Top 100 MongoDB Interview Questions and Answers

MongoDB Interview Questions

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1. What is MongoDB?

Answer: MongoDB is a NoSQL database that stores data in a flexible, document-oriented format using JSON-like documents.

// Sample MongoDB document
{
  "_id": ObjectId("5f7200f8b3dabc1234567890"),
  "name": "John Doe",
  "age": 30,
  "email": "john@example.com"
}

2. Explain the term “NoSQL.”

Answer: NoSQL stands for “not only SQL.” It’s a type of database that doesn’t rely solely on traditional SQL relational databases. Instead, it offers flexible schema designs and horizontal scaling.


3. How is data stored in MongoDB?

Answer: MongoDB stores data in collections, which are similar to tables in relational databases. Each collection contains multiple documents, which are JSON-like structures.

// Inserting a document into a collection
db.users.insertOne({
  "name": "Alice",
  "age": 25
});

4. What is a document in MongoDB?

Answer: A document is a single record stored in a MongoDB collection. It consists of key-value pairs, similar to JSON objects.

// Example document
{
  "_id": ObjectId("5f7200f8b3dabc1234567890"),
  "name": "Jane Smith",
  "age": 28
}

5. What is a collection in MongoDB?

Answer: A collection is a group of MongoDB documents. It’s the equivalent of a table in relational databases.

// Creating a collection
db.createCollection("products");

6. How can you insert documents into a MongoDB collection?

Answer: Use the insertOne() or insertMany() methods to insert documents into a collection.

// Insert a single document
db.products.insertOne({
  "name": "Laptop",
  "price": 999
});

7. Explain the _id field in MongoDB.

Answer: The _id field is a unique identifier for documents in a collection. MongoDB automatically generates it if not provided during document insertion.

// Explicitly providing _id
db.orders.insertOne({
  "_id": ObjectId("5f7200f8b3dabc1234567891"),
  "product": "Phone",
  "quantity": 2
});

8. How can you query data from a MongoDB collection?

Answer: Use the find() method to query data. Provide conditions using query operators.

// Query documents with age greater than 25
db.users.find({ "age": { $gt: 25 } });

9. What is indexing in MongoDB?

Answer: Indexing improves query performance by creating an index on specific fields. It speeds up data retrieval but adds some overhead during updates.

// Creating an index on the "name" field
db.users.createIndex({ "name": 1 });

10. How can you update documents in MongoDB?

Answer: Use the updateOne() or updateMany() methods to modify documents.

// Update a single document
db.products.updateOne(
  { "name": "Laptop" },
  { $set: { "price": 899 } }
);

11. Explain the aggregation framework in MongoDB.

Answer: The aggregation framework is used to perform complex data transformations and manipulations on collections. It offers operators like $group, $match, and $project to reshape data.

// Example aggregation pipeline
db.sales.aggregate([
  { $match: { "date": { $gte: ISODate("2022-01-01") } } },
  { $group: { _id: "$product", totalSales: { $sum: "$quantity" } } }
]);

12. How can you delete documents from a MongoDB collection?

Answer: Use the deleteOne() or deleteMany() methods to remove documents.

// Delete a single document
db.users.deleteOne({ "name": "Alice" });

13. What is sharding in MongoDB?

Answer: Sharding is a technique to distribute data across multiple servers. It helps achieve horizontal scalability by splitting data into chunks and distributing them across nodes.

// Enabling sharding for a collection
sh.enableSharding("mydb");
sh.shardCollection("mydb.products", { "_id": "hashed" });

14. Explain the BSON data format used by MongoDB.

Answer: BSON (Binary JSON) is the binary-encoded serialization of JSON-like documents. It supports various data types and is efficient for storage and data exchange.


15. How can you perform text search in MongoDB?

Answer: Use the $text operator along with the text index to perform text search.

// Creating a text index
db

.articles.createIndex({ "content": "text" });

// Performing text search
db.articles.find({ $text: { $search: "MongoDB" } });

16. What is the difference between findOne() and find() methods?

Answer: findOne() returns a single document that matches the query, while find() returns a cursor that can iterate over multiple documents matching the query.

// Using findOne()
db.users.findOne({ "age": 30 });

// Using find()
const cursor = db.users.find({ "age": 30 });

17. How can you perform joins in MongoDB?

Answer: MongoDB supports noSQL-style joins using the $lookup aggregation stage. It lets you combine data from multiple collections based on a common field.

