MongoDB

MongoDB is a cross-platform document-oriented database program. Are you looking for a job as a MongoDB Developer, try these interview questions in MongoDB to ace the job interview.

Q.1 Which parameter in config file is used for storing mongodb output?
logpath is used for storing mongodb output
Q.2 How do you create a new document in MongoDB?
To create a new document in MongoDB, you would use the insertOne() or insertMany() method in the MongoDB shell or any MongoDB driver. For example, in the MongoDB shell, to insert a single document, you would use db.collectionName.insertOne({ field1: value1, field2: value2 }).
Q.3 Can you explain the difference between insertOne() and insertMany() methods?
insertOne() is used to insert a single document, while insertMany() is used to insert multiple documents in a single operation. insertMany() takes an array of documents as input and inserts them in one batch, which can be more efficient than using insertOne() multiple times for each document.
Q.4 How can you update a specific document in MongoDB?
MongoDB provides the updateOne() method to update a specific document matching a given filter. For instance, to update a document where the field "name" is "John", you would use db.collectionName.updateOne({ name: "John" }, { $set: { age: 30 } }). This would update the "age" field to 30 in the first document matching the filter.
Q.5 What is the purpose of the $set operator in MongoDB updates?
The $set operator is used to update specific fields within a document without affecting other fields. It allows you to modify existing fields' values or add new fields to the document without altering the entire structure.
Q.6 How do you delete a document in MongoDB?
To delete a document in MongoDB, you can use the deleteOne() method to remove a single document matching a filter. For example, db.collectionName.deleteOne({ field: value }) will remove the first document that matches the specified filter.
Q.7 Explain the significance of indexes in document management in MongoDB.
Indexes in MongoDB improve query performance by allowing the database to find and retrieve documents more efficiently. They work similarly to indexes in traditional databases, helping to speed up the search and retrieval of data based on indexed fields.
Q.8 What happens if you try to insert a document without specifying an "_id" field?
If you insert a document without specifying an "_id" field, MongoDB will automatically generate a unique ObjectId for that document. This ObjectId serves as the primary key for the document and ensures its uniqueness within the collection.
Q.9 How can you enforce unique constraints on a specific field during document insertion?
To enforce unique constraints on a field, you can create a unique index on that field using the createIndex() method with the unique option set to true. This will prevent the insertion of duplicate values in that field.
Q.10 What is the role of "upsert" in MongoDB updates?
"Upsert" is a combination of "update" and "insert." When performing an update with the updateOne() method with the upsert option set to true, if the filter matches a document, it will be updated. However, if no matching document is found, a new document will be inserted based on the update criteria.
Q.11 How can you perform bulk updates in MongoDB efficiently?
To perform bulk updates efficiently, you can use the bulkWrite() method. This allows you to execute multiple update operations in a single batch, reducing the number of round-trips to the server and improving overall performance.
Q.12 What are the differences between the updateOne() and updateMany() methods in MongoDB?
updateOne() updates the first document that matches the filter, while updateMany() updates all documents that match the filter. Use updateOne() when you want to modify a single document and updateMany() when you want to update multiple documents simultaneously.
Q.13 How can you perform a partial update on a document in MongoDB?
To perform a partial update, you can use various update operators such as $set, $unset, $inc, etc. The $set operator is used to update specific fields, $unset to remove fields, and $inc to increment numeric field values.
Q.14 Explain the purpose of the findAndModify command in MongoDB.
The findAndModify command is used to atomically find and update a document in a single operation. It allows you to retrieve the document before updating it, making it useful for scenarios requiring read-before-write behavior.
Q.15 How can you delete multiple documents that match a given filter in MongoDB?
To delete multiple documents matching a filter, you can use the deleteMany() method. For example, db.collectionName.deleteMany({ field: value }) will remove all documents matching the specified filter.
Q.16 What is the purpose of the multi option in update operations?
The multi option (also known as multi: true) is used to update multiple documents at once when performing an update operation. By default, only the first matching document is updated. Setting multi: true ensures that all matching documents are updated.
Q.17 How do you create a unique index on multiple fields in MongoDB?
To create a unique index on multiple fields, you can use the createIndex() method with the unique option set to true and specifying the fields as an array in the index definition.
Q.18 Can you revert a delete operation in MongoDB after executing it?
