MongoDB MCQs – Performance Optimization

Performance optimization is critical for ensuring MongoDB operates efficiently in real-world applications. Techniques like creating indexes, using the query profiler, enabling journaling, and leveraging sharding significantly enhance database performance.

These MCQs cover essential concepts such as $explain for analyzing queries, $lookup for optimizing joins, and $merge for efficient aggregation. A solid understanding of these topics helps identify and resolve performance bottlenecks. Preparing with these MCQs ensures candidates can handle performance-related interview questions.

1.) Which command is used to analyze query performance in MongoDB?

A) db.collection.analyze()
B) db.collection.explain()
C) db.collection.profile()
D) db.collection.performance()

Answer: Option B

Explanation: The explain() method analyzes query performance by providing details about execution plans, indexes used, and query execution time.

2.) What is the purpose of the db.currentOp() command?

A) To display active queries and operations
B) To optimize query execution
C) To list all collections
D) To create indexes

Answer: Option A

Explanation: The db.currentOp() command shows currently running queries and operations on the server.

3.) Which index type is created by default for every MongoDB collection?

A) Compound index
B) Text index
C) Geospatial index
D) Single-field index on _id

Answer: Option D

Explanation: MongoDB automatically creates a single-field index on the _id field for every collection.

4.) How can you monitor slow queries in MongoDB?

A) By enabling the query profiler
B) By using the db.collection.index() command
C) By setting the mongo.logs file
D) By using the $lookup stage

Answer: Option A

Explanation: The MongoDB profiler captures slow queries and operations, helping identify performance bottlenecks.

5.) What does the wiredTiger storage engine use to optimize performance?

A) Locking entire collections
B) Document-level concurrency control
C) A single-threaded architecture
D) File-based locking

Answer: Option B

Explanation: The wiredTiger storage engine improves performance by using document-level locking, allowing multiple operations to run concurrently.

6.) Which of the following significantly improves query performance?

A) Avoiding queries with $or
B) Using large arrays
C) Creating indexes
D) Disabling validation

Answer: Option C

Explanation: Indexes improve query performance by reducing the number of documents MongoDB needs to scan.

7.) Which command provides statistics for a collection, including index usage?

A) db.collection.stats()
B) db.collection.explain()
C) db.collection.info()
D) db.collection.performance()

Answer: Option A

Explanation: The stats() method provides detailed information about a collection, including index usage and storage details.

8.) What is the impact of having too many indexes on a collection?

A) Slower read performance
B) Improved write performance
C) Increased disk space usage
D) Improved query performance

Answer: Option C

Explanation: Too many indexes can increase disk space usage and degrade write performance because indexes need to be updated during writes.

9.) Which of the following is the best practice for queries that filter on multiple fields?

A) Avoid using indexes
B) Use separate indexes for each field
C) Use $regex filters
D) Use a compound index

Answer: Option D

Explanation: Compound indexes improve query performance by supporting efficient filtering on multiple fields.

10.) Which of the following commands resets the query profiler?

A) db.resetProfiler()
B) db.setProfilingLevel(0)
C) db.system.profile.drop()
D) db.resetQueryLogs()

Answer: Option C

Explanation: Dropping the system.profile collection clears the profiler data and resets query profiling.

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