// Performing a join using $lookup
db.orders.aggregate([
  {
    $lookup: {
      from: "products",
      localField: "productId",
      foreignField: "_id",
      as: "productInfo"
    }
  }
]);

18. What is a capped collection in MongoDB?

Answer: A capped collection is a fixed-size collection that automatically overwrites older documents when it reaches its size limit. It’s useful for maintaining log-like data.

// Creating a capped collection
db.createCollection("logs", { capped: true, size: 100000 });

19. How can you create an index in MongoDB?

Answer: Use the createIndex() method to create indexes on one or more fields.

// Creating an index on the "name" field
db.users.createIndex({ "name": 1 });

// Creating a compound index
db.products.createIndex({ "category": 1, "price": -1 });

20. What is the use of the explain() method in MongoDB?

Answer: The explain() method provides information about the execution plan of a query. It helps analyze query performance and index usage.

// Using explain on a query
db.products.find({ "category": "Electronics" }).explain("executionStats");

21. How can you perform aggregation using the Map-Reduce model in MongoDB?

Answer: The Map-Reduce model involves writing JavaScript functions for map and reduce operations. It’s suitable for complex aggregation tasks but may be less efficient compared to the aggregation framework.

// Example Map-Reduce operations
var mapFunction = function() {
  emit(this.category, this.price);
};

var reduceFunction = function(key, values) {
  return Array.avg(values);
};

db.products.mapReduce(mapFunction, reduceFunction, {
  out: "average_prices_by_category"
});

22. What is the difference between a primary key and a secondary key in MongoDB?

Answer: In MongoDB, the _id field is the primary key, uniquely identifying each document. Secondary keys are indexes on other fields that enhance query performance.

// Creating a secondary index
db.products.createIndex({ "category": 1 });

23. How can you perform upserts in MongoDB?

Answer: Use the updateOne() method with the upsert option to perform an update that inserts a new document if no matching document exists.

// Performing an upsert
db.users.updateOne(
  { "email": "jane@example.com" },
  { $set: { "name": "Jane Doe" } },
  { upsert: true }
);

24. Explain the concept of a TTL (Time To Live) index in MongoDB.

Answer: A TTL index automatically deletes documents from a collection after a specified time period. It’s useful for storing data that has an expiration date.

// Creating a TTL index
db.logs.createIndex({ "createdAt": 1 }, { expireAfterSeconds: 3600 });

25. How can you perform array updates in MongoDB?

Answer: Use update operators like $push, $pull, $addToSet, etc., to modify arrays within documents.

// Adding an item to an array
db.users.updateOne(
  { "name": "John" },
  { $push: { "hobbies": "Gardening" } }
);

26. Explain the benefits of replica sets in MongoDB.

Answer: Replica sets provide data redundancy and high availability by maintaining multiple copies (replicas) of data across different servers. If the primary server fails, one of the replicas automatically becomes the new primary.

// Creating a replica set
rs.initiate();

27. How can you perform transactions in MongoDB?

Answer: Use the startSession() method and transaction functions to perform multi-document transactions.

// Starting a session
var session = db.getMongo().startSession();

// Running a transaction
session.startTransaction();
db.products.updateOne({ "_id": ObjectId("...") }, { $inc: { "quantity": -1 } });
db.orders

.insertOne({ "product": "Laptop", "quantity": 1 });
session.commitTransaction();
session.endSession();

28. What is the MongoDB Aggregation Pipeline?

Answer: The Aggregation Pipeline is a powerful tool to process data within MongoDB. It’s a series of stages that can perform transformations, filtering, sorting, and grouping on documents.

// Example aggregation pipeline
db.sales.aggregate([
  { $match: { "date": { $gte: ISODate("2023-01-01") } } },
  { $group: { _id: "$product", totalSales: { $sum: "$quantity" } } }
]);

29. How can you perform geospatial queries in MongoDB?

Answer: MongoDB supports geospatial queries using geospatial indexes and operators like $geoNear, $geoWithin, and $near.