No, MongoDB does not have a built-in undo or rollback feature for delete operations. Once a document is deleted, it cannot be directly restored unless you have taken backups or have some form of replication set up.
Q.19 What are the benefits of sharding in a MongoDB cluster?
Sharding distributes data across multiple servers (shards) to improve scalability and performance. It allows MongoDB to handle large datasets and heavy workloads by horizontally partitioning the data, ensuring even distribution and efficient queries.
Q.20 How do you update nested fields within a document in MongoDB?
To update nested fields, you can use the dot notation to specify the path to the nested field. For example, db.collectionName.updateOne({ "nestedField.subField": value }, { $set: { "nestedField.subField": newValue } }) will update the specified nested field.
Q.21 How can you ensure that a document adheres to a predefined schema in MongoDB?
MongoDB is schema-less, but you can enforce some level of schema validation using the createCollection() method with the validator option. This allows you to define rules for the structure and data types of fields, ensuring documents meet certain criteria.
Q.22 What is the basic syntax to perform a data query in MongoDB?
The basic syntax to perform a data query in MongoDB is by using the find() method. For example, db.collectionName.find({ field: value }) retrieves all documents in the collection where the specified field matches the given value.
Q.23 How can you limit the number of documents returned in a MongoDB query?
You can use the limit() method to restrict the number of documents returned in a MongoDB query. For instance, db.collectionName.find({}).limit(10) will return only the first 10 documents from the collection.
Q.24 What is an index in MongoDB, and how does it improve query performance?
An index in MongoDB is a data structure that optimizes the search for documents based on the indexed fields. It improves query performance by reducing the number of documents that need to be scanned, making the query execution faster.
Q.25 How do you create an index on a specific field in MongoDB?
To create an index on a specific field, you can use the createIndex() method. For example, db.collectionName.createIndex({ field: 1 }) creates an ascending index on the "field" in the "collectionName" collection.
Q.26 What are the different types of indexes available in MongoDB?
MongoDB supports several types of indexes, including single field indexes, compound indexes (indexes on multiple fields), text indexes for text search, geospatial indexes for geospatial queries, and hashed indexes for hash-based sharding.
Q.27 How can you check if an index is being used by a query in MongoDB?
You can use the explain() method to get information about the query execution plan, including whether an index was used. Running db.collectionName.find({ field: value }).explain("executionStats") will provide details on index usage and query performance.
Q.28 Explain the concept of covered queries in MongoDB.
A covered query is a query that can be entirely satisfied using the index without needing to access the actual documents in the collection. It is more efficient because it avoids the extra step of fetching the actual data from disk.
Q.29 Can you create an index on an array field in MongoDB?
Yes, you can create an index on an array field in MongoDB. By default, the index will be created on the whole array as a single value. However, you can use dot notation to index specific elements within the array.
Q.30 How can you drop an index in MongoDB?
To drop an index, you can use the dropIndex() method. For example, db.collectionName.dropIndex({ field: 1 }) will remove the index on the "field" in the "collectionName" collection.
Q.31 What factors should you consider when deciding whether to create an index on a field?
When deciding whether to create an index on a field, consider factors such as the frequency of queries on that field, the size of the collection, the selectivity of the field (how many unique values it has), and the impact of index maintenance on write operations.
Q.32 What is the purpose of Map-Reduce in MongoDB?
Map-Reduce is a data processing paradigm used to aggregate and analyze large datasets in MongoDB. It involves two stages: "Map," where data is grouped and processed, and "Reduce," where the grouped data is combined to produce the final results.
Q.33 How is Map-Reduce different from the Aggregation Framework in MongoDB?
The Aggregation Framework is a more powerful and efficient alternative to Map-Reduce for data processing and analysis in MongoDB. While both can perform similar tasks, the Aggregation Framework is designed to handle most data processing needs and is generally preferred over Map-Reduce due to its performance advantages.
Q.34 What is the syntax to execute a Map-Reduce operation in MongoDB?
To execute a Map-Reduce operation, you use the mapReduce() method in MongoDB. The method takes the map function, reduce function, and optional parameters as arguments. For example, db.collectionName.mapReduce(mapFunction, reduceFunction, { out: "outputCollection" }).
Q.35 How does the Aggregation Framework work in MongoDB?
The Aggregation Framework in MongoDB uses a pipeline of stages to transform and process data. Each stage performs a specific operation on the data, such as filtering, grouping, projecting, sorting, etc. The output of each stage becomes the input to the next stage, allowing complex data processing.
