// Find documents
db.collection.find({ status: "active" })
db.collection.findOne({ _id: ObjectId("...") })

// Query operators
db.users.find({ age: { $gte: 18, $lt: 65 } })
db.posts.find({ tags: { $in: ["mongodb", "database"] } })
db.products.find({ price: { $exists: true } })

// Projection (select specific fields)
db.users.find({ status: "active" }, { name: 1, email: 1 })

// Cursor operations
db.collection.find().sort({ createdAt: -1 }).limit(10).skip(20)

// Insert
db.collection.insertOne({ name: "Alice", age: 30 })
db.collection.insertMany([{ name: "Bob" }, { name: "Charlie" }])

// Update
db.users.updateOne(
  { _id: userId },
  { $set: { status: "verified" } }
)
db.users.updateMany(
  { lastLogin: { $lt: cutoffDate } },
  { $set: { status: "inactive" } }
)

// Replace entire document
db.users.replaceOne({ _id: userId }, newUserDoc)

// Delete
db.users.deleteOne({ _id: userId })
db.users.deleteMany({ status: "deleted" })

// Upsert (update or insert if not exists)
db.users.updateOne(
  { email: "user@example.com" },
  { $set: { name: "User", lastSeen: new Date() } },
  { upsert: true }
)

// Increment counter
db.posts.updateOne(
  { _id: postId },
  { $inc: { views: 1 } }
)

// Add to array (if not exists)
db.users.updateOne(
  { _id: userId },
  { $addToSet: { interests: "mongodb" } }
)

// Push to array
db.posts.updateOne(
  { _id: postId },
  { $push: { comments: { author: "Alice", text: "Great!" } } }
)

// Find and modify atomically
db.counters.findAndModify({
  query: { _id: "sequence" },
  update: { $inc: { value: 1 } },
  new: true,
  upsert: true
})

$eq, $ne, $gt, $gte, $lt, $lte
$in, $nin

$and, $or, $not, $nor

// Example
db.products.find({
  $and: [
    { price: { $gte: 100 } },
    { stock: { $gt: 0 } }
  ]
})

$all, $elemMatch, $size
$firstN, $lastN, $maxN, $minN

// Example: Find docs with all tags
db.posts.find({ tags: { $all: ["mongodb", "database"] } })

// Match array element with multiple conditions
db.products.find({
  reviews: {
    $elemMatch: { rating: { $gte: 4 }, verified: true }
  }
})

$exists, $type

// Find documents with optional field
db.users.find({ phoneNumber: { $exists: true } })

// Type checking
db.data.find({ value: { $type: "string" } })

db.orders.aggregate([
  // Stage 1: Filter documents
  { $match: { status: "completed", total: { $gte: 100 } } },

  // Stage 2: Join with customers
  { $lookup: {
    from: "customers",
    localField: "customerId",
    foreignField: "_id",
    as: "customer"
  }},

  // Stage 3: Unwind array
  { $unwind: "$items" },

  // Stage 4: Group and aggregate
  { $group: {
    _id: "$items.category",
    totalRevenue: { $sum: "$items.total" },
    orderCount: { $sum: 1 },
    avgOrderValue: { $avg: "$total" }
  }},

  // Stage 5: Sort results
  { $sort: { totalRevenue: -1 } },

  // Stage 6: Limit results
  { $limit: 10 },

  // Stage 7: Reshape output
  { $project: {
    category: "$_id",
    revenue: "$totalRevenue",
    orders: "$orderCount",
    avgValue: { $round: ["$avgOrderValue", 2] },
    _id: 0
  }}
])

db.events.aggregate([
  { $match: { timestamp: { $gte: startDate, $lt: endDate } } },
  { $group: {
    _id: {
      year: { $year: "$timestamp" },
      month: { $month: "$timestamp" },
      day: { $dayOfMonth: "$timestamp" }
    },
    count: { $sum: 1 }
  }}
])