// Creating a geospatial index
db.places.createIndex({ "location": "2dsphere" });

// Performing a geospatial query
db.places.find({ "location": { $near: { $geometry: { type: "Point", coordinates: [x, y] } } } });

30. Explain the concept of Aggregation Framework vs. Map-Reduce in MongoDB.

Answer: The Aggregation Framework is a flexible and powerful tool for data transformation, aggregation, and analysis. It’s often faster and more efficient than the Map-Reduce model, which involves writing custom JavaScript functions for map and reduce operations.

References:


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31. What is the MongoDB Atlas?

Answer: MongoDB Atlas is a cloud-based database service provided by MongoDB. It offers fully managed database clusters, automated backups, scaling, and security features, making it easier to deploy, manage, and scale MongoDB databases in the cloud.


32. How can you perform text search in MongoDB?

Answer: MongoDB provides text search capabilities using the $text operator. To perform text search, create a text index on the field you want to search within, and then use the $text operator in your queries.

// Creating a text index
db.articles.createIndex({ "content": "text" });

// Performing text search
db.articles.find({ $text: { $search: "MongoDB" } });

33. What is the purpose of the ObjectId data type in MongoDB?

Answer: The ObjectId data type is a 12-byte identifier used as the primary key for documents in MongoDB. It consists of a timestamp, a machine identifier, a process identifier, and a counter. It ensures uniqueness and allows for efficient indexing.


34. How can you backup and restore data in MongoDB?

Answer: MongoDB provides tools like mongodump and mongorestore for backing up and restoring data. Use mongodump to create binary dumps of the data, and mongorestore to restore the data from those dumps.

# Backup data
mongodump --db mydb --out /path/to/backup

# Restore data
mongorestore --db mydb /path/to/backup/mydb

35. Explain the concept of sharding in MongoDB.

Answer: Sharding is a method of distributing data across multiple machines to achieve horizontal scalability. Each machine or shard stores a portion of the data. MongoDB’s sharding enables databases to handle larger datasets and higher loads by distributing the workload.


36. What is the difference between SQL databases and MongoDB?

Answer: SQL databases are relational databases that use structured query language (SQL) for data manipulation. MongoDB is a NoSQL database that stores data in a JSON-like format and uses a flexible, schema-less model. MongoDB is better suited for dynamic and unstructured data, while SQL databases are better for structured data and complex queries.


37. How can you handle transactions in a sharded MongoDB environment?

Answer: MongoDB 4.0 introduced distributed transactions that allow multi-document transactions across multiple shards. Use startSession() to initiate a session, perform transactional operations, and commit/abort the session as needed.

// Starting a session
var session = db.getMongo().startSession();

// Running a transaction
session.startTransaction();
db.collection1.update({ "field1": value }, { $set: { "field2": newValue } });
db.collection2.insert({ "field3": value });
session.commitTransaction();
session.endSession();

38. How does MongoDB handle concurrency control?

Answer: MongoDB uses multi-version concurrency control (MVCC) to handle concurrency. Each document version maintains a unique _id and a version number. Reads can occur on older versions while writes create new versions. MVCC prevents conflicts between read and write operations.


39. What is the Aggregation Pipeline in MongoDB?

Answer: The Aggregation Pipeline is a framework that enables data transformation and aggregation. It consists of multiple stages like $match, $group, $project, etc., that process documents in sequence to perform complex data manipulations.

// Example aggregation pipeline
db.sales.aggregate([
  { $match: { "date": { $gte: ISODate("2023-01-01") } } },
  { $group: { _id: "$product", totalSales: { $sum: "$quantity" } } }
]);

40. How can you perform geospatial queries in MongoDB?

Answer: MongoDB supports geospatial queries using geospatial indexes and operators like $geoNear, $geoWithin, and $near.

// Creating a geospatial index
db.places.createIndex({ "location": "2dsphere" });

// Performing a geospatial query
db.places.find({ "location": { $near: { $geometry: { type: "Point", coordinates: [x, y] } } } });

41. What is a MongoDB aggregation cursor?

Answer: An aggregation cursor is a pointer to the result set of an aggregation operation. You can iterate through the cursor to access the documents resulting from the aggregation pipeline.

// Using an aggregation cursor
const cursor = db.orders.aggregate([
  { $match: { "status": "completed" } },
  { $group: { _id: "$product", totalSales: { $sum: "$quantity" } } }
]);

// Iterating through the cursor
cursor.forEach(printjson);

42. How can you optimize MongoDB queries?

Answer: MongoDB queries can be optimized by creating

appropriate indexes, using the explain() method to analyze query execution plans, avoiding large result sets with proper filtering, and considering data modeling for efficient queries.


