Query patterns that cause collection scans in MongoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Which query causes a collection scan due to missing index?

Given a collection users with an index on age, which query will cause a collection scan?

MongoDB

db.users.find({name: 'Alice'})

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

B db.users.find({age: 30, name: 'Alice'})

C db.users.find({name: 'Alice'})

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

💡 Hint

Think about which field has an index and which does not.

Only queries filtering on the indexed field age can use the index. Querying by name without an index causes a collection scan.

❓ query_result

intermediate

Which query pattern causes a collection scan despite an index?

Assuming an index exists on status, which query will still cause a collection scan?

MongoDB

db.orders.find({status: {$ne: 'shipped'}})

A db.orders.find({status: {$in: ['shipped', 'pending']}})

B db.orders.find({status: 'shipped'})

C db.orders.find({status: {$eq: 'shipped'}})

D db.orders.find({status: {$ne: 'shipped'}})

💡 Hint

Think about how negation operators affect index usage.

The $ne operator cannot use indexes efficiently and causes a collection scan even if an index exists on the field.

📝 Syntax

advanced

Which query syntax causes a runtime error due to invalid operator usage?

Identify the query that will cause a runtime error in MongoDB due to incorrect operator usage.

A db.products.find({price: {$between: [50, 100]}})

B db.products.find({$and: [{price: {$gt: 50}}, {price: {$lt: 100}}]})

C db.products.find({price: {$gte: 50, $lte: 100}})

D db.products.find({price: {$lt: 100}})

💡 Hint

Check if the operator is valid in MongoDB query language.

MongoDB does not support the $between operator. Using it causes a runtime error.

❓ optimization

advanced

Which query pattern can be optimized to avoid collection scan?

Given a collection with an index on category, which query can be rewritten to use the index and avoid a collection scan?

A db.items.find({category: {$exists: true}})

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

C db.items.find({category: {$ne: null}})

D db.items.find({category: {$not: {$eq: 'clothing'}}})

💡 Hint

Consider which operators allow index usage.

The $in operator can use indexes efficiently. Other operators like $exists, $ne, and $not often cause collection scans.

🧠 Conceptual

expert

Why does a query with a regex pattern cause a collection scan?

Consider a collection with an index on the username field. Why does the query db.users.find({username: /admin/}) cause a collection scan?

A Because MongoDB can only use indexes for regex queries if the pattern is a prefix without special characters.

B Because the regex pattern is anchored at the start, so index is not used.

C Because regex queries never use indexes in MongoDB.

D Because the index on username is corrupted.

💡 Hint

Think about how MongoDB uses indexes with regex patterns.

MongoDB can use indexes for regex queries only if the pattern is a simple prefix without special regex characters. Complex patterns cause collection scans.

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