Q.36 What are some advantages of using the Aggregation Framework over Map-Reduce?
The Aggregation Framework provides better performance, as it can take advantage of indexes, uses native BSON data format, and is optimized for data processing in MongoDB. Additionally, its expressive and concise syntax makes it easier to read and write complex data transformations.
Q.37 How can you perform a basic aggregation using the Aggregation Framework?
To perform a basic aggregation, you can use the $group stage to group data based on a specific field and then apply aggregation operators like $sum, $avg, $max, $min, etc., to calculate desired values. For example, { $group: { _id: "$field", total: { $sum: "$quantity" } } }.
Q.38 What is the purpose of the $project stage in the Aggregation Framework?
The $project stage is used to reshape the documents in the pipeline. It can include or exclude fields, add new fields with computed values, and rename fields, allowing you to customize the output structure of the aggregation results.
Q.39 How can you optimize an aggregation pipeline in MongoDB?
To optimize an aggregation pipeline, you can strategically place early stages that use indexes to filter and reduce the data as much as possible before applying more computationally intensive stages. Additionally, using the $match stage early in the pipeline can help in pushing down filtering to the earliest possible stage.
Q.40 Can you use the Aggregation Framework for data transformation and data cleansing?
Yes, the Aggregation Framework is suitable for data transformation and cleansing tasks. It allows you to reshape and modify data, perform data type conversions, filter out irrelevant information, and aggregate data to make it more suitable for analysis or reporting.
Q.41 How can you handle large-scale data processing with the Aggregation Framework?
For large-scale data processing, you can take advantage of MongoDB's sharding capabilities, which distribute data across multiple shards. By properly sharding your data, you can leverage the Aggregation Framework to process data in parallel across shards, improving performance and scalability.
Q.42 What is a DBRef in MongoDB, and when should you use it?
A DBRef (Database Reference) is a way to reference documents from one collection in another collection. It consists of the referenced collection name, the document's ObjectId, and optionally the database name. DBRefs are typically used when establishing relationships between documents in different collections.
Q.43 Explain the db.eval() method in MongoDB and its use cases.
The db.eval() method allows you to execute JavaScript code on the server directly. It is rarely used in production environments due to security and performance concerns. However, it can be helpful for quick testing and debugging purposes.
Q.44 What is GridFS in MongoDB, and why is it used?
GridFS is a specification in MongoDB used for storing and retrieving large files, such as images, videos, and other binary data, that exceed the BSON document size limit (16 MB). GridFS divides files into smaller chunks and stores them as separate documents, enabling efficient file handling and retrieval.
Q.45 How do you store a file using GridFS in MongoDB?
To store a file using GridFS, you can use the mongofiles command-line tool or the drivers' APIs. For example, using the mongofiles tool, you would execute mongofiles put filename to store a file named "filename" in GridFS.
Q.46 What are the advantages of using GridFS over storing files directly in the MongoDB collection?
GridFS provides several advantages, such as the ability to store files larger than 16 MB, efficient file retrieval, easy replication of large files across a sharded cluster, and better handling of small updates to large files without re-uploading the entire file.
Q.47 Explain what capped collections are in MongoDB and their use case.
Capped collections are fixed-size collections that have a constant insertion order. Once a capped collection reaches its specified size, new data overwrites the oldest data, like a circular buffer. They are often used for logging or storing event data where old data can be automatically discarded once the collection is full.
Q.48 How can you create a capped collection in MongoDB?
To create a capped collection, you can use the createCollection() method with the capped: true option and specify the size in bytes or the maximum number of documents the collection should hold.
Q.49 Can you modify the size of a capped collection after it has been created?
No, you cannot modify the size of a capped collection after it has been created. Once a capped collection is defined, its size and other options are fixed and cannot be altered. To change the size, you need to create a new capped collection with the desired size and migrate the data.
Q.50 How does MongoDB ensure data consistency in GridFS?
In GridFS, file chunks are stored separately, but MongoDB ensures data consistency by using an internal two-phase commit mechanism. When writing a file, both the file metadata and its chunks are committed together, ensuring that either all the data is successfully stored, or none of it is.
Q.51 Can you use indexes in GridFS to improve file retrieval performance?