43. Explain the concept of capped collections in MongoDB.

Answer: Capped collections are fixed-size collections that maintain insertion order. Once the collection reaches its maximum size, older documents are removed to make space for new documents. Capped collections are used for log storage and event tracking.

// Creating a capped collection
db.createCollection("logs", { capped: true, size: 1000000, max: 100 });

44. What is MongoDB Compass?

Answer: MongoDB Compass is a GUI tool provided by MongoDB for interacting with databases. It offers a user-friendly interface to visually explore and manipulate data, create queries, and perform data analysis.


45. How can you perform full-text search in MongoDB?

Answer: MongoDB provides full-text search capabilities using text indexes and the $text operator. Create a text index on the field you want to search, and use the $text operator to perform full-text searches.

// Creating a text index
db.articles.createIndex({ "content": "text" });

// Performing full-text search
db.articles.find({ $text: { $search: "MongoDB" } });

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

Answer: WiredTiger is the default storage engine in MongoDB since version 3.2. It provides features like compression, multi-version concurrency control (MVCC), and support for both document-level and collection-level locking, improving performance and efficiency.


47. How does MongoDB ensure high availability and fault tolerance?

Answer: MongoDB achieves high availability through replica sets. A replica set consists of primary and secondary nodes, where data is replicated from the primary to the secondaries. If the primary fails, a secondary can be elected as the new primary.


48. Explain the difference between embedded documents and references in MongoDB.

Answer: Embedded documents are nested within other documents and are stored within a single collection. References involve storing a reference to another document’s _id in a separate collection. Embedded documents are efficient for one-to-few relationships, while references are suitable for one-to-many or many-to-many relationships.


49. What is the Aggregation Framework in MongoDB?

Answer: The Aggregation Framework is a powerful tool for data transformation, analysis, and reporting in MongoDB. It consists of a pipeline of stages such as $match, $group, $sort, etc., which can be combined to perform complex operations on documents and generate meaningful insights.


50. How can you create an index in MongoDB?

Answer: Indexes in MongoDB improve query performance. Use the createIndex() method to create indexes on fields of a collection. MongoDB provides various types of indexes, such as single-field indexes, compound indexes, and text indexes.

// Creating a single-field index
db.collection.createIndex({ "field": 1 });

// Creating a compound index
db.collection.createIndex({ "field1": 1, "field2": -1 });

// Creating a text index
db.collection.createIndex({ "content": "text" });

References:


51. How does MongoDB handle schema changes?

Answer: MongoDB’s flexible schema allows adding or modifying fields without affecting existing documents. New fields are automatically added to documents, and queries can handle documents with varying structures.


52. What is the $lookup stage in the Aggregation Pipeline?

Answer: The $lookup stage in the Aggregation Pipeline performs a left outer join between two collections. It matches documents from the source collection with documents from the joined collection and combines matching documents into a single document.

// Using the $lookup stage
db.orders.aggregate([
  {
    $lookup: {
      from: "customers",
      localField: "customerId",
      foreignField: "_id",
      as: "customerDetails"
    }
  }
]);

53. How can you achieve data isolation in MongoDB?

Answer: Data isolation can be achieved using separate databases or by organizing collections within a single database. Proper access control and authentication ensure that different users or applications access only the relevant data.


54. Explain the usage of the $push operator in MongoDB.

Answer: The $push operator is used to append a value to an array field in a document. It is commonly used to add elements to arrays, such as adding items to a shopping cart or comments to a blog post.

// Using the $push operator
db.posts.update({ _id: postId }, { $push: { comments: newComment } });

55. How can you aggregate data using the $group stage?

Answer: The $group stage in the Aggregation Pipeline groups documents by a specified field and calculates aggregate values using aggregation operators like $sum, $avg, $min, $max, etc.

// Using the $group stage
db.sales.aggregate([
  {
    $group: {
      _id: "$product",
      totalSales: { $sum: "$quantity" },
      avgPrice: { $avg: "$price" }
    }
  }
]);

56. What is the purpose of the $unset operator in MongoDB?

Answer: The $unset operator removes a specified field from a document. It is useful for removing unnecessary or obsolete fields from documents.