db.products.aggregate([
  { $match: { category: "electronics" } },
  { $facet: {
    priceRanges: [
      { $bucket: {
        groupBy: "$price",
        boundaries: [0, 100, 500, 1000, 5000],
        default: "5000+",
        output: { count: { $sum: 1 } }
      }}
    ],
    topBrands: [
      { $group: { _id: "$brand", count: { $sum: 1 } } },
      { $sort: { count: -1 } },
      { $limit: 5 }
    ],
    avgPrice: [
      { $group: { _id: null, avg: { $avg: "$price" } } }
    ]
  }}
])

db.sales.aggregate([
  { $setWindowFields: {
    partitionBy: "$region",
    sortBy: { date: 1 },
    output: {
      runningTotal: { $sum: "$amount", window: { documents: ["unbounded", "current"] } },
      movingAvg: { $avg: "$amount", window: { documents: [-7, 0] } }
    }
  }}
])

$add, $subtract, $multiply, $divide, $mod
$abs, $ceil, $floor, $round, $sqrt, $pow
$log, $log10, $ln, $exp

$concat, $substr, $toLower, $toUpper
$trim, $ltrim, $rtrim, $split
$regexMatch, $regexFind, $regexFindAll

$arrayElemAt, $slice, $first, $last, $reverse
$sortArray, $filter, $map, $reduce
$zip, $concatArrays

$dateAdd, $dateDiff, $dateFromString, $dateToString
$dayOfMonth, $month, $year, $dayOfWeek
$week, $hour, $minute, $second

$toInt, $toString, $toDate, $toDouble
$toDecimal, $toObjectId, $toBool

db.users.createIndex({ email: 1 })  // ascending
db.posts.createIndex({ createdAt: -1 })  // descending

// Order matters! Index on { status: 1, createdAt: -1 }
db.orders.createIndex({ status: 1, createdAt: -1 })

// Supports queries on:
// - { status: "..." }
// - { status: "...", createdAt: ... }
// Does NOT efficiently support: { createdAt: ... } alone

db.articles.createIndex({ title: "text", body: "text" })

// Search
db.articles.find({ $text: { $search: "mongodb database" } })

// With relevance score
db.articles.find(
  { $text: { $search: "mongodb" } },
  { score: { $meta: "textScore" } }
).sort({ score: { $meta: "textScore" } })

// 2dsphere for earth-like geometry
db.places.createIndex({ location: "2dsphere" })

// Find nearby
db.places.find({
  location: {
    $near: {
      $geometry: { type: "Point", coordinates: [lon, lat] },
      $maxDistance: 5000  // meters
    }
  }
})

// Index all fields in subdocuments
db.products.createIndex({ "attributes.$**": 1 })

// Supports queries on any field under attributes
db.products.find({ "attributes.color": "red" })

// Index only documents matching filter
db.orders.createIndex(
  { customerId: 1 },
  { partialFilterExpression: { status: "active" } }
)

// Delete documents 24 hours after createdAt
db.sessions.createIndex(
  { createdAt: 1 },
  { expireAfterSeconds: 86400 }
)

db.users.createIndex({ userId: "hashed" })

// Basic explain
db.users.find({ email: "user@example.com" }).explain()

// Execution stats (shows actual performance)
db.users.find({ age: { $gte: 18 } }).explain("executionStats")

// Key metrics to check:
// - executionTimeMillis
// - totalDocsExamined vs. nReturned (should be close)
// - stage: "IXSCAN" (using index) vs. "COLLSCAN" (full scan - BAD)

// Create index
db.users.createIndex({ email: 1, name: 1 })

// Query covered by index (no document fetch needed)
db.users.find(
  { email: "user@example.com" },
  { email: 1, name: 1, _id: 0 }  // project only indexed fields
)

// Force specific index
db.users.find({ status: "active", city: "NYC" })
  .hint({ status: 1, createdAt: -1 })

// List all indexes
db.collection.getIndexes()