No, GridFS does not support indexes on file data. However, it is possible to use regular collection indexes on the files collection to optimize queries for file metadata, such as filenames or metadata fields.
Q.52 How do you start a MongoDB instance?
To start a MongoDB instance, you can run the mongod command, which starts the MongoDB daemon process. For example, mongod --dbpath /data/db starts the MongoDB instance with the data directory set to /data/db.
Q.53 What is the purpose of the --bind_ip option in the mongod command?
The --bind_ip option specifies the network interface on which the MongoDB instance should listen for incoming connections. By default, MongoDB listens on all available network interfaces, but you can use --bind_ip to restrict connections to specific IP addresses.
Q.54 How can you shut down a running MongoDB instance gracefully?
To shut down a running MongoDB instance gracefully, you can use the db.shutdownServer() method in the MongoDB shell. Alternatively, you can send a SIGINT signal (CTRL+C) to the mongod process in the terminal where it is running.
Q.55 What is the purpose of the --fork option in the mongod command?
The --fork option is used to run the mongod process as a background job. It is commonly used in production environments to detach the MongoDB instance from the terminal and run it as a background service.
Q.56 How can you check the status of a MongoDB instance?
To check the status of a MongoDB instance, you can use the rs.status() or db.serverStatus() method in the MongoDB shell. It provides information about the replication status, server metrics, and other relevant details.
Q.57 Explain how to take a backup of a running MongoDB instance.
To take a backup of a running MongoDB instance, you can use tools like mongodump or filesystem snapshots. mongodump is a built-in MongoDB tool that creates a binary export of the data, while filesystem snapshots take a point-in-time copy of the data directory.
Q.58 What happens when a MongoDB instance runs out of disk space during operation?
When a MongoDB instance runs out of disk space, it may result in write failures and potential data corruption. It is essential to monitor disk space regularly and take appropriate actions, such as scaling up storage or archiving data, to prevent such scenarios.
Q.59 How can you enable authentication on a MongoDB instance?
To enable authentication on a MongoDB instance, you need to start the instance with the --auth option. This will enforce authentication for all client connections, requiring users to provide valid credentials to access the database.
Q.60 What is the purpose of the --repair option in the mongod command?
The --repair option performs a repair operation on a MongoDB instance, checking and repairing any corrupted data files. It is typically used when there are suspected data integrity issues.
Q.61 How can you upgrade a MongoDB instance to a newer version?
To upgrade a MongoDB instance to a newer version, you need to follow the recommended upgrade procedure provided in the MongoDB documentation. This usually involves stopping the current instance, performing a backup, installing the new version, and then starting the upgraded instance.
Q.62 What is the Admin interface in MongoDB?
The Admin interface in MongoDB is a web-based user interface that provides a graphical way to interact with and manage MongoDB deployments. It allows administrators to monitor server status, manage databases, collections, users, and perform various administrative tasks.
Q.63 How can you access the Admin interface in MongoDB?
The Admin interface is accessed through the web browser by navigating to the MongoDB instance's IP address or hostname followed by the default port number 8080. For example, http://localhost:8080/.
Q.64 What are the benefits of using the Admin interface for MongoDB administration?
The Admin interface provides a user-friendly way to visualize and manage MongoDB deployments, making it easier for administrators to monitor server metrics, analyze performance, and perform administrative tasks without relying solely on the command-line interface.
Q.65 How can you secure the Admin interface to prevent unauthorized access?
It is recommended to secure the Admin interface by enabling authentication on the MongoDB instance and setting up proper access control. This ensures that only authenticated users with appropriate privileges can access the Admin interface.
Q.66 What is serverStatus in MongoDB, and what information does it provide?
The serverStatus command in MongoDB returns various statistics and metrics about the current state of the server. It provides information on database operations, memory usage, network utilization, replication status, index utilization, and more.
Q.67 How can you execute the serverStatus command in MongoDB?
To execute the serverStatus command, you can use the db.runCommand({ serverStatus: 1 }) method in the MongoDB shell. It will return a document with detailed server statistics.
Q.68 Explain the significance of serverStatus metrics like "connections," "opcounters," and "memory".
"Connections" represents the number of current client connections to the MongoDB server. "Opcounters" provide information about the number of database operations (inserts, queries, updates, etc.) performed. "Memory" displays memory usage details, including resident, virtual, and mapped memory.
Q.69 How can you use serverStatus metrics to diagnose performance issues in MongoDB?