// Using the $unset operator
db.products.update({ _id: productId }, { $unset: { oldField: "" } });

57. How can you improve MongoDB performance for read-heavy workloads?

Answer: To improve read-heavy performance, use appropriate indexes to optimize query execution, utilize read preference settings to distribute read operations, enable read scaling with replica sets, and use caching mechanisms like MongoDB’s in-memory storage engine.


58. What is the purpose of the explain() method in MongoDB?

Answer: The explain() method provides insights into how MongoDB executes a query. It returns details about the query plan, index usage, execution statistics, and more, helping developers analyze and optimize queries.

// Using the explain() method
db.collection.find({ field: value }).explain("executionStats");

59. How can you prevent data loss in MongoDB?

Answer: To prevent data loss, implement regular backups using tools like mongodump. Additionally, configure replica sets for automatic failover and data redundancy. Consider using MongoDB Atlas for managed backups and high availability.


60. Explain the role of the mongos process in MongoDB.

Answer: The mongos process acts as a query router in MongoDB sharded clusters. It directs client requests to the appropriate shard based on the sharding key and coordinates the overall query execution.


61. How does MongoDB handle network partitioning and split-brain scenarios?

Answer: MongoDB uses a voting mechanism among replica set members to avoid split-brain scenarios. A majority of members must be accessible for a primary to be elected. In network partitions, a secondary with higher priority and longer uptime is typically elected as the new primary.


62. What is the use of the $out stage in the Aggregation Pipeline?

Answer: The $out stage in the Aggregation Pipeline writes the resulting documents of an aggregation operation to a specified collection. It allows you to store the results of an aggregation pipeline for further analysis or reporting.

// Using the $out stage
db.orders.aggregate([
  { $group: { _id: "$product", totalSales: { $sum: "$quantity" } } },
  { $out: "productSalesSummary" }
]);

63. How can you implement data validation in MongoDB?

Answer: MongoDB 3.2 introduced data validation rules that enforce field constraints on documents. You can define validation rules using the validator option when creating a collection.

// Creating a collection with validation
db.create

Collection("users", {
  validator: {
    $jsonSchema: {
      bsonType: "object",
      required: ["name", "email"],
      properties: {
        name: { bsonType: "string" },
        email: { bsonType: "string", pattern: "^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$" }
      }
    }
  }
});

64. How can you implement transactions in MongoDB?

Answer: MongoDB supports multi-document transactions that allow you to perform multiple write operations as a single, atomic transaction. Use the startSession() method to create a session and the withTransaction() method to execute a transaction.

// Example of a transaction
session.startTransaction();
try {
  db.accounts.updateOne({ _id: fromAccountId }, { $inc: { balance: -amount } });
  db.accounts.updateOne({ _id: toAccountId }, { $inc: { balance: amount } });
  session.commitTransaction();
} catch (error) {
  session.abortTransaction();
}

References:


65. What is sharding in MongoDB, and why is it used?

Answer: Sharding is the process of distributing data across multiple servers (shards) to improve scalability and performance. It allows MongoDB to handle large datasets by horizontally partitioning data. Sharding is useful when data exceeds the capacity of a single server and enables better distribution of read and write operations.


66. How can you create a text index in MongoDB?

Answer: A text index enables text-based search capabilities. You can create a text index on a field that contains string content, such as product names or descriptions.

// Creating a text index
db.products.createIndex({ name: "text", description: "text" });

67. Explain the role of the mongod process in MongoDB.

Answer: The mongod process is the primary database process responsible for managing data storage, processing queries, and handling read and write operations. It manages the storage engine and interacts with client applications and drivers.


68. How can you perform a case-insensitive search in MongoDB?

Answer: To perform a case-insensitive search, use the $regex operator with the $options modifier set to "i".

// Performing a case-insensitive search
db.products.find({ name: { $regex: "keyword", $options: "i" } });

69. What is the significance of the _id field in MongoDB?

Answer: The _id field is a primary key for documents in MongoDB. It ensures the uniqueness of each document within a collection and is automatically indexed. MongoDB provides an _id value for each document by default, but you can specify your own values as well.


70. How can you implement time-to-live (TTL) indexes in MongoDB?

Answer: TTL indexes automatically remove documents from a collection after a specified time interval. Create a TTL index on a field that contains a timestamp, and MongoDB will delete documents older than the specified time.

