Transform partition key, generate hive path

pyiceberg/partitioning.py

@@ -16,9 +16,21 @@
 # under the License.
 from __future__ import annotations
 
+import uuid
 from abc import ABC, abstractmethod
+from dataclasses import dataclass
+from datetime import date, datetime
 from functools import cached_property, singledispatch
-from typing import Any, Dict, Generic, List, Optional, Tuple, TypeVar
+from typing import (
+    Any,
+    Dict,
+    Generic,
+    List,
+    Optional,
+    Tuple,
+    TypeVar,
+)
+from urllib.parse import quote
 
 from pydantic import (
     BeforeValidator,
@@ -41,8 +53,18 @@
     YearTransform,
     parse_transform,
 )
-from pyiceberg.typedef import IcebergBaseModel
-from pyiceberg.types import NestedField, StructType
+from pyiceberg.typedef import IcebergBaseModel, Record
+from pyiceberg.types import (
+    DateType,
+    IcebergType,
+    NestedField,
+    PrimitiveType,
+    StructType,
+    TimestampType,
+    TimestamptzType,
+    UUIDType,
+)
+from pyiceberg.utils.datetime import date_to_days, datetime_to_micros
 
 INITIAL_PARTITION_SPEC_ID = 0
 PARTITION_FIELD_ID_START: int = 1000
@@ -199,6 +221,23 @@ def partition_type(self, schema: Schema) -> StructType:
             nested_fields.append(NestedField(field.field_id, field.name, result_type, required=False))
         return StructType(*nested_fields)
 
+    def partition_to_path(self, data: Record, schema: Schema) -> str:
+        partition_type = self.partition_type(schema)
+        field_types = partition_type.fields
+
+        field_strs = []
+        value_strs = []
+        for pos, value in enumerate(data.record_fields()):
+            partition_field = self.fields[pos]
+            value_str = partition_field.transform.to_human_string(field_types[pos].field_type, value=value)
+
+            value_str = quote(value_str, safe='')
+            value_strs.append(value_str)
+            field_strs.append(partition_field.name)
+
+        path = "/".join([field_str + "=" + value_str for field_str, value_str in zip(field_strs, value_strs)])
+        return path
+
 
 UNPARTITIONED_PARTITION_SPEC = PartitionSpec(spec_id=0)
 
@@ -326,3 +365,59 @@ def _visit_partition_field(schema: Schema, field: PartitionField, visitor: Parti
         return visitor.unknown(field.field_id, source_name, field.source_id, repr(transform))
     else:
         raise ValueError(f"Unknown transform {transform}")
+
+
+@dataclass(frozen=True)
+class PartitionFieldValue:
+    field: PartitionField
+    value: Any
+
+
+@dataclass(frozen=True)
+class PartitionKey:
+    raw_partition_field_values: List[PartitionFieldValue]
+    partition_spec: PartitionSpec
+    schema: Schema
+
+    @cached_property
+    def partition(self) -> Record:  # partition key transformed with iceberg internal representation as input
+        iceberg_typed_key_values = {}
+        for raw_partition_field_value in self.raw_partition_field_values:
+            partition_fields = self.partition_spec.source_id_to_fields_map[raw_partition_field_value.field.source_id]
+            if len(partition_fields) != 1:
+                raise ValueError("partition_fields must contain exactly one field.")
+            partition_field = partition_fields[0]
+            iceberg_type = self.schema.find_field(name_or_id=raw_partition_field_value.field.source_id).field_type
+            iceberg_typed_value = _to_partition_representation(iceberg_type, raw_partition_field_value.value)
+            transformed_value = partition_field.transform.transform(iceberg_type)(iceberg_typed_value)
+            iceberg_typed_key_values[partition_field.name] = transformed_value
+        return Record(**iceberg_typed_key_values)
+
+    def to_path(self) -> str:
+        return self.partition_spec.partition_to_path(self.partition, self.schema)
+
+
+@singledispatch
+def _to_partition_representation(type: IcebergType, value: Any) -> Any:
+    return TypeError(f"Unsupported partition field type: {type}")
+
+
+@_to_partition_representation.register(TimestampType)
+@_to_partition_representation.register(TimestamptzType)
+def _(type: IcebergType, value: Optional[datetime]) -> Optional[int]:
+    return datetime_to_micros(value) if value is not None else None
+
+
+@_to_partition_representation.register(DateType)
+def _(type: IcebergType, value: Optional[date]) -> Optional[int]:
+    return date_to_days(value) if value is not None else None
+
+
+@_to_partition_representation.register(UUIDType)
+def _(type: IcebergType, value: Optional[uuid.UUID]) -> Optional[str]:
+    return str(value) if value is not None else None
+
+
+@_to_partition_representation.register(PrimitiveType)
+def _(type: IcebergType, value: Optional[Any]) -> Optional[Any]:
+    return value

