DMYTRO_DORONIN-w3-database

Week3/assignment/exercise1-normalization.md

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+# Exercise 3.1 - SQL Normalization
+
+Original table:
+
+member_id | member_name | member_address | dinner_id | dinner_date | venue_code | venue_description | food_code  | food_description
+--------- | ----------- | -------------- | --------- | ----------- | ---------- | ----------------- | ---------- | ----------------
+...       | ...         | ...            | ...       | ...         | ...        | ...               | C1, C2     | Curry, Cake
+...       | ...         | ...            | ...       | ...         | ...        | ...               | P1, T1, M1 | Pie, Tea, Mousse
+etc.
+
+---
+
+## 1. Which columns violate 1NF?
+
+1NF (First Normal Form) requires:
+
+- Each field contains **atomic** (indivisible) values.
+- No repeating groups or lists in a single column.
+- All values in a column are of the same type.
+
+In this table, 1NF is violated by:
+
+- **food_code** - contains multiple values separated by commas, e.g. `C1, C2`, `P1, T1, M1`.
+- **food_description** - also contains multiple values separated by commas, e.g. `Curry, Cake`, `Pie, Tea, Mousse`.
+
+Additionally, **dinner_date** is stored in multiple different formats (`2020-03-15`, `20-03-2020`, `Mar 25 '20`), which is bad practice, but they are still single scalar values. The main 1NF violation is the multi-valued food columns.
+
+---
+
+## 2. Which entities can be extracted?
+
+From the table we can identify the following entities:
+
+1. **Member**
+    - member_id
+    - member_name
+    - member_address
+
+2. **Dinner (Event)**
+    - dinner_id
+    - dinner_date
+    - venue_code (the place where the dinner is held)
+
+3. **Venue**
+    - venue_code
+    - venue_description
+
+4. **Food**
+    - food_code
+    - food_description
+
+5. **MemberDinner / Attendance**
+    - which member attended which dinner  
+      (many-to-many relationship between Member and Dinner)
+
+6. **DinnerFood / Menu**
+    - which food items were served at a given dinner  
+      (many-to-many relationship between Dinner and Food)
+
+---
+
+## 3. Tables and columns for a 3NF-compliant solution
+
+Below is a 3NF schema.
+
+### 1. Table `members`
+
+- **member_id** (PK)
+- member_name
+- member_address
+
+Functional dependency:  
+`member_id → member_name, member_address`  
+No transitive dependencies.
+
+---
+
+### 2. Table `venues`
+
+- **venue_code** (PK)
+- venue_description
+
+Functional dependency:  
+`venue_code → venue_description`
+
+---
+
+### 3. Table `dinners`
+
+- **dinner_id** (PK)
+- dinner_date (DATE type)
+- venue_code (FK → venues.venue_code)
+
+Functional dependency:  
+`dinner_id → dinner_date, venue_code`
+
+---
+
+### 4. Table `foods`
+
+- **food_code** (PK)
+- food_description
+
+Functional dependency:  
+`food_code → food_description`
+
+---
+
+### 5. Table `member_dinners` (attendance)
+
+- **member_id** (FK → members.member_id)
+- **dinner_id** (FK → dinners.dinner_id)
+- (PK is the combination (member_id, dinner_id))
+
+This table represents which member attended which dinner (many-to-many).
+
+---
+
+### 6. Table `dinner_foods` (menu per dinner)
+
+- **dinner_id** (FK → dinners.dinner_id)
+- **food_code** (FK → foods.food_code)
+- (PK is the combination (dinner_id, food_code))
+
+This table replaces the multi-valued fields `food_code` and `food_description` by storing one row per dinner–food combination.
+
+---
+
+## Final 3NF schema
+
+- `members(member_id PK, member_name, member_address)`
+- `venues(venue_code PK, venue_description)`
+- `dinners(dinner_id PK, dinner_date, venue_code FK)`
+- `foods(food_code PK, food_description)`
+- `member_dinners(member_id FK, dinner_id FK, PK(member_id, dinner_id))`
+- `dinner_foods(dinner_id FK, food_code FK, PK(dinner_id, food_code))`

Week3/assignment/index.js

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+require("dotenv").config()
+const { MongoClient, ObjectId } = require("mongodb")
+
+const uri = process.env.MONGODB_URI
+
+if (!uri) {
+    throw new Error("Please set MONGODB_URI in your .env file")
+}
+
+async function main() {
+    const client = new MongoClient(uri)
+
+    try {
+        await client.connect()
+        console.log("Connected to MongoDB Atlas")
+
+        const db = client.db("databaseWeek3")
+        const episodes = db.collection("bob_ross_episodes")
+
+        const newEpisode = {
+            title: "My Custom Joy of Painting Episode",
+            season: 100,
+            episode: 1,
+            elements: ["happy little trees", "mountain", "lake"],
+            aired_on: new Date("2025-01-01"),
+        }
+
+        const insertResult = await episodes.insertOne(newEpisode)
+        console.log("Inserted new episode with _id:", insertResult.insertedId)
+
+
+        const insertedId = insertResult.insertedId
+        const foundById = await episodes.findOne({ _id: insertedId })
+
+        const cursor = episodes.find({ elements: "happy little trees" })
+        const episodesWithTrees = await cursor.toArray()
+
+        console.log(
+            `Episodes with "happy little trees": ${episodesWithTrees.length}`
+        )
+
+        const updateResult = await episodes.updateOne(
+            { _id: insertedId },
+            {
+                $set: {
+                    title: "Updated Custom Joy of Painting Episode",
+                    updated_at: new Date(),
+                },
+            }
+        )
+
+        console.log(
+            `Updated episodes: matched ${updateResult.matchedCount}, modified ${updateResult.modifiedCount}`
+        )
+
+        const updatedDoc = await episodes.findOne({ _id: insertedId })
+
+        const deleteResult = await episodes.deleteOne({ _id: insertedId })
+        console.log(`Deleted documents: ${deleteResult.deletedCount}`)
+    } catch (err) {
+        console.error("MongoDB error:", err)
+    } finally {
+        await client.close()
+        console.log("Connection to MongoDB closed")
+    }
+}
+
+main().catch((err) => {
+    console.error(err)
+    process.exit(1)
+})