// Creating a TTL index
db.logs.createIndex({ createdAt: 1 }, { expireAfterSeconds: 3600 });

71. Explain the use of the $regex operator in MongoDB.

Answer: The $regex operator is used for regular expression pattern matching in queries. It allows you to search for documents that match a specific pattern within a string field.

// Using the $regex operator
db.products.find({ name: { $regex: "keyword" } });

72. How can you ensure data consistency in a sharded MongoDB cluster?

Answer: MongoDB uses a two-phase commit process to ensure data consistency in a sharded cluster. When a transaction involves multiple shards, the mongos routers coordinate with the shards to commit or abort the transaction across all involved shards.


73. Explain the usage of the $redact stage in the Aggregation Pipeline.

Answer: The $redact stage is used to control access to documents by applying access control rules. It uses conditional expressions to determine which fields are visible or hidden in the output documents.

// Using the $redact stage
db.documents.aggregate([
  {
    $redact: {
      $cond: {
        if: { $eq: ["$level", 3] },
        then: "$$DESCEND",
        else: "$$PRUNE"
      }
    }
  }
]);

74. How can you monitor MongoDB performance?

Answer: MongoDB provides tools like mongostat and mongotop to monitor server performance. Additionally, MongoDB Atlas offers a comprehensive monitoring and alerting platform for cloud-hosted databases.


75. Explain the usage of the $min and $max operators in MongoDB.

Answer: The $min and $max operators are used in update operations to modify numeric or date fields with the minimum or maximum value among the provided values and the existing value.

// Using the $min and $max operators
db.products.update({ _id: productId }, { $min: { price: newPrice } });
db.products.update({ _id: productId }, { $max: { stock: newStock } });

76. How can you implement field-level encryption in MongoDB?

Answer: MongoDB supports field-level encryption to secure sensitive data at rest. Use the Client-Side Field Level Encryption (CSFLE) feature to encrypt and decrypt fields within a document using a master key stored outside of MongoDB.


77. Explain the role of the mongodump and mongorestore utilities.

Answer: The mongodump utility creates binary backups of MongoDB data. The mongorestore utility restores data from binary backup files created by mongodump. These utilities are useful for data backup and restoration.


78. How can you create an index on an array field in MongoDB?

Answer: To create an index on an array field, you can use the createIndex method and specify the field within an array.

// Creating an index on an array field
db.products.createIndex({ "tags": 1 });

79. Explain the usage of the $unwind operator in aggregation.

Answer: The $unwind operator is used to transform an array field into multiple documents, each containing a single array element. It’s often used before aggregation stages that require individual array elements to be processed separately.

// Using the $unwind operator
db.orders.aggregate([
  { $unwind: "$items" },
  { $group: { _id: "$items.product", totalQuantity: { $sum: "$items.quantity" } } }
]);

80. How can you find documents with distinct values in a specific field?

Answer: Use the distinct method to find unique values in a field.

// Finding distinct values
const uniqueNames = db.customers.distinct("name");

81. Explain the usage of the $lookup stage in aggregation.

Answer: The $lookup stage performs a left outer join between two collections. It combines documents from the source collection with matching documents from the joined collection.

// Using the $lookup stage
db.orders.aggregate([
  {
    $lookup: {
      from: "products",
      localField: "productId",
      foreignField: "_id",
      as: "productDetails"
    }
  }
]);

82. How can you enforce unique constraints on embedded documents in an array field?

Answer: You can use the $addToSet operator with the $each modifier to ensure uniqueness while adding elements to an array.

// Enforcing unique constraints
db.customers.update(
  { _id: customerId },
  { $addToSet: { orders: { $each: [{ orderDate: new Date(), total: 100 }] } } }
);

83. Explain the purpose of the WiredTiger storage engine in MongoDB.

Answer: The WiredTiger storage engine is the default storage engine in MongoDB since version 3.2. It provides features like compression, support for multiple storage structures, and improved concurrency control, resulting in better performance and efficiency.


84. How can you find the nth highest value in a field?

Answer: You can use the aggregate framework to find the nth highest value in a field.

