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

Challenge - 5 Problems

🧠 Conceptual

intermediate

How do indexes improve query speed in MongoDB?

Imagine you have a huge phone book and you want to find a person's phone number. Without an index, you might have to look at every page. How does an index help MongoDB find data faster?

A Indexes compress data to make it smaller and faster to read.

B Indexes store all data in memory so queries never access the disk.

C Indexes let MongoDB jump directly to the data location without scanning all documents.

D Indexes duplicate all data to speed up queries.

💡 Hint

Think about how a book's index helps you find a topic quickly.

Indexes create a fast lookup structure that points to the exact location of data, avoiding full collection scans.

❓ query_result

intermediate

What is the output count of a query with and without an index?

Given a collection users with 100,000 documents, 10,000 have age: 30. You run this query:

db.users.find({age: 30}).count()

What will be the count returned?

A 10000

B 0

C 100000

D Error: no index found

💡 Hint

The count is about how many documents match, not how fast the query runs.

The query counts all documents where age is 30, which is 10,000 regardless of indexing.

📝 Syntax

advanced

Which index creation command is correct for fast queries on 'email' field?

You want to create an index on the email field in the users collection. Which command is correct?

A db.users.createIndex({email})

B db.users.createIndex(email)

C db.users.createIndex(['email'])

D db.users.createIndex({email: 1})

💡 Hint

Indexes need a field name and sort order inside an object.

The correct syntax uses an object with the field name as key and 1 for ascending order.

❓ optimization

advanced

Which index type is best for queries filtering on multiple fields?

You often query orders collection filtering by customerId and status. Which index improves performance best?

A A text index on customerId and status

B A compound index on {customerId: 1, status: 1}

C Separate single-field indexes on customerId and status

D No index, just scan all documents

💡 Hint

Think about how combining fields in one index helps multi-field queries.

A compound index on both fields lets MongoDB efficiently filter by both at once.

🔧 Debug

expert

Why does this query run slowly despite an index on 'username'?

Collection users has an index on username. This query is slow:

db.users.find({username: /john/i})

Why?

A Regex with case-insensitive flag prevents index use

B Index on username is corrupted

C Query syntax is invalid

D MongoDB does not support indexes on strings

💡 Hint

Think about how indexes work with regular expressions.

Case-insensitive regex disables index use because it can't match index order efficiently.