By monitoring serverStatus metrics, you can identify potential performance bottlenecks, such as high connection usage, excessive operations, or memory pressure. Analyzing these metrics helps in understanding the overall health and performance of the MongoDB deployment.
Q.70 Can you automate the collection of serverStatus metrics for ongoing monitoring?
Yes, you can automate the collection of serverStatus metrics by using external monitoring tools or MongoDB's built-in tools like MongoDB Cloud Manager or Ops Manager. These tools can collect and visualize server statistics over time for effective monitoring and troubleshooting.
Q.71 What are some other useful commands for monitoring and managing MongoDB instances?
Some other useful commands include db.stats() to get database statistics, db.currentOp() to view current operations, db.killOp() to terminate an operation, and db.getLogs() to retrieve MongoDB log messages, among others.
Q.72 How can you enable authentication in MongoDB to enhance security?
Authentication can be enabled by starting the MongoDB instance with the --auth option. This enforces that clients must provide valid credentials to access the MongoDB deployment.
Q.73 What are the default authentication mechanisms available in MongoDB?
MongoDB supports several authentication mechanisms, including SCRAM-SHA-256 (default as of MongoDB 4.0), SCRAM-SHA-1, and MONGODB-CR (legacy). SCRAM-SHA-256 is recommended for improved security.
Q.74 How do you create a user with specific privileges in MongoDB?
To create a user with specific privileges, you can use the db.createUser() method in the MongoDB shell or MongoDB administration tools. For example, db.createUser({ user: "username", pwd: "password", roles: [{ role: "readWrite", db: "databaseName" }] }) creates a user with read-write access to the "databaseName" database.
Q.75 What are the recommended practices for managing MongoDB user credentials securely?
Recommended practices include using strong passwords, avoiding using common or default usernames, regularly rotating passwords, and utilizing external authentication providers like LDAP or Kerberos where possible.
Q.76 How can you enforce SSL encryption for secure communication between MongoDB clients and servers?
SSL encryption can be enabled by configuring MongoDB to use a TLS/SSL certificate. This ensures that all communication between clients and servers is encrypted, protecting data in transit.
Q.77 Explain the role of Role-Based Access Control (RBAC) in MongoDB security.
RBAC in MongoDB allows administrators to assign specific roles to users, defining the privileges they have on databases and collections. It provides a granular level of control over access, ensuring users only have the necessary permissions.
Q.78 How do you restrict network access to MongoDB to enhance security?
You can restrict network access by specifying the bindIp configuration option in the MongoDB configuration file. Set it to the IP addresses or network interfaces from which MongoDB should accept incoming connections.
Q.79 What is the purpose of enabling auditing in MongoDB?
Enabling auditing allows MongoDB to log operations performed on the database, including authentication events, CRUD operations, and system events. It helps in compliance, security analysis, and troubleshooting.
Q.80 How can you enable auditing in MongoDB?
Auditing can be enabled by setting the auditLog configuration option in the MongoDB configuration file or using command-line options. You can specify the audit log path and filtering options as needed.
Q.81 What is the potential risk of using the db.eval() method in MongoDB from a security perspective?
The db.eval() method allows executing arbitrary JavaScript code on the server, which poses a significant security risk if not handled carefully. It is generally not recommended for security reasons and has been deprecated in MongoDB 4.4.
Q.82 How do you perform a backup of a MongoDB database?
To perform a backup of a MongoDB database, you can use the mongodump tool, which creates a binary export of the data. For example, mongodump --db databaseName creates a backup of the "databaseName" database.
Q.83 What is the purpose of point-in-time backups in MongoDB?
Point-in-time backups capture the database state at a specific moment, allowing you to restore the data to a particular timestamp. They are helpful in recovering data from a specific point in the past in case of accidental data loss or corruption.
Q.84 How can you enable replication in MongoDB to ensure data redundancy and availability?
Replication can be enabled by setting up a replica set. A replica set is a group of MongoDB servers that maintain the same data, providing automatic failover and data redundancy. To create a replica set, you need to initiate multiple MongoDB instances as replicas and elect a primary node.
Q.85 Explain the primary and secondary nodes in a MongoDB replica set.
In a MongoDB replica set, one node is elected as the primary, and the others are secondary nodes. The primary node handles all write operations and serves client reads by default. Secondary nodes replicate data from the primary and can serve read operations if explicitly configured.
