// Insert document
db.users.insertOne({
  email: "john@example.com",
  name: "John Doe",
  profile: { age: 30, city: "NYC" },
  tags: ["developer", "nodejs"],
  createdAt: new Date(),
});

// Query with projection
db.users.find({ "profile.city": "NYC" }, { name: 1, email: 1 });

db.orders.aggregate([
  {
    $match: { status: "completed", createdAt: { $gte: ISODate("2024-01-01") } },
  },
  {
    $group: {
      _id: "$customerId",
      totalAmount: { $sum: "$amount" },
      orderCount: { $count: {} },
      avgOrder: { $avg: "$amount" },
    },
  },
  {
    $lookup: {
      from: "customers",
      localField: "_id",
      foreignField: "_id",
      as: "customer",
    },
  },
  { $unwind: "$customer" },
  {
    $project: {
      customerName: "$customer.name",
      totalAmount: 1,
      orderCount: 1,
    },
  },
  { $sort: { totalAmount: -1 } },
  { $limit: 10 },
]);

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

// Compound index
db.orders.createIndex({ customerId: 1, createdAt: -1 });

// Text index for search
db.products.createIndex({ name: "text", description: "text" });

// TTL index for auto-expiry
db.sessions.createIndex({ createdAt: 1 }, { expireAfterSeconds: 3600 });

// Embedding for 1:few
{
  _id: ObjectId("..."),
  name: "John",
  addresses: [
    { type: "home", city: "NYC" },
    { type: "work", city: "Boston" }
  ]
}

// References for 1:many
{
  _id: ObjectId("..."),
  name: "John",
  orderIds: [ObjectId("..."), ObjectId("...")]
}

// Bucket pattern for time-series
{
  sensorId: "temp-001",
  date: ISODate("2024-01-15"),
  readings: [
    { time: ISODate("..."), value: 22.5 },
    { time: ISODate("..."), value: 23.1 }
  ]
}