Query patterns that cause collection scans in MongoDB - Step-by-Step Execution

Concept Flow - Query patterns that cause collection scans

Receive Query

↓

Check for Indexes

↓

Use Index

↓

Return Results

↓

End

The database receives a query, checks if an index can be used, and if not, performs a collection scan to find matching documents.

Execution Sample

MongoDB

db.users.find({ age: { $gt: 30 } })

Query to find users older than 30, which may cause a collection scan if no index on 'age' exists.

Execution Table

Step	Action	Index Available?	Operation	Documents Examined	Result
1	Receive query { age: { $gt: 30 } }	Unknown	Check indexes	0	Proceed
2	Check if index on 'age' exists	No	Decide operation	0	No index found
3	Perform collection scan	No	Scan all documents	1000	Filter documents with age > 30
4	Return matching documents	No	Return results	N/A	Documents with age > 30
5	End query execution	No	Complete	N/A	Query finished

💡 No index on 'age' found, so collection scan examines all 1000 documents.

Variable Tracker

Variable	Start	After Step 2	After Step 3	Final
indexExists	Unknown	False	False	False
documentsExamined	0	0	1000	1000
matchingDocuments	0	0	Variable	Variable

Key Moments - 2 Insights

Why does the query scan the entire collection instead of using an index?

Because the execution_table row 2 shows no index exists on the 'age' field, so the database must scan all documents.

Does the collection scan check every document?

Yes, as shown in execution_table row 3, all 1000 documents are examined to filter those matching the condition.

Visual Quiz - 3 Questions

Look at the execution_table, at which step does the database decide to perform a collection scan?

A Step 1

B Step 3

C Step 2

D Step 4

💡 Hint

Check the 'Operation' and 'Index Available?' columns in execution_table row 2.

According to variable_tracker, how many documents are examined during the collection scan?

A 1000

B 0

C 500

D Variable

💡 Hint

Look at 'documentsExamined' after Step 3 in variable_tracker.

If an index on 'age' existed, which step would change in the execution_table?

A Step 1 would skip

B Step 3 would use index instead of collection scan

C Step 4 would not return results

D Step 5 would be removed

💡 Hint

Refer to the 'Operation' column in execution_table rows 2 and 3.

Concept Snapshot

Query patterns without matching indexes cause collection scans.
Database checks for indexes first.
If no index, scans all documents.
Collection scans are slower on large data.
Create indexes on queried fields to avoid scans.

Full Transcript

When a MongoDB query runs, the database first checks if an index exists for the queried field. If an index is found, it uses it to quickly find matching documents. If no index exists, the database performs a collection scan, meaning it looks at every document in the collection to find matches. For example, querying users with age greater than 30 without an index on 'age' causes a collection scan. This scan examines all documents, which can be slow for large collections. To improve performance, create indexes on fields used in queries.

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