Identifying missing indexes in MongoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of indexes in MongoDB?

Indexes help MongoDB find data faster, like a book's table of contents helps you find chapters quickly.

intermediate

How can you identify missing indexes in MongoDB?

You can check the system.profile collection or use the db.currentOp() and explain() methods to find slow queries that might need indexes.

beginner

What does the explain() method show regarding indexes?

It shows how MongoDB executes a query, including whether it uses an index or scans the whole collection (which is slower).

beginner

What is a sign that a query might be missing an index?

If the query does a collection scan (scans all documents) instead of using an index, it means an index might be missing.

intermediate

How does MongoDB's profiler help in identifying missing indexes?

The profiler records slow queries and their details, helping you spot queries that could benefit from new indexes.

Which MongoDB command helps you see if a query uses an index?

A db.collection.explain()

B db.collection.find()

C db.collection.insert()

D db.collection.update()

The explain() method shows query execution details, including index usage.

What does a collection scan indicate in MongoDB?

A The query scans all documents without an index

B The query is invalid

C The database is empty

D The query uses an index

A collection scan means MongoDB reads all documents, which is slower and suggests a missing index.

Where can you find slow query logs in MongoDB?

A system.users collection

B system.profile collection

C system.indexes collection

D system.logs collection

The system.profile collection stores profiling data including slow queries.

Which tool helps identify queries that might benefit from new indexes?

A MongoDB compass

B MongoDB shell

C MongoDB profiler

D MongoDB backup

The profiler records slow queries, helping find candidates for indexing.

What is a common sign that an index is missing for a query?

A Query runs instantly

B Query returns no results

C Query uses an index

D Query performs a collection scan

A collection scan means no index is used, indicating a missing index.

Explain how you can find missing indexes in MongoDB using the profiler and explain() method.

Think about how slow queries and query plans reveal missing indexes.

Describe why missing indexes can slow down MongoDB queries and how to detect them.

Focus on the relationship between indexes, query speed, and detection methods.

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