// Drop index
db.collection.dropIndex("indexName")

// Hide index (test before dropping)
db.collection.hideIndex("indexName")
db.collection.unhideIndex("indexName")

// Index stats
db.collection.aggregate([{ $indexStats: {} }])

// User with single address
{
  _id: ObjectId("..."),
  name: "Alice",
  email: "alice@example.com",
  address: {
    street: "123 Main St",
    city: "NYC",
    zipcode: "10001"
  }
}

// Blog post with comments (< 100 comments)
{
  _id: ObjectId("..."),
  title: "MongoDB Guide",
  comments: [
    { author: "Bob", text: "Great post!", date: ISODate("...") },
    { author: "Charlie", text: "Thanks!", date: ISODate("...") }
  ]
}

// Author collection
{ _id: ObjectId("author1"), name: "Alice" }

// Books collection (many books per author)
{ _id: ObjectId("book1"), title: "Book 1", authorId: ObjectId("author1") }
{ _id: ObjectId("book2"), title: "Book 2", authorId: ObjectId("author1") }

// Users collection
{
  _id: ObjectId("user1"),
  name: "Alice",
  groupIds: [ObjectId("group1"), ObjectId("group2")]
}

// Groups collection
{
  _id: ObjectId("group1"),
  name: "MongoDB Users",
  memberIds: [ObjectId("user1"), ObjectId("user2")]
}

// High-frequency sensor data
{
  _id: ObjectId("..."),
  sensorId: "sensor-123",
  timestamp: ISODate("2025-01-01T00:00:00Z"),
  readings: [
    { time: 0, temp: 23.5, humidity: 45 },
    { time: 60, temp: 23.6, humidity: 46 },
    { time: 120, temp: 23.4, humidity: 45 }
  ]
}

// Create time series collection
db.createCollection("sensor_data", {
  timeseries: {
    timeField: "timestamp",
    metaField: "sensorId",
    granularity: "minutes"
  }
})

// User document with pre-computed stats
{
  _id: ObjectId("..."),
  username: "alice",
  stats: {
    postCount: 150,
    followerCount: 2500,
    lastUpdated: ISODate("...")
  }
}

// Update stats periodically or with triggers

// Support schema evolution
{
  _id: ObjectId("..."),
  schemaVersion: 2,
  // v2 fields
  name: { first: "Alice", last: "Smith" },
  // Migration code handles v1 format
}

db.createCollection("users", {
  validator: {
    $jsonSchema: {
      bsonType: "object",
      required: ["email", "name"],
      properties: {
        email: {
          bsonType: "string",
          pattern: "^.+@.+$",
          description: "must be a valid email"
        },
        age: {
          bsonType: "int",
          minimum: 0,
          maximum: 120
        },
        status: {
          enum: ["active", "inactive", "pending"]
        }
      }
    }
  },
  validationLevel: "strict",  // or "moderate"
  validationAction: "error"   // or "warn"
})

rs.initiate({
  _id: "myReplicaSet",
  members: [
    { _id: 0, host: "mongo1:27017" },
    { _id: 1, host: "mongo2:27017" },
    { _id: 2, host: "mongo3:27017" }
  ]
})

// Check status
rs.status()

// Add member
rs.add("mongo4:27017")

// Remove member
rs.remove("mongo4:27017")

// Wait for majority acknowledgment (durable)
db.users.insertOne(
  { name: "Alice" },
  { writeConcern: { w: "majority", wtimeout: 5000 } }
)

// Common levels:
// w: 1 - primary acknowledges (default)
// w: "majority" - majority of nodes acknowledge (recommended for production)
// w: <number> - specific number of nodes
// w: 0 - no acknowledgment (fire and forget)

// Options:
// - primary (default): read from primary only
// - primaryPreferred: primary if available, else secondary
// - secondary: read from secondary only
// - secondaryPreferred: secondary if available, else primary
// - nearest: lowest network latency

db.collection.find().readPref("secondaryPreferred")