Identifying missing indexes in MongoDB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to list all indexes on the 'users' collection.

MongoDB

db.users.[1]()

Drag options to blanks, or click blank then click option'

AlistIndexes

BfindIndexes

CshowIndexes

DgetIndexes

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'findIndexes' which does not exist.

Using 'showIndexes' which is not a valid method.

Using 'getIndexes' which is incorrect.

The listIndexes() method returns all indexes on a collection in MongoDB.

2fill in blank

medium

Complete the code to check the current index usage statistics for the 'orders' collection.

MongoDB

db.orders.[1]()

Drag options to blanks, or click blank then click option'

AgetIndexStats

BindexStats

CshowIndexStats

DlistIndexStats

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'getIndexStats' which is not a MongoDB method.

Using 'showIndexStats' which does not exist.

Using 'listIndexStats' which is invalid.

The indexStats() method returns statistics about index usage on a collection.

3fill in blank

hard

Complete the code to find slow queries that might need indexes in the 'products' collection.

MongoDB

db.[1]({ millis: { $gt: 100 } })

Drag options to blanks, or click blank then click option'

AgetProfilingStatus

Bsystem.profile.find()

Cprofile.find

Dsystem.profile.find

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'getProfilingStatus' which only returns profiling settings.

Using 'system.profile.find()' which is a method call, not a property.

Using 'profile.find' which is not a valid collection name.

To find slow queries, you query the system.profile collection with find(). The correct syntax is db.system.profile.find({ millis: { $gt: 100 } }). To filter specifically for the 'products' collection, include a condition like { ns: /products$/, millis: { $gt: 100 } } (adjust db name as needed). Here, the blank expects system.profile.find.

4fill in blank

hard

Fill both blanks to create an index on the 'email' field in the 'customers' collection to improve query speed.

MongoDB

db.customers.createIndex({ [1]: [2] })

Drag options to blanks, or click blank then click option'

Aemail

B1

C-1

Dusername

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'username' instead of 'email' as the field name.

Using -1 when ascending order is intended.

Swapping the field name and index order.

To create an ascending index on the 'email' field, use { email: 1 }. The field name is 'email' and the value 1 means ascending order.

5fill in blank

hard

Fill all three blanks to create a compound index on 'lastName' (ascending) and 'age' (descending) fields in the 'employees' collection.

MongoDB

db.employees.createIndex({ [1]: [2], [3]: -1 })

Drag options to blanks, or click blank then click option'

AlastName

B1

Cage

DfirstName

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'firstName' instead of 'lastName'.

Using -1 for the first field instead of 1.

Swapping the field names.

A compound index is created by specifying multiple fields. Here, 'lastName' is indexed ascending (1), and 'age' descending (-1).

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