Covered queries with indexes in MongoDB

Introduction

Covered queries help MongoDB find data quickly by using only the index without looking at the full documents.

When you want to speed up read operations on a collection.

When you only need a few fields from documents, not the whole document.

When you want to reduce the amount of data MongoDB reads from disk.

When you want to improve performance for frequent queries on specific fields.

Syntax

MongoDB

db.collection.createIndex({ field1: 1, field2: 1 })
db.collection.find({ field1: value }, { field1: 1, field2: 1, _id: 0 })

The index must include all fields used in the query filter and the fields returned in the result.

Exclude the _id field in the projection if it is not part of the index to keep the query covered.

Examples

This query uses an index on category and price to return only those fields without reading full documents.

MongoDB

db.products.createIndex({ category: 1, price: 1 })
db.products.find({ category: "books" }, { category: 1, price: 1, _id: 0 })

A simple covered query that uses an index on username and returns only the username field.

MongoDB

db.users.createIndex({ username: 1 })
db.users.find({ username: "alice" }, { username: 1, _id: 0 })

Sample Program

This query finds orders for customer 12345 and returns only customerId and status fields using the index.

MongoDB

db.orders.createIndex({ customerId: 1, status: 1 })
db.orders.find({ customerId: 12345 }, { customerId: 1, status: 1, _id: 0 })

Important Notes

Covered queries reduce disk I/O because MongoDB does not fetch the full document.

Make sure the index covers all fields in the query filter and projection to benefit from covered queries.

If you include fields in the projection that are not in the index, MongoDB will fetch the full document.

Summary

Covered queries use indexes to return data without reading full documents.

They improve query speed and reduce resource use.

Create indexes that include all fields you filter and return.

Practice

1. What is a covered query in MongoDB?

easy

A. A query that only returns the document _id field

B. A query that scans all documents in a collection

C. A query that updates documents without using indexes

D. A query that uses an index to return all requested fields without reading the full document

Solution

1. Step 1: Understand what a covered query means

   A covered query uses an index that contains all the fields needed for the query, so MongoDB does not need to fetch the full document from the collection.

2. Step 2: Identify the correct description

   A query that uses an index to return all requested fields without reading the full document correctly describes a covered query as one that returns all requested fields from the index alone, improving speed and resource use.

3. Final Answer:

   A query that uses an index to return all requested fields without reading the full document -> Option D

4. Quick Check:

   Covered query = uses index only [OK]

Hint: Covered queries return data only from indexes, no document fetch [OK]

Common Mistakes:

• Thinking covered queries scan full documents
• Confusing covered queries with index-only updates
• Assuming covered queries only return _id field

2. Which MongoDB index definition supports a covered query for filtering on status and returning status and score fields?

easy

A. { status: 1, score: 1 }

B. { score: 1 }

C. { status: 1 }

D. { _id: 1, status: 1 }

Solution

1. Step 1: Identify fields needed for covered query

   The query filters on status and returns status and score. The index must include all these fields.

2. Step 2: Choose index covering all fields

   { status: 1, score: 1 } includes both status and score, so it can cover the query without fetching documents.

3. Final Answer:

   { status: 1, score: 1 } -> Option A

4. Quick Check:

   Index includes filter and return fields [OK]

Hint: Index must include all filter and return fields for coverage [OK]

Common Mistakes:

• Using index with only filter or only return fields
• Assuming _id is always included in covered queries
• Ignoring order of fields in index for coverage

3. Given the index { category: 1, price: 1 } on a collection, what will be the output of this query?

db.products.find({ category: 'books' }, { category: 1, price: 1, _id: 0 })

medium

A. Error because _id is excluded

B. Documents with all fields because index is ignored

C. Documents with only category and price fields, fetched from index (covered query)

D. Documents with category only, price missing

Solution

1. Step 1: Analyze the index and query fields

   The index covers category and price. The query filters on category and returns category and price only, excluding _id.

2. Step 2: Determine if query is covered

   Since all requested fields are in the index, MongoDB can return results from the index without fetching full documents, making it a covered query.

3. Final Answer:

   Documents with only category and price fields, fetched from index (covered query) -> Option C

4. Quick Check:

   Index covers filter and projection fields [OK]

Hint: Projection fields must be in index for covered query output [OK]

Common Mistakes:

• Assuming _id exclusion causes error
• Thinking full documents are always returned
• Ignoring index coverage for projection

4. You have an index { user: 1 } but your query is:

db.users.find({ user: 'alice' }, { age: 1, _id: 0 })

Why is this query NOT a covered query?

medium

A. Because the index does not include the age field in the index keys

B. Because the query excludes _id which is always required

C. Because the index does not include the age field in the projection

D. Because the query filters on user but projection excludes it

Solution

1. Step 1: Check index fields and query projection

   The index has only user. The query filters on user but only returns age, excluding _id.

2. Step 2: Understand covered query requirements

   For a covered query, the index must include all returned fields in the projection. Since age is not in the index, MongoDB must fetch the full document.

3. Final Answer:

   Because the index does not include the age field in the index keys -> Option A

4. Quick Check:

   Index must include all projection fields [OK]

Hint: All projected fields must be in the index for coverage [OK]

Common Mistakes:

• Thinking _id exclusion breaks coverage
• Assuming index on filter field covers all projections
• Thinking filter fields must appear in projection

5. You want to optimize this query for coverage:

db.orders.find({ status: 'shipped', total: { $gt: 100 } }, { status: 1, total: 1, customer: 1, _id: 0 })

Which index will allow this query to be covered?

hard

A. { status: 1, total: 1 }

B. { status: 1, total: 1, customer: 1 }

C. { total: 1, customer: 1 }

D. { status: 1, customer: 1 }

Solution

1. Step 1: Identify filter and projection fields

   The query filters on status and total, and returns status, total, and customer.

2. Step 2: Choose index covering all fields

   To cover the query, the index must include all filter and returned fields: status, total, and customer. { status: 1, total: 1, customer: 1 } includes all three.

3. Final Answer:

   { status: 1, total: 1, customer: 1 } -> Option B

4. Quick Check:

   Index covers filter + projection fields [OK]

Hint: Index must include all filter and returned fields for coverage [OK]

Common Mistakes:

• Leaving out returned fields from index
• Assuming filter fields alone suffice
• Ignoring order of fields in index