Q.86 How can you monitor the replication status of a MongoDB replica set?
You can monitor the replication status by using the rs.status() method in the MongoDB shell. This command provides information about the replication lag, health of nodes, and the primary's status.
Q.87 What is the process of adding a new member to an existing MongoDB replica set?
To add a new member to an existing replica set, you need to start a new MongoDB instance with the --replSet option set to the replica set name. Then, you initiate the replica set configuration and add the new member using the rs.add() method in the MongoDB shell.
Q.88 How can you perform repair and data recovery on a MongoDB database?
To perform repair and data recovery, you can use the mongod --repair option, which repairs and rebuilds the MongoDB database. Additionally, point-in-time backups can be used to restore data to a specific point before the issue occurred.
Q.89 Explain the difference between journaling and replication in MongoDB.
Journaling is a write-ahead log mechanism that ensures data consistency in the event of a crash or power failure. It keeps a record of write operations before applying them to the database. Replication, on the other hand, involves copying data across replica set members to provide data redundancy and high availability.
Q.90 How can you perform a rollback in MongoDB?
MongoDB does not support manual rollbacks. In the case of a catastrophic failure, the best approach is to restore the data from a recent backup and then let replication catch up to the current state.
Q.91 What precautions should be taken while performing backup and restore operations in MongoDB?
While performing backup and restore operations, you should ensure that the MongoDB instance is stable, and there are no active write operations. Additionally, it is crucial to test the restore process regularly to verify that backups are working correctly.
Q.92 What is autosharding in MongoDB, and why is it used?
Autosharding is a feature in MongoDB that automatically distributes data across multiple shards (servers) to achieve horizontal scalability. It allows MongoDB to handle large datasets and heavy workloads by distributing data efficiently across multiple nodes.
Q.93 How does MongoDB determine which shard to store data on?
MongoDB determines the shard to store data on based on the shard key. The shard key is a field or a set of fields in the document that MongoDB uses to distribute data across shards.
Q.94 What factors should you consider when choosing a shard key for a collection?
When choosing a shard key, consider the cardinality (number of unique values) of the key, the distribution of data, and the expected query patterns. An ideal shard key should evenly distribute data across shards and align with your query workload.
Q.95 What happens if you have an unbalanced distribution of data across shards?
An unbalanced distribution of data can lead to hotspots on certain shards, causing performance issues. It is essential to choose an appropriate shard key and, if needed, rebalance the data manually to ensure an even distribution.
Q.96 How can you enable autosharding in MongoDB for a specific collection?
To enable autosharding for a collection, you need to create a sharded collection using the sh.shardCollection() method in the MongoDB shell. For example, sh.shardCollection("dbName.collectionName", { shardKeyField: "hashed" }) enables sharding on the "collectionName" collection with the "shardKeyField" as the shard key.
Q.97 Explain the concept of range-based sharding in MongoDB.
Range-based sharding is a type of sharding where data is distributed based on ranges of shard key values. MongoDB ensures that documents with similar shard key values are stored on the same shard.
Q.98 What is the difference between hashed sharding and range-based sharding?
Hashed sharding uses a hashed value of the shard key to distribute data uniformly across shards, resulting in a more even distribution. Range-based sharding, on the other hand, distributes data based on the actual value of the shard key.
Q.99 Can you change the shard key for an existing sharded collection?
Changing the shard key for an existing sharded collection is a complex and resource-intensive operation. It is generally not recommended, and it is better to carefully choose the shard key during the initial setup.
Q.100 How do you monitor the performance and health of a sharded cluster in MongoDB?
MongoDB provides built-in tools like mongotop, mongostat, and mongosniff to monitor the performance of a sharded cluster. Additionally, external monitoring tools like MongoDB Cloud Manager or Ops Manager can provide more comprehensive monitoring capabilities.
Q.101 What are some common challenges when working with autosharding in MongoDB?
Some common challenges include choosing an appropriate shard key, managing data distribution and balancing, handling hotspots, and ensuring proper index usage across shards.
Q.102 What is the type of MongoDB?
It's Document-oriented
Q.103 What is the data structure representation of document in JavaScript?
Object orinted
Q.104 What will be the port number for HTTP based admin interface if, MongoDB is running at 443?
1443
Q.105 What is the number of bytes taken by an ObjectId?
16
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