MongoDB interview.

As an AI language model, I can provide you with some common interview questions and possible answers to help you prepare for a MongoDB interview.

1. What is MongoDB?

• MongoDB is a NoSQL document-oriented database management system that allows for the storage and retrieval of data in a flexible and scalable manner. It uses a document data model, which means that data is stored in JSON-like documents that can be nested, making it easier to represent complex data structures.

2. What is a document in MongoDB?

• A document in MongoDB is a record in a collection that is stored as a JSON-like structure. Each document has a unique ID, and it can contain multiple fields, each of which stores a value.

3. What is a collection in MongoDB?

• A collection in MongoDB is a grouping of documents. It is similar to a table in a traditional relational database.

4. What is sharding in MongoDB?

• Sharding is the process of partitioning data across multiple machines in a distributed database system like MongoDB. It allows for horizontal scaling of data and ensures that data is evenly distributed across different shards.

5. What is replication in MongoDB?

• Replication in MongoDB is the process of copying data across multiple machines to ensure that data is always available even if one machine fails. MongoDB uses a primary-secondary replication model, where one machine is designated as the primary and the others as secondary machines that mirror the data.

6. What is indexing in MongoDB?

• Indexing in MongoDB is the process of creating indexes on specific fields in a collection to optimize query performance. Indexes allow for faster searches, sorting, and filtering of data.

7. What is a TTL index in MongoDB?

• A TTL (Time-To-Live) index in MongoDB is an index that automatically deletes documents from a collection after a specified amount of time. This is useful for storing temporary data or data that is only relevant for a certain amount of time.

8. What is GridFS in MongoDB?

• GridFS is a file storage system used in MongoDB for storing and retrieving large files, such as images and videos. It stores files in multiple chunks, allowing for efficient storage and retrieval of large files.

9. What is the difference between MongoDB and MySQL?

• MongoDB is a NoSQL document-oriented database management system, while MySQL is a traditional relational database management system. MongoDB is designed for scalability, flexibility, and handling unstructured data, while MySQL is designed for structured data and transactions.

10. What are some advantages of using MongoDB?

• MongoDB offers high scalability, flexible data modeling, automatic sharding, and high availability. It also has a rich query language, supports geospatial indexing, and is easy to use and maintain.

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11. What are the different types of indexes in MongoDB?

• There are several types of indexes in MongoDB, including single-field indexes, compound indexes, multikey indexes, text indexes, and geospatial indexes.

12. How does MongoDB handle transactions?

• MongoDB supports multi-document transactions in versions 4.0 and above. Transactions allow for atomicity, consistency, isolation, and durability (ACID) properties in a distributed database system.

13. What is the role of the MongoDB Connector for BI?

• The MongoDB Connector for BI allows for the integration of MongoDB data with popular business intelligence (BI) tools, such as Tableau and Power BI. It provides a SQL interface to query MongoDB data using BI tools.

14. How does MongoDB handle backups and restores?

• MongoDB provides several options for backups and restores, including point-in-time backups, continuous backups, and cloud-based backups. It also supports backup compression and encryption for secure and efficient backups.

15. What is the difference between find() and findOne() methods in MongoDB?

• The find() method in MongoDB returns a cursor to a collection that can be used to iterate over multiple documents. The findOne() method, on the other hand, returns a single document that matches a specified query.

16. What is MapReduce in MongoDB?

• MapReduce is a data processing technique used in MongoDB to analyze large datasets. It involves mapping data to key-value pairs, reducing the data by aggregating values for each key, and then returning the results.

17. How does MongoDB handle schema changes?

• MongoDB is schemaless, meaning that it does not enforce a fixed schema for collections. This makes it easy to handle schema changes, as new fields can be added to documents without affecting the existing ones.

18. What is a capped collection in MongoDB?

• A capped collection in MongoDB is a fixed-size collection that has a maximum number of documents or maximum storage size. Once the maximum size is reached, new documents overwrite the oldest ones.

19. How does MongoDB handle security?

• MongoDB provides several security features, including role-based access control, SSL/TLS encryption, authentication mechanisms, and auditing capabilities. It also offers integration with external authentication services, such as LDAP and Kerberos.

20. What is the MongoDB Atlas?

• MongoDB Atlas is a fully managed cloud database service for MongoDB. It provides features such as automated backups, high availability, and scalability, making it easy to deploy and manage MongoDB clusters in the cloud.

