MongoDB explain() Practice Questions with Solutions

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Introduction

MongoDB’s explain() method helps developers understand how MongoDB executes a query. It can show whether MongoDB uses an index, scans the entire collection, how many documents or index keys it examines, and other execution details. In this chapter, you will practice using explain(), understanding IXSCAN and COLLSCAN, checking execution statistics, and comparing queries with different indexes. MongoDB explain() practice questions with solutions to help you understand the concepts.

Q1. Use explain() with a Basic Query

Problem Statement

Display the execution plan for a query that finds a student named Rahul.

MongoDB Command / Query

db.students.find({
  name: "Rahul"
}).explain()

Expected Output

The output contains an execution plan similar to:

{
  queryPlanner: {
    ...
  }
}

Explanation

explain() does not simply return the matching documents. Instead, it provides information about how MongoDB plans and executes the query.

Q2. Use explain("executionStats")

Problem Statement

Find students whose age is greater than 15 and display detailed execution statistics.

MongoDB Command / Query

db.students.find({
  age: {
    $gt: 15
  }
}).explain("executionStats")

Expected Output

The result contains information similar to:

{
  executionStats: {
    executionSuccess: true,
    nReturned: 3,
    executionTimeMillis: 1,
    totalKeysExamined: 0,
    totalDocsExamined: 10
  }
}

Explanation

"executionStats" provides actual execution information, including:

  • nReturned — number of documents returned
  • totalKeysExamined — number of index entries examined
  • totalDocsExamined — number of documents examined
  • executionTimeMillis — reported execution time

The exact values depend on your data and indexes.

Q3. Check for a Collection Scan

Problem Statement

Check how MongoDB executes a query searching for students from Delhi.

MongoDB Command / Query

db.students.find({
  city: "Delhi"
}).explain("executionStats")

Expected Output

If there is no suitable index, the execution plan may contain:

COLLSCAN

Explanation

COLLSCAN means Collection Scan.

MongoDB examines documents in the collection to find matching documents.

For a small collection, this may be perfectly acceptable. For a large collection, an appropriate index may reduce the amount of data MongoDB needs to examine.

Q4. Create an Index and Check for IXSCAN

Problem Statement

Create an index on city and check the execution plan for a query searching for students from Delhi.

MongoDB Command / Query

Create the index:

db.students.createIndex({
  city: 1
})

Run the query:

db.students.find({
  city: "Delhi"
}).explain("executionStats")

Expected Output

The execution plan may contain:

IXSCAN

Explanation

IXSCAN means Index Scan.

MongoDB is using an index to locate matching records rather than scanning the entire collection.

Q5. Check How Many Documents Were Examined

Problem Statement

Find students enrolled in Python and check how many documents MongoDB examined.

MongoDB Command / Query

db.students.find({
  course: "Python"
}).explain("executionStats")

Look for:

executionStats.totalDocsExamined

Expected Output

Example:

totalDocsExamined: 5

Explanation

totalDocsExamined tells you how many documents MongoDB examined during execution.

The actual number depends on your collection, indexes, query, and query plan.

Q6. Check How Many Index Keys Were Examined

Problem Statement

Create an index on email and inspect how many index keys MongoDB examines when searching for an email address.

MongoDB Command / Query

Create the index:

db.students.createIndex({
  email: 1
})

Run:

db.students.find({
  email: "rahul@example.com"
}).explain("executionStats")

Look for:

executionStats.totalKeysExamined

Expected Output

Example:

totalKeysExamined: 1

Explanation

totalKeysExamined shows how many index entries MongoDB examined during query execution.

The exact value can vary depending on the query and index.

Q7. Check the Number of Returned Documents

Problem Statement

Find students older than 15 and use explain() to determine how many documents the query returned.

MongoDB Command / Query

db.students.find({
  age: {
    $gt: 15
  }
}).explain("executionStats")

Look for:

executionStats.nReturned

Expected Output

Example:

nReturned: 4

Explanation

nReturned represents the number of documents returned by the query.