pyiceberg/transforms.py

@@ -655,6 +655,11 @@ def _(value: int, _type: IcebergType) -> str:
     return _int_to_human_string(_type, value)
 
 
+@_human_string.register(bool)
+def _(value: bool, _type: IcebergType) -> str:
+    return str(value).lower()
+
+
 @singledispatch
 def _int_to_human_string(_type: IcebergType, value: int) -> str:
     return str(value)

tests/conftest.py

@@ -46,9 +46,10 @@
 import boto3
 import pytest
 from moto import mock_aws
+from pyspark.sql import SparkSession
 
 from pyiceberg import schema
-from pyiceberg.catalog import Catalog
+from pyiceberg.catalog import Catalog, load_catalog
 from pyiceberg.catalog.noop import NoopCatalog
 from pyiceberg.expressions import BoundReference
 from pyiceberg.io import (
@@ -1925,3 +1926,51 @@ def table_v2(example_table_metadata_v2: Dict[str, Any]) -> Table:
 @pytest.fixture
 def bound_reference_str() -> BoundReference[str]:
     return BoundReference(field=NestedField(1, "field", StringType(), required=False), accessor=Accessor(position=0, inner=None))
+
+
+@pytest.fixture(scope="session")
+def session_catalog() -> Catalog:
+    return load_catalog(
+        "local",
+        **{
+            "type": "rest",
+            "uri": "http://localhost:8181",
+            "s3.endpoint": "http://localhost:9000",
+            "s3.access-key-id": "admin",
+            "s3.secret-access-key": "password",
+        },
+    )
+
+
+@pytest.fixture(scope="session")
+def spark() -> SparkSession:
+    import importlib.metadata
+    import os
+
+    spark_version = ".".join(importlib.metadata.version("pyspark").split(".")[:2])
+    scala_version = "2.12"
+    iceberg_version = "1.4.3"
+
+    os.environ["PYSPARK_SUBMIT_ARGS"] = (
+        f"--packages org.apache.iceberg:iceberg-spark-runtime-{spark_version}_{scala_version}:{iceberg_version},"
+        f"org.apache.iceberg:iceberg-aws-bundle:{iceberg_version} pyspark-shell"
+    )
+    os.environ["AWS_REGION"] = "us-east-1"
+    os.environ["AWS_ACCESS_KEY_ID"] = "admin"
+    os.environ["AWS_SECRET_ACCESS_KEY"] = "password"
+
+    spark = (
+        SparkSession.builder.appName("PyIceberg integration test")
+        .config("spark.sql.extensions", "org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions")
+        .config("spark.sql.catalog.integration", "org.apache.iceberg.spark.SparkCatalog")
+        .config("spark.sql.catalog.integration.catalog-impl", "org.apache.iceberg.rest.RESTCatalog")
+        .config("spark.sql.catalog.integration.uri", "http://localhost:8181")
+        .config("spark.sql.catalog.integration.io-impl", "org.apache.iceberg.aws.s3.S3FileIO")
+        .config("spark.sql.catalog.integration.warehouse", "s3://warehouse/wh/")
+        .config("spark.sql.catalog.integration.s3.endpoint", "http://localhost:9000")
+        .config("spark.sql.catalog.integration.s3.path-style-access", "true")
+        .config("spark.sql.defaultCatalog", "integration")
+        .getOrCreate()
+    )
+
+    return spark