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21. What is the difference between a primary and secondary node in MongoDB?

• In a MongoDB replica set, the primary node is responsible for accepting writes and reading data from the database, while the secondary nodes replicate the primary data and can be used for reads in case of primary node failure.

22. How does MongoDB handle data consistency in a distributed environment?

• MongoDB uses a replica set architecture to ensure data consistency in a distributed environment. In a replica set, data is replicated across multiple nodes, and the primary node is responsible for maintaining the consistency of the data.

23. What is a change stream in MongoDB?

• A change stream in MongoDB is a feature that allows applications to monitor changes in a MongoDB collection in real-time. It can be used to notify applications of changes made to the data and trigger actions based on those changes.

24. What is a projection in MongoDB?

• A projection in MongoDB is a feature that allows applications to retrieve only specific fields from a collection instead of returning the entire document. This can help optimize query performance and reduce network traffic.

25. What is the difference between a collection and a database in MongoDB?

• A database in MongoDB is a logical container for collections, while a collection is a grouping of documents that share a common schema. Multiple collections can be stored within a single database.

26. What is the MongoDB Aggregation Framework?

• The MongoDB Aggregation Framework is a set of tools and operators used to perform complex data aggregation operations, such as grouping, filtering, and sorting, on MongoDB collections.

27. What is a partial index in MongoDB?

• A partial index in MongoDB is an index that is created on a subset of documents in a collection. It can help optimize query performance by only indexing the documents that are relevant to the query.

28. How does MongoDB handle data locality?

• MongoDB uses a sharded architecture to handle data locality in a distributed environment. In a sharded cluster, data is partitioned into chunks and distributed across multiple nodes based on a shard key. This ensures that data is stored on nodes that are geographically close to the users accessing it.

29. What is a covered query in MongoDB?

• A covered query in MongoDB is a query that can be satisfied entirely using the index without needing to access the underlying documents in the collection. This can help optimize query performance and reduce disk I/O.

30. How does MongoDB handle concurrency?

• MongoDB uses a locking mechanism to handle concurrency in a multi-threaded environment. In a replica set, the primary node uses a write lock to ensure that only one write operation can occur at a time. In a sharded cluster, each shard uses a separate write lock.

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31. What is the role of the WiredTiger storage engine in MongoDB?

• WiredTiger is the default storage engine in MongoDB 3.2 and above. It provides features such as compression, document-level locking, and efficient storage for large datasets.

32. What is a TTL index in MongoDB?

• A TTL (Time To Live) index in MongoDB is an index that automatically deletes documents from a collection after a certain period of time. It is commonly used for expiring session data or log data.

33. What is the role of the oplog in MongoDB?

• The oplog (operation log) in MongoDB is a capped collection that records all write operations to a replica set. It is used for replication and allows secondary nodes to catch up with the primary node.

34. What is the difference between a shard key and a primary key in MongoDB?

• A shard key in MongoDB is used to partition data across multiple nodes in a sharded cluster, while a primary key is used to uniquely identify documents in a collection.

35. What is the role of the balancer in MongoDB?

• The balancer in MongoDB is a process that moves chunks of data between shards in a sharded cluster. It ensures that data is evenly distributed across the cluster and helps maintain performance.

36. What is the role of the mongos process in MongoDB?

• The mongos process in MongoDB is a router that sits between the application and the sharded cluster. It routes queries to the appropriate shards and merges the results before returning them to the application.

37. What is the difference between a hard and soft limit in MongoDB?

• A hard limit in MongoDB is a limit that cannot be exceeded, while a soft limit is a limit that can be exceeded temporarily. MongoDB uses both types of limits for resource management, such as memory usage or file size.

38. What is a write concern in MongoDB?

• A write concern in MongoDB is a parameter that controls the level of acknowledgement a write operation receives from the replica set. It can be used to ensure that data is written to multiple nodes for durability and consistency.

39. What is the role of the profiler in MongoDB?

• The profiler in MongoDB is a feature that logs database operations for analysis and optimization. It can be used to identify slow queries or inefficient indexes.

40. What is the MongoDB Compass?

• The MongoDB Compass is a graphical user interface (GUI) tool for MongoDB. It provides a visual representation of the data, schema, and indexes in a collection, and allows for easy querying and data manipulation.