Sparse indexes in MongoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a sparse index in MongoDB?

A sparse index only includes documents in the index if the indexed field exists. Documents without the field are not indexed.

beginner

How does a sparse index differ from a regular index?

A regular index includes all documents, even if the indexed field is missing or null. A sparse index skips documents missing the field.

intermediate

Why use a sparse index?

To save space and improve performance when many documents do not have the indexed field, because only documents with the field are indexed.

intermediate

Can a sparse index be used with unique constraints?

Yes, but only documents with the indexed field are checked for uniqueness. Documents without the field can have duplicates.

beginner

How do you create a sparse index in MongoDB?

Use the createIndex method with the option { sparse: true }, for example: db.collection.createIndex({ field: 1 }, { sparse: true })

What does a sparse index in MongoDB exclude?

A All documents in the collection

B Documents where the indexed field is present

C Documents where the indexed field is missing

D Only documents with null values in the indexed field

Sparse indexes exclude documents where the indexed field does not exist.

Which option is used to create a sparse index in MongoDB?

A { unique: true }

B { sparse: true }

C { background: true }

D { expireAfterSeconds: 3600 }

The option { sparse: true } tells MongoDB to create a sparse index.

Can a sparse index enforce uniqueness on documents missing the indexed field?

A Yes, it enforces uniqueness on all documents

B Yes, but only if the field is null

C No, sparse indexes cannot be unique

D No, it only enforces uniqueness on documents with the indexed field

Sparse unique indexes enforce uniqueness only on documents that have the indexed field.

What is a benefit of using a sparse index?

A Saves space by indexing fewer documents

B Indexes all documents regardless of field presence

C Automatically updates documents

D Prevents all duplicates in the collection

Sparse indexes save space by indexing only documents that contain the indexed field.

If a document does not have the indexed field, how does a sparse index treat it?

A Excludes it from the index

B Throws an error

C Indexes it as zero

D Includes it in the index with a null value

Documents missing the indexed field are excluded from a sparse index.

Explain what a sparse index is and when you would use it in MongoDB.

Think about indexing only documents that have a certain field.

Describe how uniqueness works with sparse indexes in MongoDB.

Consider how missing fields affect unique constraints.

Practice

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

easy

A. To index only documents that contain the indexed field

B. To index all documents regardless of field presence

C. To create a backup of the database

D. To speed up writes by disabling indexing

Solution

1. Step 1: Understand sparse index behavior

   Sparse indexes only include documents that have the indexed field present.

2. Step 2: Compare with other index types

   Unlike regular indexes, sparse indexes skip documents missing the field, saving space and improving query speed on sparse data.

3. Final Answer:

   To index only documents that contain the indexed field -> Option A

4. Quick Check:

   Sparse index = indexes only documents with the field [OK]

Hint: Sparse indexes skip documents missing the field [OK]

Common Mistakes:

• Thinking sparse indexes index all documents
• Confusing sparse indexes with backups
• Assuming sparse indexes disable indexing

2. Which of the following is the correct way to create a sparse index on the field email in MongoDB?

easy

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

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

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

D. db.collection.createIndex({ email: 1 }, { expireAfterSeconds: 3600 })

Solution

1. Step 1: Identify sparse index syntax

   The option { sparse: true } is used to create a sparse index in MongoDB.

2. Step 2: Verify the correct command

   The command db.collection.createIndex({ email: 1 }, { sparse: true }) correctly creates a sparse index on the email field.

3. Final Answer:

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

4. Quick Check:

   Sparse index creation uses { sparse: true } [OK]

Hint: Use { sparse: true } option to create sparse indexes [OK]

Common Mistakes:

• Using unique instead of sparse option
• Confusing background with sparse
• Using expireAfterSeconds for sparse index

3. Given a collection with documents:

{ _id: 1, name: "Alice", age: 30 }

{ _id: 2, name: "Bob" }

{ _id: 3, name: "Charlie", age: 25 }

and a sparse index on age, what documents will be returned by db.collection.find({ age: { $gte: 25 } })?

medium

A. Documents with _id 1 and 3 only

B. Documents with _id 1, 2, and 3

C. Documents with _id 2 only

D. No documents returned

Solution

1. Step 1: Understand sparse index effect on query

   The sparse index on age only indexes documents that have the age field. Document with _id 2 has no age field, so it is not indexed.

2. Step 2: Evaluate the query filter

   The query { age: { $gte: 25 } } matches documents where age is 25 or more. Documents with _id 1 (age 30) and _id 3 (age 25) match. Document _id 2 is excluded because it has no age field.

3. Final Answer:

   Documents with _id 1 and 3 only -> Option A

4. Quick Check:

   Sparse index excludes docs missing field, so only _id 1 and 3 match [OK]

Hint: Sparse index excludes docs missing field, so only those with field match [OK]

Common Mistakes:

• Including documents without the indexed field
• Assuming all documents are returned
• Confusing sparse index with regular index

4. You created a sparse index on phone field but your queries on phone are slow. What is a likely cause?

medium

A. Sparse indexes index all documents regardless of field presence

B. Sparse indexes always slow down queries

C. You forgot to create the index

D. Many documents do not have the phone field, so index is small and not used

Solution

1. Step 1: Analyze sparse index behavior

   Sparse indexes only index documents with the field. If many documents lack the phone field, the index is small.

2. Step 2: Understand query performance impact

   If the index is small or not selective, MongoDB may choose not to use it, causing slower queries.

3. Final Answer:

   Many documents do not have the phone field, so index is small and not used -> Option D

4. Quick Check:

   Sparse index small if field missing in many docs, may not speed queries [OK]

Hint: Sparse index small if many docs lack field, may not improve speed [OK]

Common Mistakes:

• Assuming sparse indexes always slow queries
• Forgetting to create the index
• Thinking sparse indexes index all documents

5. You want to create an index on the status field, but only for documents where status exists and is not null. Which MongoDB index type should you use and why?

hard

A. TTL index, because it removes documents after a time

B. Sparse index, because it indexes only documents with the field present

C. Regular index, because it indexes all documents regardless of field

D. Unique index, because it enforces unique values

Solution

1. Step 1: Identify index requirement

   You want to index only documents where status exists and is not null, skipping documents without status.

2. Step 2: Match index type to requirement

   Sparse indexes index only documents that have the indexed field, which fits the requirement perfectly.

3. Final Answer:

   Sparse index, because it indexes only documents with the field present -> Option B

4. Quick Check:

   Use sparse index to index only docs with the field [OK]

Hint: Use sparse index to index only documents with the field present [OK]

Common Mistakes:

• Choosing regular index which indexes all documents
• Confusing TTL or unique indexes with sparse
• Not understanding sparse index skips missing fields