Covered queries with indexes in MongoDB - Mini Project: Build & Apply

Covered Queries with Indexes in MongoDB

📖 Scenario: You are managing a small online bookstore database. You want to speed up queries that search for books by author and title without fetching the entire document from the database.

🎯 Goal: Create a MongoDB collection called books with sample data. Then create a covered query by building an index on author and title fields. Finally, write a query that uses this index to return only the author and title fields, ensuring the query is covered by the index.

📋 What You'll Learn

Create a books collection with 3 documents containing author, title, and year fields

Create a compound index on author and title

Write a query that finds books by a specific author and returns only author and title fields

Ensure the query is covered by the index (no document fetch needed)

💡 Why This Matters

🌍 Real World

Covered queries help speed up database reads by using indexes alone, which is important for fast search features in apps like online bookstores.

💼 Career

Understanding covered queries and indexes is essential for database administrators and backend developers to optimize query performance and reduce server load.

1

Create the books collection with sample documents

Create a MongoDB collection called books and insert these exact documents: { author: "George Orwell", title: "1984", year: 1949 }, { author: "Harper Lee", title: "To Kill a Mockingbird", year: 1960 }, and { author: "George Orwell", title: "Animal Farm", year: 1945 }.

MongoDB

// Insert the 3 specified documents into the books collection
// Your code here

Hint

Use db.books.insertMany([...]) with the exact documents inside the array.

2

Create a compound index on author and title

Create a compound index on the books collection for the fields author and title in ascending order.

MongoDB

db.books.insertMany([
  { author: "George Orwell", title: "1984", year: 1949 },
  { author: "Harper Lee", title: "To Kill a Mockingbird", year: 1960 },
  { author: "George Orwell", title: "Animal Farm", year: 1945 }
])
// Create the compound index on author and title
// Your code here

Hint

Use db.books.createIndex({ author: 1, title: 1 }) to create the index.

3

Write a query to find books by George Orwell returning only author and title

Write a MongoDB query on the books collection to find documents where author is "George Orwell". Return only the author and title fields (exclude _id).

MongoDB

db.books.insertMany([
  { author: "George Orwell", title: "1984", year: 1949 },
  { author: "Harper Lee", title: "To Kill a Mockingbird", year: 1960 },
  { author: "George Orwell", title: "Animal Farm", year: 1945 }
])
db.books.createIndex({ author: 1, title: 1 })
// Write the query to find George Orwell's books returning only author and title
// Your code here

Hint

Use db.books.find({ author: "George Orwell" }, { author: 1, title: 1, _id: 0 }) to return only the needed fields.

4

Ensure the query is covered by the index

Add the .explain("executionStats") method to the query to check that the query is covered by the index (no document fetch).

MongoDB

db.books.insertMany([
  { author: "George Orwell", title: "1984", year: 1949 },
  { author: "Harper Lee", title: "To Kill a Mockingbird", year: 1960 },
  { author: "George Orwell", title: "Animal Farm", year: 1945 }
])
db.books.createIndex({ author: 1, title: 1 })
db.books.find(
  { author: "George Orwell" },
  { author: 1, title: 1, _id: 0 }
).explain("executionStats")
// Your code here

Hint

Add .explain("executionStats") after the find() query to check the query plan.

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