Identifying missing indexes in MongoDB

Introduction

Indexes help MongoDB find data faster. Identifying missing indexes shows where queries can be improved to run quicker.

When queries on a collection are slow and you want to speed them up.

When you notice high CPU or disk usage during database operations.

When MongoDB suggests creating indexes in its logs or profiler.

When you want to optimize reports or dashboards that take too long to load.

Syntax

MongoDB

db.collection.getIndexes()
db.collection.find().explain('queryPlanner')
use system.profile collection to check slow queries

Use db.collection.getIndexes() to see existing indexes on a collection.

Use explain() on queries to see if indexes are used or missing.

Examples

Shows all indexes on the 'orders' collection.

MongoDB

db.orders.getIndexes()

Shows how MongoDB runs this query and if it uses an index.

MongoDB

db.orders.find({customerId: 123}).explain('executionStats')

Finds recent slow queries taking more than 100 milliseconds.

MongoDB

db.system.profile.find({millis: {$gt: 100}}).sort({ts: -1}).limit(5)

Sample Program

This script checks current indexes, explains a query to see if it uses an index, and lists recent slow queries to identify missing indexes.

MongoDB

use shopDB

// Check existing indexes on products collection
printjson(db.products.getIndexes())

// Run a query and explain to see if index is used
var explainResult = db.products.find({category: 'books'}).explain('executionStats')
printjson(explainResult.queryPlanner)

// Check slow queries from profiler
var slowQueries = db.system.profile.find({millis: {$gt: 50}}).sort({ts: -1}).limit(3).toArray()
printjson(slowQueries)

Important Notes

If a query uses COLLSCAN (collection scan), it means no index was used and performance can be slow.

The system.profile collection stores recent slow queries if profiling is enabled.

Creating indexes on fields used in queries can greatly improve speed.

Summary

Indexes help MongoDB find data faster and reduce query time.

Use getIndexes() and explain() to check if indexes exist and are used.

Look at slow queries in system.profile to find where indexes are missing.

Practice

1. What is the main reason to create indexes in MongoDB collections?

easy

A. To store more data in the database

B. To make queries run faster by helping MongoDB find data quickly

C. To backup the database automatically

D. To encrypt the data for security

Solution

1. Step 1: Understand the purpose of indexes

   Indexes are special data structures that help MongoDB quickly locate data without scanning the entire collection.

2. Step 2: Compare options with index purpose

   Only To make queries run faster by helping MongoDB find data quickly correctly states that indexes speed up queries by helping find data faster.

3. Final Answer:

   To make queries run faster by helping MongoDB find data quickly -> Option B

4. Quick Check:

   Indexes improve query speed = A [OK]

Hint: Indexes speed up data search, not storage or security [OK]

Common Mistakes:

• Thinking indexes store more data
• Confusing indexes with backups
• Assuming indexes encrypt data

2. Which MongoDB command lists all indexes on a collection named users?

easy

A. db.users.showIndexes()

B. db.users.getIndex()

C. db.users.findIndexes()

D. db.users.listIndexes()

Solution

1. Step 1: Recall the correct method to list indexes

   The correct MongoDB method to list indexes on a collection is listIndexes().

2. Step 2: Check each option's validity

   Only db.users.listIndexes() is a valid MongoDB command; others are incorrect or do not exist.

3. Final Answer:

   db.users.listIndexes() -> Option D

4. Quick Check:

   List indexes command = listIndexes() [OK]

Hint: Use listIndexes() to see all indexes on a collection [OK]

Common Mistakes:

• Using getIndex() which is not a MongoDB method
• Trying findIndexes() which does not exist
• Confusing showIndexes() with listIndexes()

3. Given the query db.orders.find({ customerId: 123 }) and the collection has no index on customerId, what will explain('executionStats') likely show?

medium

A. A COLLSCAN (collection scan) with high number of documents examined

B. An IXSCAN (index scan) using the customerId index

C. A syntax error because explain cannot be used here

D. No documents returned because no index exists

Solution

1. Step 1: Understand query behavior without index

   Without an index on customerId, MongoDB must scan the entire collection (COLLSCAN) to find matching documents.

2. Step 2: Interpret explain output

   The explain('executionStats') will show a COLLSCAN and a high number of documents examined, indicating no index was used.

3. Final Answer:

   A COLLSCAN (collection scan) with high number of documents examined -> Option A

4. Quick Check:

   No index means COLLSCAN = B [OK]

Hint: No index means full collection scan in explain output [OK]

Common Mistakes:

• Expecting an index scan without an index
• Thinking explain causes syntax error
• Assuming no documents returned without index

4. You notice a slow query on db.products.find({ category: 'books', price: { $lt: 20 } }). The collection has an index only on category. What is the best fix?

medium

A. Rewrite the query to remove the price filter

B. Remove the existing index on category

C. Add a compound index on { category: 1, price: 1 }

D. Add an index only on price

Solution

1. Step 1: Analyze existing index and query filters

   The query filters on both category and price, but only category is indexed, so the price filter is not optimized.

2. Step 2: Choose the best index to optimize query

   A compound index on { category: 1, price: 1 } allows MongoDB to efficiently filter by both fields, speeding up the query.

3. Final Answer:

   Add a compound index on { category: 1, price: 1 } -> Option C

4. Quick Check:

   Compound index matches query fields = D [OK]

Hint: Use compound indexes for queries filtering multiple fields [OK]

Common Mistakes:

• Removing useful indexes
• Adding index on only one field when query filters multiple
• Changing query to remove filters instead of indexing

5. A MongoDB collection logs has slow queries filtering by userId and sorting by timestamp. Which index best improves performance?

hard

A. A compound index on { userId: 1, timestamp: -1 }

B. An index on { timestamp: 1 }

C. An index on { userId: 1 }

D. No index needed; increase RAM instead

Solution

1. Step 1: Understand query pattern with filter and sort

   The query filters by userId and sorts by timestamp, so both fields affect performance.

2. Step 2: Select index that supports filter and sort

   A compound index on { userId: 1, timestamp: -1 } supports efficient filtering by userId and sorting by timestamp in descending order.

3. Final Answer:

   A compound index on { userId: 1, timestamp: -1 } -> Option A

4. Quick Check:

   Compound index matches filter and sort = C [OK]

Hint: Compound index with sort field improves filter + sort queries [OK]

Common Mistakes:

• Using single-field index ignoring sort
• Choosing wrong sort order in index
• Ignoring indexing and blaming hardware