MongoDB

// MongoDB document structure
{
  "_id": ObjectId("64abc123"),
  "name": "Sufi Sulaiman",
  "email": "sufi@example.com",
  "role": "admin",
  "tags": ["engineer", "ai"],
  "address": {
    "city": "Toronto",
    "country": "Canada"
  },
  "orders": [
    { "id": "ord1", "total": 99.99, "date": ISODate("2024-01-15") }
  ],
  "createdAt": ISODate("2024-01-01T00:00:00Z")
}

// CRUD operations
const db = client.db('myapp');
const users = db.collection('users');

// Insert await users.insertOne({ name: "Alice", email: "alice@example.com" }); await users.insertMany([{ name: "Bob" }, { name: "Charlie" }]);

// Find await users.find({ role: "admin" }).sort({ createdAt: -1 }).limit(10).toArray(); await users.findOne({ email: "alice@example.com" });

// Update (no replace by default with $set) await users.updateOne({ _id: id }, { $set: { role: "admin" }, $push: { tags: "vip" } }); await users.updateMany({ role: "user" }, { $set: { active: true } });

// Delete await users.deleteOne({ _id: id }); await users.deleteMany({ active: false, createdAt: { $lt: cutoff } }); ```

// Query operators
await users.find({
  age: { $gte: 18, $lt: 65 },
  tags: { $in: ["vip", "premium"] },
  "address.city": "Toronto",
  name: { $regex: /^sufi/i },
  deletedAt: { $exists: false },
}).toArray();

// Aggregation pipeline await orders.aggregate([ { $match: { status: "completed", createdAt: { $gte: startDate } } }, { $group: { _id: "$userId", totalSpent: { $sum: "$total" }, orderCount: { $sum: 1 }, avgOrderValue: { $avg: "$total" } }}, { $sort: { totalSpent: -1 } }, { $limit: 10 }, { $lookup: { // join with users collection from: "users", localField: "_id", foreignField: "_id", as: "user" }}, { $unwind: "$user" }, { $project: { name: "$user.name", totalSpent: 1, orderCount: 1 } } ]).toArray(); ```

// Single field index
await users.createIndex({ email: 1 }, { unique: true });

// Compound index (order matters leftmost prefix rule) await orders.createIndex({ userId: 1, createdAt: -1 });

// Partial index (only index matching documents) await users.createIndex({ email: 1 }, { partialFilterExpression: { active: true } });

// Text index for full-text search await products.createIndex({ name: "text", description: "text" }); await products.find({ $text: { $search: "wireless keyboard" } });

// Explain query plan await users.find({ email: "test@example.com" }).explain("executionStats");

// Mongoose schema with indexes const orderSchema = new mongoose.Schema({ userId: { type: ObjectId, ref: 'User', index: true }, status: { type: String, enum: ['pending','paid','shipped','delivered'] }, total: { type: Number, required: true }, createdAt: { type: Date, default: Date.now } }); orderSchema.index({ userId: 1, createdAt: -1 }); ```

// ── Embedded vs Referenced ────────────────────────────
// EMBED when: data is accessed together, child count is bounded
// REFERENCE when: data is large, accessed independently, unbounded

// Embedded (Blog post + comments) { _id: ObjectId("..."), title: "MongoDB Patterns", content: "...", comments: [ // embed accessed together, bounded { author: "Alice", text: "Great post!", date: ISODate("2024-01-15") }, { author: "Bob", text: "Very helpful!", date: ISODate("2024-01-16") } ] }

// Referenced (User + Orders orders are large and numerous) // users collection { _id: ObjectId("user1"), name: "Alice", email: "alice@example.com" }

// orders collection { _id: ObjectId("..."), userId: ObjectId("user1"), // reference total: 99.99, items: [{ sku: "abc", qty: 2, price: 49.99 }] }

// ── Bucket Pattern (time-series data) ───────────────── // Instead of one document per measurement → bucket by hour { sensor_id: "temp-01", hour: ISODate("2024-01-15T14:00:00Z"), // bucket key measurements: [ { minute: 0, value: 22.1 }, { minute: 1, value: 22.2 }, // ... 60 measurements ], nMeasurements: 60, minTemp: 21.8, maxTemp: 23.1 }

// ── Aggregation Pipeline ────────────────────────────── db.orders.aggregate([ { $match: { status: "completed", createdAt: { $gte: startDate } } }, { $unwind: "$items" }, { $group: { _id: "$items.sku", totalSold: { $sum: "$items.qty" }, totalRev: { $sum: { $multiply: ["$items.qty", "$items.price"] } } }}, { $sort: { totalRev: -1 } }, { $limit: 10 }, { $lookup: { from: "products", localField: "_id", foreignField: "sku", as: "product" }}, { $unwind: "$product" }, { $project: { _id: 0, name: "$product.name", totalSold: 1, totalRev: 1 }} ]); ```