Mongoose Advanced Patterns: Performance and Flexibility

// === Basic populate ===
const user = await User.findById(userId).populate('addresses');
// SELECT u.*, a.* FROM users u LEFT JOIN addresses a ON u._id = a.userId

// === Nested populate ===
const order = await Order.findById(orderId)
  .populate('userId')
  .populate({
    path: 'items.productId',
    select: 'sku title price'
  });

// === Conditions populate ===
const orders = await Order.find()
  .populate({
    path: 'userId',
    match: { isActive: true },
    select: 'username avatar'
  });

// === Basics User Model ===
const UserSchema = new mongoose.Schema({
  email: String,
  username: String,
  passwordHash: String
}, { discriminatorKey: 'role' });

const User = mongoose.model('User', UserSchema);

// === Customer Discriminator ===
const Customer = User.discriminator('Customer', new mongoose.Schema({
  loyaltyPoints: { type: Number, default: 0 },
  preferredCategories: [String]
}));

// === Admin Discriminator ===
const Admin = User.discriminator('Admin', new mongoose.Schema({
  permissions: [String],
  lastLoginAt: Date
}));

// === Create Different Roles ===
const customer = await Customer.create({
  email: 'alice@example.com',
  username: 'alice',
  passwordHash: '...',
  loyaltyPoints: 100,
  preferredCategories: ['Electronics']
});

const admin = await Admin.create({
  email: 'admin@example.com',
  username: 'admin',
  passwordHash: '...',
  permissions: ['manage_products']
});

// === When querying, based on role Category ===
const customers = await Customer.find();
const admins = await Admin.find();
// All data is in the same collection（users），Through discriminatorKey Category

// === General Inquiry：Back mongoose Document ===
const products = await Product.find();
// Each product is a Mongoose Document (with save() and other methods)

// === lean()：Return to Pure JS Object ===
const products = await Product.find().lean();
// Each product is a plain object, Performance up 3-5x

// === Comparison Test ===
console.time('without lean');
const a = await Product.find({ category: 'Electronics' }).limit(100);
console.timeEnd('without lean');  // ~150ms

console.time('with lean');
const b = await Product.find({ category: 'Electronics' }).lean().limit(100);
console.timeEnd('with lean');  // ~30ms

// === mongoose Using Aggregation in ===
const stats = await Product.aggregate([
  { $match: { isActive: true } },
  { $group: { _id: '$category', count: { $sum: 1 }, avgPrice: { $avg: '$price' } } },
  { $sort: { count: -1 } }
]);

// === aggregate + populate（mongoose 6+）===
const results = await Order.aggregate([
  { $match: { status: 'paid' } },
  {
    $lookup: {
      from: 'users',
      localField: 'userId',
      foreignField: '_id',
      as: 'customer'
    }
  },
  { $unwind: '$customer' }
]);

const ProductSchema = new mongoose.Schema({
  sku: { type: String, index: true, unique: true },
  title: { type: String, text: true },  // Text Index
  price: { type: Number, index: true },
  category: { type: String, index: true }
});

// === Composite Index ===
ProductSchema.index({ category: 1, price: -1 });

// === Selected Indexes ===
ProductSchema.index(
  { category: 1 },
  { partialFilterExpression: { isActive: true } }
);

// === TTL Index ===
ProductSchema.index(
  { createdAt: 1 },
  { expireAfterSeconds: 30 * 24 * 60 * 60 }
);

// === Optimization 1：Disable autoIndex（Production）===
mongoose.connect(uri, { autoIndex: false });
// Manually create indexes at startup：await Product.syncIndexes();

// === Optimization 2：Bulk Operations ===
await Product.bulkWrite([
  { updateOne: { filter: { sku: 'A' }, update: { $inc: { stock: -1 } } } },
  { updateOne: { filter: { sku: 'B' }, update: { $inc: { stock: -1 } } } }
]);

// === Optimization 3：Projection Reduces Data Transmission ===
const products = await Product.find()
  .select('sku title price')  // Search only 3 field
  .lean();

// === Optimization 4：Usage cursor Streaming Processing of Big Data ===
const cursor = Product.find().cursor();
for await (const doc of cursor) {
  // Process each document
}

// === Optimization 5：Bulk Insert ===
await Product.insertMany(docs, { ordered: false });

// === Optimized List API ===
app.get('/api/products', async (req, res) => {
  const { page = 1, limit = 20, category, search } = req.query;

  // 1. Build a Query
  const query = { isActive: true };
  if (category) query.category = category;
  if (search) query.$text = { $search: search };

  // 2. Parallel Queries（find + count）
  const [products, total] = await Promise.all([
    Product.find(query)
      .select('sku title price thumbnail rating')  // Projection
      .sort({ createdAt: -1 })
      .limit(+limit)
      .skip((page - 1) * limit)
      .lean(),  // Performance Optimization
    Product.countDocuments(query)
  ]);

  res.json({
    success: true,
    data: products,
    meta: { page: +page, limit: +limit, total, pages: Math.ceil(total / limit) }
  });
});

// === Scene：ShopHub Order Details API（3 Layer Association）===
const mongoose = require('mongoose');

