query Language +:includedir: ../../shared/modules/sqlpp/partials +:toc: +:toclevels: 1 + +:aggregate-functions: xref:builtins.adoc#AggregateFunctions +:window-functions: xref:builtins.adoc#WindowFunctions +:over-clauses: xref:manual.adoc#Over_clauses +:service-api: link:../api.html#queryservice + +include::{includedir}/1_intro.adoc[] +include::{includedir}/2_expr_title.adoc[] +include::{includedir}/2_expr.adoc[] +include::{includedir}/3_query_title.adoc[] +include::{includedir}/3_declare_dataverse.adoc[] +include::{includedir}/3_declare_function.adoc[] +include::{includedir}/3_query.adoc[] +include::{includedir}/4_error_title.adoc[] +include::{includedir}/4_error.adoc[] +include::{includedir}/5_ddl_head.adoc[] +include::{includedir}/5_ddl_dataset_index.adoc[] +include::{includedir}/5_ddl_function_removal.adoc[] +include::{includedir}/5_ddl_dml.adoc[] +include::{includedir}/appendix_1_title.adoc[] +include::{includedir}/appendix_1_keywords.adoc[] +include::{includedir}/appendix_2_title.adoc[] +include::{includedir}/appendix_2_parameters.adoc[] +include::{includedir}/appendix_2_parallel_sort.adoc[] +include::{includedir}/appendix_2_index_only.adoc[] +include::{includedir}/appendix_3_title.adoc[] +include::{includedir}/appendix_3_resolution.adoc[]