JavaScript
// Connect and perform basic operations
const { MongoClient } = require('mongodb');

const client = new MongoClient('mongodb://localhost:27017');
await client.connect();
const db = client.db('myapp');
const collection = db.collection('users');

// Insert document
await collection.insertOne({
  name: 'John Doe',
  email: 'john@example.com',
  createdAt: new Date()
});

// Query with index-friendly patterns
const users = await collection.find({ email: 'john@example.com' }).toArray();

Progress:

• Schema Design: Plan document structure and relationships
• Indexing Strategy: Create appropriate indexes before data growth
• Query Implementation: Write efficient queries using aggregation pipeline
• Performance Testing: Monitor query performance and optimize
• Error Handling: Implement proper connection and operation error handling

Schema Design Process

1. Identify access patterns and query requirements
2. Design embedded vs referenced data based on read/write patterns
3. Plan for data growth and sharding if needed
4. Validate schema with sample data

Query Optimization

1. Use explain() to analyze query execution
2. Create compound indexes for multi-field queries
3. Use aggregation pipeline for complex data transformations
4. Implement proper pagination with cursor-based approach

Example 1: User Profile with Embedded Data Input: User with posts and comments

JavaScript
// Schema design
{
  _id: ObjectId,
  username: "johndoe",
  profile: {
    firstName: "John",
    lastName: "Doe",
    avatar: "avatar.jpg"
  },
  recentPosts: [
    { title: "Post 1", createdAt: ISODate, excerpt: "..." }
  ]
}

// Efficient query
db.users.find({ username: "johndoe" }).project({ "recentPosts": { $slice: 5 } })

Example 2: Aggregation Pipeline Input: Calculate user engagement metrics

JavaScript
db.users.aggregate([
  { $match: { lastLogin: { $gte: new Date(Date.now() - 30*24*60*60*1000) } } },
  { $lookup: { from: "posts", localField: "_id", foreignField: "authorId", as: "posts" } },
  { $project: {
    username: 1,
    postCount: { $size: "$posts" },
    avgLikes: { $avg: "$posts.likes" }
  }},
  { $sort: { postCount: -1 } }
])

Example 3: Proper Indexing

JavaScript
// Compound index for common query patterns
db.users.createIndex({ "status": 1, "createdAt": -1 })
db.posts.createIndex({ "authorId": 1, "publishedAt": -1 })

// Text index for search
db.posts.createIndex({ "title": "text", "content": "text" })