// Schemas
const AddressSchema = new mongoose.Schema({ city: String, country: String, zipCode: String });
const UserSchema = new mongoose.Schema({
  email: String, username: String,
  addresses: [{ type: mongoose.Schema.Types.ObjectId, ref: 'Address' }]
});
const ProductSchema = new mongoose.Schema({ sku: String, title: String, price: Number, thumbnail: String });
const OrderSchema = new mongoose.Schema({
  orderNumber: String,
  userId: { type: mongoose.Schema.Types.ObjectId, ref: 'User' },
  items: [{ productId: { type: mongoose.Schema.Types.ObjectId, ref: 'Product' }, qty: Number, price: Number }],
  status: String
}, { timestamps: true });

const Address = mongoose.model('Address', AddressSchema);
const User = mongoose.model('User', UserSchema);
const Product = mongoose.model('Product', ProductSchema);
const Order = mongoose.model('Order', OrderSchema);

// 3-level populate + lean
const order = await Order.findById('647f1f77bcf86cd799439001')
  .populate({ path: 'userId', select: 'username email',
    populate: { path: 'addresses', select: 'city country' }
  })
  .populate({ path: 'items.productId', select: 'sku title price' })
  .lean();

console.log({
  orderNumber: order.orderNumber,
  customer: order.userId.username,
  city: order.userId.addresses[0]?.city,
  items: order.items.map(i => `${i.productId.title} x${i.qty}`)
});
// Output：{ orderNumber: 'ORD-001', customer: 'alice', city: 'San Francisco',
//         items: ['Smartphone X x2', 'Laptop Pro x1'] }

// === 1. populate Multi-level relationships ===
// Order + User + Products（3 Nested Layers）
const order = await Order.findById(orderId)
  .populate({
    path: 'userId',
    select: 'username email avatar',
    populate: { path: 'addresses', select: 'city country' }  // Address under the user
  })
  .populate({
    path: 'items.productId',
    select: 'sku title price thumbnail'
  })
  .lean();  // Performance Optimization

console.log('Order:', {
  orderNumber: order.orderNumber,
  customer: {
    username: order.userId.username,
    address: order.userId.addresses[0]?.city
  },
  items: order.items.map(i => ({
    product: i.productId.title,
    qty: i.qty,
    price: i.price
  }))
});

// === 2. discriminator Single Set, Multiple Schema ===
// User Base Class
const UserSchema = new mongoose.Schema({
  email: { type: String, required: true, unique: true },
  username: String,
  passwordHash: String,
  createdAt: { type: Date, default: Date.now }
}, { discriminatorKey: 'role' });

const User = mongoose.model('User', UserSchema);

// Customer Discriminator（Inheritance User + Extended Fields）
const Customer = User.discriminator('Customer', new mongoose.Schema({
  loyaltyPoints: { type: Number, default: 0 },
  preferredCategories: [String],
  totalSpent: mongoose.Schema.Types.Decimal128
}));

// Admin Discriminator
const Admin = User.discriminator('Admin', new mongoose.Schema({
  permissions: [String],
  lastLoginAt: Date
}));

// Create Different Roles（All exist users Gathering，Through role Field Delimiter）
const customer = await Customer.create({
  email: 'alice@example.com',
  username: 'alice',
  passwordHash: '...',
  loyaltyPoints: 100,
  preferredCategories: ['Electronics']
});

const admin = await Admin.create({
  email: 'admin@example.com',
  username: 'admin',
  passwordHash: '...',
  permissions: ['manage_products', 'manage_users']
});

// When querying, based on role Automatic Filtering
const customers = await Customer.find({ loyaltyPoints: { $gt: 50 } });
// Actual Query：{ role: 'Customer', loyaltyPoints: { $gt: 50 } }

// === 3. lean() Performance Optimization Comparison ===
console.time('without lean');
const a = await Product.find({ category: 'Electronics' }).limit(100);
console.timeEnd('without lean');  // ~150ms

console.time('with lean');
const b = await Product.find({ category: 'Electronics' }).lean().limit(100);
console.timeEnd('with lean');  // ~30ms（5x Performance Improvements）

// === 4. Model.aggregate() Database-Level Aggregation ===
const stats = await Product.aggregate([
  { $match: { isActive: true } },
  {
    $facet: {
      totalCount: [{ $count: 'count' }],
      byCategory: [
        { $group: { _id: '$category', count: { $sum: 1 }, avgPrice: { $avg: '$price' } } },
        { $sort: { count: -1 } }
      ],
      topRated: [
        { $sort: { rating: -1 } },
        { $limit: 5 },
        { $project: { sku: 1, title: 1, rating: 1 } }
      ]
    }
  }
]);

// Output：
// {
//   totalCount: [{ count: 1250 }],
//   byCategory: [
//     { _id: 'Electronics', count: 450, avgPrice: 599 },
//     { _id: 'Books', count: 380, avgPrice: 29 },
//     ...
//   ],
//   topRated: [
//     { sku: 'PHONE-001', title: 'Smartphone X', rating: 4.9 },
//     ...
//   ]
// }