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Master MongoDB index creation and types. Learn single-field, compound, unique, text, geospatial, and TTL indexes. Optimize query performance dramatically with proper indexing.
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| name | mongodb-index-creation |
| version | 2.1.0 |
| description | Master MongoDB index creation and types. Learn single-field, compound, unique, text, geospatial, and TTL indexes. Optimize query performance dramatically with proper indexing. |
| sasmp_version | 1.3.0 |
| bonded_agent | 04-mongodb-performance-indexing |
| bond_type | PRIMARY_BOND |
| capabilities | ["single-field-indexes","compound-indexes","unique-indexes","text-indexes","geospatial-indexes","ttl-indexes"] |
| input_validation | {"required_context":["collection_name","query_patterns"],"optional_context":["existing_indexes","write_frequency","collection_size"]} |
| output_format | {"index_definition":"object","creation_command":"string","impact_analysis":"object","maintenance_notes":"array"} |
| error_handling | {"common_errors":[{"code":"INDEX001","condition":"Duplicate index","recovery":"Check existing indexes, drop duplicate before creating"},{"code":"INDEX002","condition":"Background index build failed","recovery":"Check disk space, memory, restart build with background: true"},{"code":"INDEX003","condition":"Index too large for memory","recovery":"Consider partial index or remove low-value indexes"}]} |
| prerequisites | {"mongodb_version":"4.4+","required_knowledge":["query-patterns","esr-rule"],"performance_baseline":["Current query latencies documented"]} |
| testing | {"unit_test_template":"// Verify index created and used\nawait collection.createIndex({ field: 1 })\nconst indexes = await collection.indexes()\nexpect(indexes.some(i => i.key.field === 1)).toBe(true)\nconst explain = await collection.find({ field: value }).explain()\nexpect(explain.queryPlanner.winningPlan.inputStage.stage).toBe('IXSCAN')\n"} |
Dramatically improve query performance with strategic indexing.
// Single field index
await collection.createIndex({ email: 1 })
// Compound index (order matters!)
await collection.createIndex({ status: 1, createdAt: -1 })
// Unique index
await collection.createIndex({ email: 1 }, { unique: true })
// Sparse index (skip null values)
await collection.createIndex({ phone: 1 }, { sparse: true })
// TTL index (auto-delete after 24 hours)
await collection.createIndex({ createdAt: 1 }, { expireAfterSeconds: 86400 })
// Text index (full-text search)
await collection.createIndex({ title: 'text', content: 'text' })
// Geospatial index
await collection.createIndex({ location: '2dsphere' })
db..({ : })
// Multiple fields - ORDER MATTERS!
db.orders.createIndex({ status: 1, createdAt: -1 })
// Good for queries like:
// { status: 'completed', createdAt: {$gt: date} }
// { status: 'completed' } // Can use this index
// Bad for:
// { createdAt: {$gt: date} } // Won't use index well
// Ensure field uniqueness
db.users.createIndex({ email: 1 }, { unique: true })
// Prevents duplicates:
// - insertOne with duplicate email → ERROR
// - Can't insert if email already exists
// Sparse unique (allow multiple nulls)
db.users.createIndex({ phone: 1 }, { unique: true, sparse: true })
// Skip documents where field is null/missing
db.users.createIndex({ phone: 1 }, { sparse: true })
// Benefits:
// - Smaller index (excludes nulls)
// - Matches queries with { $exists: true }
// When to use:
// - Optional fields (not all documents have it)
// - Reduce index size
// Full-text search
db.articles.createIndex({
title: 'text',
content: 'text',
tags: 'text'
})
// Query:
db.articles.find({ $text: { $search: 'mongodb' } })
// Weights (title more important than content)
db.articles.createIndex({
title: 'text',
content: 'text'
}, { weights: { title: 10, content: 5 } })
// 2D spherical (lat/long)
db.venues.createIndex({ location: '2dsphere' })
// Query nearby
db.venues.find({
location: {
$near: {
type: 'Point',
coordinates: [-73.97, 40.77]
},
$maxDistance: 5000 // 5km
}
})
// Auto-delete documents after time period
db.sessions.createIndex({ createdAt: 1 }, {
expireAfterSeconds: 3600 // 1 hour
})
// Use cases:
// - Sessions that expire
// - Temporary logs
// - Cache-like collections
// MongoDB checks once per minute
// Deletion might lag up to 1 minute
// Show all indexes
const indexes = await collection.indexes()
console.log(indexes)
// Shows: name, key, size, doc count
// Drop specific index
await collection.dropIndex('email_1')
// Drop all non-_id indexes
await collection.dropIndexes()
await collection.createIndex({ email: 1 }, {
unique: true, // Enforce uniqueness
sparse: true, // Skip nulls
background: true, // Don't block writes
expireAfterSeconds: 86400, // TTL
collation: { locale: 'en' }, // Language-specific
name: 'custom_name' // Custom index name
})
Equality, Sort, Range - optimal compound index order
// Query: Find active users sorted by created date, age 18-65
db.users.find({
status: 'active', // Equality
age: { $gte: 18, $lte: 65 } // Range
}).sort({ createdAt: -1 }) // Sort
// Optimal index:
db.users.createIndex({
status: 1, // Equality first
createdAt: -1, // Sort second
age: 1 // Range last
})
// Query returns entirely from index, no documents fetched!
// Create index with all needed fields
db.users.createIndex({ email: 1, name: 1, age: 1 })
// Query (covered - no docs fetched)
db.users.find(
{ email: 'user@example.com' },
{ projection: { email: 1, name: 1, age: 1, _id: 0 } }
)
// Much faster than fetching documents!
// MongoDB 4.4+
db.collection.aggregate([
{ $indexStats: {} }
])
// Shows:
// - accesses.ops: Number of operations using index
// - accesses.since: When index was created
// Identify unused:
// - Low accesses.ops value
// - Recent accesses.since date
// Drop unused indexes:
await collection.dropIndex('unused_index_name')
✅ Index Design:
✅ Performance:
❌ Avoid:
Ready to speed up your MongoDB! ⚡