Covered queries with indexes in MongoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a covered query in MongoDB?

A covered query is a query that can be answered using only the index without reading the actual documents from the collection. This makes the query faster because it avoids fetching full documents.

beginner

How do indexes help covered queries in MongoDB?

Indexes store the fields and their values in a way that MongoDB can quickly find data. If the query only requests fields included in the index, MongoDB can return results directly from the index, making it a covered query.

intermediate

What fields must be included in an index to support a covered query?

All fields used in the query filter and all fields returned in the query projection must be included in the index for the query to be covered.

intermediate

Example: Which index supports this query as a covered query? Query: db.users.find({age: 30}, {name: 1, age: 1, _id: 0})

An index on {age: 1, name: 1} supports this covered query because it includes the filter field 'age' and the returned field 'name'. The _id field is excluded in projection, so it doesn't need to be in the index.

beginner

Why might a covered query improve performance compared to a normal query?

Because MongoDB can answer the query using only the index, it avoids reading the full documents from disk or memory. This reduces I/O and speeds up query response time.

What does a covered query in MongoDB avoid reading?

A The index entries

B The full documents from the collection

C The query filter

D The query projection

Covered queries use only the index to answer the query, so they avoid reading the full documents.

Which fields must be in the index for a query to be covered?

A Only the fields in the query filter

B Only the fields in the query projection

C Both the fields in the query filter and projection

D None, indexes are not needed

All fields used in the query filter and projection must be in the index for the query to be covered.

If a query returns the _id field but the index does not include _id, is the query covered?

A No, _id must be in the index for coverage

B Yes, _id is always included automatically

C Yes, if the query filter fields are in the index

D No, _id is never returned

For covered queries, all projected fields including _id must be in the index. Compound indexes do not include _id by default.

What is a benefit of using covered queries?

A They reduce network traffic by returning only index data

B They increase disk usage

C They slow down query execution

D They require no indexes

Covered queries reduce disk I/O and network traffic by returning data directly from the index.

Which MongoDB command helps check if a query is covered?

A db.collection.update()

B db.collection.find()

C db.collection.insert()

D db.collection.explain()

The explain() command shows query execution details, including whether the query is covered by an index.

Explain what a covered query is and why it improves performance in MongoDB.

Think about how indexes can answer queries without fetching full data.

Describe the requirements for an index to support a covered query.

Consider which fields the query uses and returns.

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