Why indexes are critical for performance in MongoDB - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create an index on the 'name' field in MongoDB.

MongoDB

db.collection.createIndex({ name: [1] })

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

A1

Bfalse

Ctrue

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using -1 instead of 1 for ascending index.

Using true or false which are invalid values here.

In MongoDB, creating an index on a field uses 1 for ascending order.

2fill in blank

medium

Complete the query to find documents where 'age' is greater than 30 using an index.

MongoDB

db.collection.find({ age: { [1]: 30 } })

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

A$lt

B$gt

C$eq

D$ne

Attempts:

3 left

💡 Hint

Common Mistakes

Using $lt which means less than.

Using $eq which means equals.

The operator $gt means 'greater than' in MongoDB queries.

3fill in blank

hard

Fix the error in the index creation code to ensure it creates a compound index on 'age' ascending and 'score' descending.

MongoDB

db.collection.createIndex({ age: [1], score: [2] })

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

A1

Btrue

C-1

Dfalse

Attempts:

3 left

💡 Hint

Common Mistakes

Using true or false instead of 1 or -1.

Using the same order for both fields.

Compound indexes use 1 for ascending and -1 for descending order.

4fill in blank

hard

Fill both blanks to write a query that uses an index to find documents where 'status' is 'active' and 'points' are at least 50.

MongoDB

db.collection.find({ status: [1], points: { [2]: 50 } })

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

A"active"

B$gte

C$lte

D"inactive"

Attempts:

3 left

💡 Hint

Common Mistakes

Using $lte instead of $gte for points.

Using 'inactive' instead of 'active' for status.

The status must be 'active' (a string) and points greater than or equal to 50 uses $gte.

5fill in blank

hard

Fill all three blanks to create a text index on 'title' and 'description' fields and then query documents matching 'mongodb'.

MongoDB

db.collection.createIndex({ [1]: "text", [2]: "text" })
db.collection.find({ $text: { $search: [3] } })

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

Atitle

Bdescription

C"mongodb"

D"database"

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong field names for the index.

Not quoting the search string.

Text indexes are created on fields like 'title' and 'description'. The search term must be a string like "mongodb".

Practice

1. Why are indexes important in MongoDB for query performance?

easy

A. They speed up data retrieval by avoiding scanning the entire collection.

B. They increase the storage size without any performance benefit.

C. They automatically backup the database.

D. They encrypt the data for security.

Solution

1. Step 1: Understand what happens without indexes

   Without indexes, MongoDB must scan every document in the collection to find matches, which is slow.

2. Step 2: Role of indexes in query speed

   Indexes allow MongoDB to quickly locate documents by using a data structure, avoiding full scans.

3. Final Answer:

   They speed up data retrieval by avoiding scanning the entire collection. -> Option A

4. Quick Check:

   Indexes improve query speed = C [OK]

Hint: Indexes avoid full scans, making queries faster [OK]

Common Mistakes:

• Thinking indexes backup data
• Believing indexes encrypt data
• Assuming indexes only increase storage without benefit

2. Which of the following is the correct way to create an index on the field username in MongoDB?

easy

A. db.collection.addIndex({username: true})

B. db.collection.createIndex('username')

C. db.collection.index({username: 'asc'})

D. db.collection.createIndex({username: 1})

Solution

1. Step 1: Recall MongoDB index creation syntax

   The correct method is createIndex with a document specifying field and order (1 for ascending).

2. Step 2: Check each option

   db.collection.createIndex({username: 1}) uses correct syntax: createIndex({username: 1}). Others are invalid or incorrect method names.

3. Final Answer:

   db.collection.createIndex({username: 1}) -> Option D

4. Quick Check:

   Correct index syntax = A [OK]

Hint: Use createIndex with field: 1 or -1 for ascending/descending [OK]

Common Mistakes:

• Using wrong method names like addIndex
• Passing field name as string instead of object
• Using incorrect field order values

3. Given a collection users with an index on email, what will be the output of the following explain query?

db.users.find({email: '[e-mail]'}).explain('executionStats')

Which statement is true about the executionStats output?

medium

A. The query will show a COLLSCAN stage indicating a full collection scan.

B. The query will show an IXSCAN stage indicating an index scan on email.

C. The query will fail because explain cannot be used with find.

D. The query will show no stages because indexes are ignored.

Solution

1. Step 1: Understand explain with executionStats

   Explain with 'executionStats' shows how MongoDB executes the query, including index usage.

2. Step 2: Effect of index on email field

   Since there is an index on email, MongoDB uses an index scan (IXSCAN) instead of a full collection scan (COLLSCAN).

3. Final Answer:

   The query will show an IXSCAN stage indicating an index scan on email. -> Option B

4. Quick Check:

   Index present means IXSCAN used = D [OK]

Hint: Explain shows IXSCAN if index used, COLLSCAN if not [OK]

Common Mistakes:

• Confusing COLLSCAN with IXSCAN
• Thinking explain causes query failure
• Assuming indexes are ignored in explain

4. You created an index on age field but your queries still perform full collection scans. What is the most likely reason?

medium

A. MongoDB does not support indexes on numeric fields.

B. Indexes slow down queries intentionally.

C. The index was created with the wrong field name or syntax error.

D. You must restart MongoDB to activate indexes.

Solution

1. Step 1: Check index creation correctness

   If the index was created with a wrong field name or syntax error, it won't be used by queries.

2. Step 2: Eliminate other options

   MongoDB supports numeric indexes, does not require restart, and indexes speed up queries, not slow them.

3. Final Answer:

   The index was created with the wrong field name or syntax error. -> Option C

4. Quick Check:

   Incorrect index creation causes no index use = B [OK]

Hint: Check index field names and syntax if queries ignore indexes [OK]

Common Mistakes:

• Believing MongoDB needs restart for indexes
• Thinking numeric fields can't be indexed
• Assuming indexes slow queries

5. You have a large collection with frequent writes and queries on status and createdAt. How should you design indexes to balance read speed and write performance?

hard

A. Create a compound index on {status: 1, createdAt: -1} and avoid extra indexes.

B. Create separate indexes on status and createdAt and many others for all queries.

C. Create no indexes to keep writes fast.

D. Create an index on a non-used field to reduce write load.

Solution

1. Step 1: Understand compound indexes for multiple query fields

   A compound index on {status: 1, createdAt: -1} supports queries filtering by status and sorting by createdAt efficiently.

2. Step 2: Balance index count for write performance

   Too many indexes slow writes. Using one compound index reduces overhead while improving read speed.

3. Final Answer:

   Create a compound index on {status: 1, createdAt: -1} and avoid extra indexes. -> Option A

4. Quick Check:

   Compound index balances reads and writes = A [OK]

Hint: Use compound indexes for multi-field queries, limit total indexes [OK]

Common Mistakes:

• Creating too many indexes hurting write speed
• Not using compound indexes for related fields
• Avoiding indexes completely hurting read speed