// Finding the nth highest value
db.sales.aggregate([
  { $sort: { amount: -1 } },
  { $skip: n - 1 },
  { $limit: 1 }
]);

85. Explain the role of the mongoreplay tool.

Answer: The mongoreplay tool captures network traffic between MongoDB clients and servers and allows you to replay the captured traffic to test the behavior of MongoDB deployments and applications.


86. How can you perform full-text search in MongoDB?

Answer: MongoDB provides the $text operator to perform full-text search on text-indexed fields. You can use it along with the $search expression to find documents containing specific words or phrases.

// Performing full-text search
db.articles.find({ $text: { $search: "search keywords" } });

87. Explain the usage of the $facet stage in aggregation.

Answer: The $facet stage enables you to run multiple aggregation pipelines in a single stage. Each pipeline within $facet produces an independent set of results that are grouped together in the output.

// Using the $facet stage
db.sales.aggregate([
  {
    $facet: {
      totalSales: [{ $group: { _id: null, total: { $sum: "$amount" } } }],
      averageAmount: [{ $group: { _id: null, avg: { $avg: "$amount" } } }]
    }
  }
]);

88. How can you update multiple documents with different values in MongoDB?

Answer: You can use the bulkWrite method to perform multiple update operations in a single request.

// Updating multiple documents
db.products.bulkWrite([
  { updateOne: { filter: { category: "electronics" }, update: { $set: { discount: 0.2 } } } },
  { updateOne: { filter: { category: "clothing" }, update: { $set: { discount: 0.1 } } } }
]);

89. Explain the purpose of the mongotop tool.

Answer: The mongotop tool provides a real-time view of the read and write activity on a MongoDB instance, organized by collection. It helps identify performance bottlenecks and resource utilization.


90. How can you retrieve only a specific range of elements from an array field?

Answer: You can use the `$ slice` projection operator to retrieve a specific range of elements from an array field.

// Retrieving a range of elements
db.students.find({ _id: studentId }, { scores: { $slice: [start, count] } });

91. Explain the usage of the $out stage in aggregation.

Answer: The $out stage writes the output of an aggregation pipeline to a specified collection. It’s useful when you want to save the results of an aggregation pipeline as a new collection.

// Using the $out stage
db.sales.aggregate([
  { $group: { _id: "$product", totalSales: { $sum: "$amount" } } },
  { $out: "product_sales" }
]);

92. How can you find documents where a field matches any value in an array?

Answer: You can use the $in operator to find documents where a field matches any value in an array.

// Finding documents using the $in operator
db.products.find({ category: { $in: ["electronics", "clothing"] } });

93. Explain the role of the mongoimport tool.

Answer: The mongoimport tool imports data from various file formats into a MongoDB collection. It supports JSON, CSV, and TSV formats, allowing you to populate your MongoDB databases with external data.


94. How can you perform aggregation on arrays in documents?

Answer: You can use aggregation operators like $unwind, $group, $project, and others to perform complex operations on arrays within documents.

// Aggregating arrays within documents
db.orders.aggregate([
  { $unwind: "$items" },
  { $group: { _id: "$customerId", totalAmount: { $sum: "$items.amount" } } }
]);

95. Explain the purpose of the mongostat tool.

Answer: The mongostat tool provides a view of the real-time performance statistics of a running MongoDB instance. It displays data about connections, memory usage, and various metrics that help monitor the database’s health.


96. How can you create a text index on a collection?

Answer: To create a text index, you can use the createIndex method with the text index type.

// Creating a text index
db.articles.createIndex({ content: "text" });

97. Explain the $regex operator for pattern matching.

Answer: The $regex operator is used in queries to perform pattern matching using regular expressions. It allows you to search for documents where a field matches a specified regular expression.

// Using the $regex operator
db.customers.find({ name: { $regex: /^Joh/ } });

98. How can you perform case-insensitive searches in MongoDB?

Answer: To perform case-insensitive searches, you can use the $regex operator along with the $options modifier.

// Case-insensitive search using the $regex operator
db.users.find({ username: { $regex: "john", $options: "i" } });

99. Explain the usage of the mongodump tool.

Answer: The mongodump tool creates a binary export of the data stored in a MongoDB instance. It’s useful for creating backups or moving data between different environments.


100. How can you drop a collection in MongoDB?

Answer: You can use the drop method to remove an entire collection from the database.

// Dropping a collection
db.products.drop();