Sparse indexes in MongoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Effect of sparse index on documents without the indexed field

Consider a MongoDB collection with documents where some have the field age and others do not. A sparse index is created on the age field.

What will be the result of the following query?

db.collection.find({ age: { $exists: false } }).hint({ age: 1 })

Assuming the sparse index is used as a hint, what will the query return?

A It returns no documents because sparse indexes exclude documents without the indexed field.

B It returns all documents where the <code>age</code> field does not exist.

C It returns all documents regardless of the <code>age</code> field existence.

D It causes a query error because sparse indexes cannot be used with $exists queries.

💡 Hint

Think about what documents are included in a sparse index.

Sparse indexes only include documents that have the indexed field. Documents without the field are not indexed and thus cannot be found using the sparse index. Using the sparse index as a hint for a query looking for documents without the field will return no results.

🧠 Conceptual

intermediate

Purpose of sparse indexes in MongoDB

What is the main purpose of creating a sparse index in MongoDB?

A To index all documents including those with null or missing values for the indexed field.

B To automatically update the index when documents are deleted.

C To create a unique index that enforces uniqueness only on documents with the indexed field.

D To index only documents that contain the indexed field, saving space and improving performance for sparse data.

💡 Hint

Think about how sparse data affects indexing.

Sparse indexes only include documents that have the indexed field. This reduces index size and improves performance when many documents lack that field.

📝 Syntax

advanced

Correct syntax to create a sparse index

Which of the following commands correctly creates a sparse index on the email field in a MongoDB collection?

A db.collection.createIndex({ email: 1 }, { isSparse: true })

B db.collection.createIndex({ email: 1 }, { sparseIndex: true })

C db.collection.createIndex({ email: 1 }, { sparse: true })

D db.collection.createIndex({ email: 1 }, { sparse: 'yes' })

💡 Hint

Check the exact option name and value type for sparse indexes.

The correct option to create a sparse index is { sparse: true }. Other options are invalid or incorrect.

❓ optimization

advanced

When to prefer sparse indexes over regular indexes

You have a MongoDB collection where only 10% of documents have the phoneNumber field. You want to index this field to speed up queries filtering by phoneNumber.

Which indexing strategy is best to optimize storage and query performance?

A Create a sparse index on <code>phoneNumber</code> to index only documents that have this field.

B Create a regular index on <code>phoneNumber</code> to index all documents regardless of field presence.

C Create a compound index including <code>phoneNumber</code> and another field to cover more queries.

D Do not create any index because sparse fields are not suitable for indexing.

💡 Hint

Consider how many documents have the field and how sparse indexes work.

A sparse index indexes only documents with the field, saving space and improving query speed when the field is missing in many documents.

🔧 Debug

expert

Unexpected query result with sparse index

A developer created a sparse index on the status field in a MongoDB collection. They run this query:

db.collection.find({ status: null })

But the query returns documents where status does not exist, even though they expected only documents with status set to null.

Why does this happen?

A Because the sparse index causes documents with <code>status</code> missing to be indexed as null.

B Because in MongoDB, querying <code>{ status: null }</code> matches documents where <code>status</code> is null or missing.

C Because sparse indexes include documents with missing fields as null values.

D Because the query syntax is invalid and returns all documents.

💡 Hint

Think about how MongoDB treats null in queries.

In MongoDB, a query for { field: null } matches documents where the field is either null or does not exist. This is independent of the sparse index.