Query patterns that cause collection scans in MongoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a collection scan in MongoDB?

A collection scan happens when MongoDB reads every document in a collection to find those that match a query. It is slow because it checks all documents instead of using an index.

beginner

Name a common query pattern that causes a collection scan.

Queries that do not use an index, such as searching on a field without an index or using operators that prevent index use, cause collection scans.

intermediate

Why does using a regular expression without an index cause a collection scan?

Because MongoDB cannot use an index efficiently for regex patterns that do not start with a fixed prefix, it scans all documents to match the pattern.

intermediate

How does querying with $not or $ne operators affect index usage?

Queries using $not or $ne often cause collection scans because these operators do not use indexes well, forcing MongoDB to check all documents.

beginner

What is a way to avoid collection scans in MongoDB queries?

Create indexes on fields used in queries and write queries that can use those indexes, avoiding operators or patterns that prevent index use.

Which of the following query patterns is most likely to cause a collection scan in MongoDB?

A Query using $ne operator on a non-indexed field

B Query using equality on an indexed field

C Query on a field with a supporting index

D Query using _id field

Using $ne on a field without an index causes MongoDB to scan all documents, resulting in a collection scan.

What does MongoDB do during a collection scan?

A Reads documents in random order

B Reads only indexed documents

C Reads all documents in the collection

D Reads only documents matching the query

A collection scan means MongoDB reads every document in the collection to find matches.

Which operator often prevents MongoDB from using an index, causing a collection scan?

A $not

B $eq

C $gt

D $in

The $not operator often prevents index use, leading to collection scans.

How can you reduce collection scans in MongoDB queries?

A Avoid creating indexes

B Use queries that match indexed fields

C Use $ne operator frequently

D Scan all documents manually

Using queries that match indexed fields helps MongoDB use indexes and avoid collection scans.

Why does a regex query without a fixed prefix cause a collection scan?

A Because regex queries never scan collections

B Because regex always uses indexes

C Because regex queries are faster without indexes

D Because MongoDB cannot use indexes efficiently without a fixed prefix

MongoDB cannot use indexes efficiently for regex patterns without a fixed prefix, causing collection scans.

Explain what causes a collection scan in MongoDB and how to avoid it.

Think about how MongoDB finds documents and what happens when no index is used.

Describe how operators like $ne and $not affect MongoDB query performance.

Consider how MongoDB searches documents when these operators are used.

Practice

1. Which of the following query patterns in MongoDB is most likely to cause a collection scan?

easy

A. Querying a field without an index

B. Querying a field with a single-field index

C. Using an indexed field with equality operator

D. Using a covered index query

Solution

1. Step 1: Understand collection scan causes

   A collection scan happens when MongoDB must check every document because no index supports the query.

2. Step 2: Analyze query patterns

   Querying a field without an index forces MongoDB to scan the entire collection, unlike queries using indexed fields.

3. Final Answer:

   Querying a field without an index -> Option A

4. Quick Check:

   No index = collection scan [OK]

Hint: No index on field? Expect collection scan [OK]

Common Mistakes:

• Assuming all queries use indexes automatically
• Confusing covered index with collection scan
• Thinking equality queries always cause scans

2. Which of the following MongoDB query syntaxes is correct and avoids collection scans by using an index on the field age?

easy

A. db.users.find({ age: { $gt: 25 } })

B. db.users.find({ $where: 'this.age > 25' })

C. db.users.find({ age: { $regex: '^2' } })

D. db.users.find({ $text: { $search: '25' } })

Solution

1. Step 1: Check query syntax correctness

   All queries are syntactically valid, but some use operators that prevent index use.

2. Step 2: Identify index-friendly query

   Query with { age: { $gt: 25 } } uses range operator on indexed field, avoiding collection scan. Queries with $where or $regex often cause scans.

3. Final Answer:

   db.users.find({ age: { $gt: 25 } }) -> Option A

4. Quick Check:

   Range query on indexed field = no scan [OK]

Hint: Use simple operators on indexed fields to avoid scans [OK]

Common Mistakes:

• Using $where causes collection scan
• Assuming $regex always uses index
• Confusing $text search with field index

3. Given a collection products with an index on category, what will be the result of this query?

db.products.find({ category: { $in: ['electronics', 'books'] } })

medium

A. Throws a syntax error due to $in usage

B. Performs a collection scan and returns all documents

C. Returns no documents because $in is unsupported

D. Uses index on category and returns matching documents

Solution

1. Step 1: Understand $in operator with indexes

   The $in operator can use indexes on the queried field to find matching values efficiently.

2. Step 2: Analyze query behavior

   Since category is indexed, MongoDB uses the index to find documents where category is 'electronics' or 'books'.

3. Final Answer:

   Uses index on category and returns matching documents -> Option D

4. Quick Check:

   $in + indexed field = index used [OK]

Hint: Indexed field + $in uses index, no scan [OK]

Common Mistakes:

• Thinking $in disables index use
• Assuming $in causes syntax error
• Believing collection scan always happens

4. You have a MongoDB collection orders with an index on status. Which query will cause a collection scan and how can you fix it?

db.orders.find({ $where: 'this.status === "shipped"' })

medium

A. Syntax error; fix by removing $where

B. Uses index; no fix needed

C. Causes collection scan; fix by using { status: 'shipped' }

D. Causes collection scan; fix by adding $regex

Solution

1. Step 1: Identify $where impact on query

   The $where operator runs JavaScript on each document, forcing a collection scan regardless of indexes.

2. Step 2: Fix query to use index

   Replacing $where with a direct field query { status: 'shipped' } uses the index on status, avoiding collection scan.

3. Final Answer:

   Causes collection scan; fix by using { status: 'shipped' } -> Option C

4. Quick Check:

   $where disables index; direct query fixes [OK]

Hint: Avoid $where; use direct field queries for indexes [OK]

Common Mistakes:

• Assuming $where uses indexes
• Trying to fix with $regex instead of direct query
• Confusing syntax error with collection scan

5. You want to optimize this MongoDB query to avoid collection scans on a large users collection:

db.users.find({ $or: [ { age: { $gt: 30 } }, { name: /John/ } ] })

Given indexes on age and name, which change will prevent collection scans?

hard

A. Remove indexes and rely on collection scan for speed

B. Rewrite query to separate $or into two queries using indexed fields

C. Use $where with JavaScript to filter documents

D. Change regex to case-insensitive without anchors

Solution

1. Step 1: Understand $or with mixed operators

   Regex queries often prevent index use, causing collection scans even if other fields are indexed.

2. Step 2: Optimize by splitting queries

   Running two separate queries--one on age and one on name--each using indexes, then combining results in application avoids scans.

3. Final Answer:

   Rewrite query to separate $or into two queries using indexed fields -> Option B

4. Quick Check:

   Split queries + indexes avoid scans [OK]

Hint: Split $or queries to use indexes separately [OK]

Common Mistakes:

• Believing regex always uses index
• Using $where increases scans
• Removing indexes reduces performance