MongoDB Performance

// Get execution stats for a query
db.users.find({ email: "alice@example.com" }).explain("executionStats")

// Key metrics to check:
// stage: "IXSCAN" = index used (good), "COLLSCAN" = full scan (bad)
// totalDocsExamined: should equal nReturned for efficient queries
// executionTimeMillis: total query time

// COVERED QUERY — all fields in query and projection are in the index
// No document fetch needed — fastest possible query
db.users.createIndex({ email: 1, name: 1, role: 1 })

// This query is "covered" — all fields are in the index
db.users.find(
  { email: "alice@example.com" },
  { name: 1, role: 1, _id: 0 }   // _id: 0 is required for covered query
).explain("executionStats")
// stage: "PROJECTION_COVERED" — no FETCH stage needed

// Use projection to limit returned fields (reduces network transfer)
db.users.find({ active: true }, { name: 1, email: 1, _id: 0 })

// Profiling levels:
// 0 = off (default)
// 1 = log only slow operations (above slowms threshold)
// 2 = log all operations

// Enable profiling for operations slower than 100ms
db.setProfilingLevel(1, { slowms: 100 })

// Enable profiling for all operations
db.setProfilingLevel(2)

// Check current profiling level
db.getProfilingStatus()

// Query the system.profile collection for slow queries
db.system.profile.find().sort({ ts: -1 }).limit(10).pretty()

// Find the slowest queries
db.system.profile.find(
  { millis: { $gt: 100 } },
  { op: 1, ns: 1, millis: 1, query: 1, ts: 1 }
).sort({ millis: -1 }).limit(5)

// Disable profiling
db.setProfilingLevel(0)

// bulkWrite() — batch multiple operations in a single round trip
db.products.bulkWrite([
  { insertOne: { document: { sku: "NEW-001", name: "Widget", price: 9.99, stock: 100 } } },
  { updateOne: {
      filter: { sku: "LAPTOP-001" },
      update: { $inc: { stock: -1 }, $set: { updatedAt: new Date() } }
  }},
  { updateMany: {
      filter: { price: { $lt: 5 } },
      update: { $set: { clearance: true } }
  }},
  { deleteOne: { filter: { sku: "OLD-999" } } }
], { ordered: false })  // ordered: false = continue on error, faster

// Connection pool settings (in connection string or MongoClient options)
const client = new MongoClient(uri, {
  maxPoolSize: 50,       // max connections in pool (default: 100)
  minPoolSize: 5,        // min connections to maintain
  maxIdleTimeMS: 30000,  // close idle connections after 30s
  waitQueueTimeoutMS: 5000  // timeout waiting for a connection
})

// Check WiredTiger cache statistics
db.serverStatus().wiredTiger.cache

// Key cache metrics:
// "bytes currently in the cache" — current cache usage
// "maximum bytes configured"     — cache size limit
// "pages read into cache"        — disk reads (want this low)
// "unmodified pages evicted"     — pages evicted from cache

// Configure WiredTiger cache size in mongod.conf
// storage:
//   wiredTiger:
//     engineConfig:
//       cacheSizeGB: 4   // set to ~50% of available RAM

// Performance checklist:
// 1. Create indexes for all frequently queried fields
// 2. Use compound indexes that match your query patterns
// 3. Use projection to return only needed fields
// 4. Avoid $where (uses JavaScript, very slow)
// 5. Use $regex with anchors (^pattern) to leverage indexes
// 6. Avoid negation operators ($ne, $nin, $not) on large collections
// 7. Use bulkWrite() for batch operations
// 8. Keep working set (hot data) in RAM
// 9. Use SSDs for storage
// 10. Monitor with db.currentOp() for long-running operations

// Kill a long-running operation
db.currentOp()
db.killOp(opId)