It is different from totalDocsExamined.

For example:

nReturned: 4
totalDocsExamined: 10

means MongoDB returned 4 documents after examining 10 documents.

Q8. Analyze a Sorted Query with explain()

Problem Statement

Create an index on age and check the execution plan for a query that sorts students by age.

MongoDB Command / Query

Create the index:

db.students.createIndex({
  age: 1
})

Run:

db.students.find()
  .sort({
    age: 1
  })
  .explain("executionStats")

Expected Output

The execution plan may contain an index-related stage such as:

IXSCAN

Explanation

An appropriate index can help MongoDB with both finding data and supporting certain sort operations.

The exact winning plan depends on the query, collection size, available indexes, and data distribution.

Q9. Analyze a Compound Index Query

Problem Statement

Create a compound index on course and age, then use explain() to analyze a query that filters using both fields.

MongoDB Command / Query

Create the index:

db.students.createIndex({
  course: 1,
  age: 1
})

Run:

db.students.find({
  course: "Python",
  age: {
    $gte: 16
  }
}).explain("executionStats")

Expected Output

The execution plan may contain:

IXSCAN

and execution statistics such as:

{
  nReturned: 2,
  totalKeysExamined: 2,
  totalDocsExamined: 2
}

Explanation

A compound index can support queries involving multiple fields when its field order matches the query pattern.

The numbers above are examples. Your actual statistics will depend on your collection.

Q10. Compare Query Plans Before and After Indexing

Problem Statement

Check the execution plan for an email query, create an index on email, and check the execution plan again.

MongoDB Command / Query

First, run:

db.students.find({
  email: "rahul@example.com"
}).explain("executionStats")

If no suitable index exists, the plan may contain:

COLLSCAN

Now create an index:

db.students.createIndex({
  email: 1
})

Run the query again:

db.students.find({
  email: "rahul@example.com"
}).explain("executionStats")

Expected Output

Before indexing, the plan may contain:

COLLSCAN

After indexing, the plan may contain:

IXSCAN

Explanation

This is a practical way to investigate how an index changes query execution.

However, IXSCAN by itself does not automatically mean a query is faster in every situation. MongoDB’s optimizer considers the available plans and workload. Use execution statistics and real workload measurements when evaluating index changes.

Key Takeaways

  • explain() shows how MongoDB plans or executes a query.
  • explain() can be used with find(), sorting, and other query operations.
  • explain("executionStats") provides actual execution statistics.
  • COLLSCAN means MongoDB performed a collection scan.
  • IXSCAN means MongoDB used an index scan.
  • nReturned shows how many documents were returned.
  • totalDocsExamined shows how many documents were examined.
  • totalKeysExamined shows how many index entries were examined.
  • executionTimeMillis reports execution time for the examined operation.
  • Creating an index can change a query plan from a collection scan to an index-based plan, depending on the query and data.
  • IXSCAN alone should not be treated as a guarantee of better performance.
  • Always consider actual query patterns, data size, and workload when analyzing indexes.

FAQs

1. What is explain() in MongoDB?

explain() is a MongoDB method used to inspect how MongoDB plans and executes a query.

2. What does explain("executionStats") do?

It provides detailed information about the execution of the query, including returned documents, examined documents, examined index keys, and reported execution time.

3. What does COLLSCAN mean in MongoDB?

COLLSCAN means Collection Scan. MongoDB examines documents in the collection to find matching records.

4. What does IXSCAN mean in MongoDB?

IXSCAN means Index Scan. MongoDB is scanning an index to help execute the query.

5. What is totalDocsExamined?

totalDocsExamined indicates the number of documents MongoDB examined while executing the query.

6. What is totalKeysExamined?

totalKeysExamined indicates the number of index entries MongoDB examined during query execution.

7. Does IXSCAN always mean the query is faster?

No. IXSCAN only tells you that an index scan was used. Query performance depends on factors such as data size, selectivity, index design, query shape, sorting, and the overall workload.

Written by Shubhranshu Shekhar, who has trained 20000+ students in coding.

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