Q: What is MongoDB?
A: MongoDB is a popular open-source NoSQL document-oriented database management system. It stores data in flexible and dynamic JSON-like documents that can have varying fields and structures, unlike traditional relational databases.
Q: What are the advantages of using MongoDB over traditional relational databases?
A: Some advantages of MongoDB include its flexible schema, ability to handle large amounts of unstructured data, and scalability. It also supports a rich set of querying and indexing capabilities and can be easily integrated with other technologies.
Q: What is a document in MongoDB?
A: A document is the basic unit of data in MongoDB, similar to a row in a relational database. It is a JSON-like data structure that contains field-value pairs and can have varying structures.
Q: What is a collection in MongoDB?
A: A collection is a group of related documents in MongoDB, similar to a table in a relational database. Collections are schema-less and can contain documents with different fields and structures.
Q: How do you create a collection in MongoDB?
A: Collections are created automatically when the first document is inserted into them. You can also create a collection explicitly using the createCollection() method.
Q: What is a shard in MongoDB?
A: A shard is a horizontal partition of data in a MongoDB cluster. It allows for the distribution of data across multiple nodes to improve scalability and performance.
Q: What is the difference between a replica set and a shard in MongoDB?
A: A replica set is a group of MongoDB servers that maintain the same data set and provide redundancy and high availability. A shard is a partition of data across multiple servers for horizontal scaling.
Q: How do you perform aggregation in MongoDB?
A: Aggregation in MongoDB is performed using the aggregate() method. It allows you to perform complex data analysis and processing operations, such as grouping, sorting, filtering, and calculating aggregate values.
Q: What is indexing in MongoDB?
A: Indexing in MongoDB is the process of creating an index on one or more fields of a collection to improve query performance. It allows MongoDB to locate and retrieve data more efficiently.
Q: How do you create an index in MongoDB?
A: Indexes can be created using the createIndex() method or by specifying an index in the collection’s schema.
Q: What is the difference between a primary key and a unique key in MongoDB?
A: In MongoDB, the primary key is automatically created for each document and is used to uniquely identify it. A unique key, on the other hand, can be created on any field to ensure that its values are unique across all documents in the collection.
Q: What is the difference between $push and $addToSet in MongoDB?
A: The $push operator appends a value to an array field in a document, even if it already exists. The $addToSet operator adds a value to an array field only if it does not already exist in the array.
Q: How do you perform backups and restores in MongoDB?
A: Backups in MongoDB can be performed using the mongodump utility, which creates a binary dump of the data. Restores can be done using the mongorestore utility, which restores the data from the binary dump.
Q: What is the syntax for inserting a document in MongoDB?
A: The syntax for inserting a document in MongoDB is as follows:
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db.collection.insertOne({field1: value1, field2: value2, …})
where collection is the name of the collection and field1, field2, etc. are the fields in the document.
Q: What is the difference between findOne() and find() in MongoDB?
A: The findOne() method returns the first document that matches the query, while the find() method returns a cursor to all the documents that match the query.
Q: How do you update a document in MongoDB?
A: You can update a document in MongoDB using the updateOne() or updateMany() methods. The syntax for updating a document is as follows:
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db.collection.updateOne({query}, {$set: {field: value}})
where collection is the name of the collection, query is the filter for the document to update, field is the name of the field to update, and value is the new value for the field.
Q: What is a cursor in MongoDB?
A: A cursor is a pointer to the result set of a query in MongoDB. It allows you to iterate over the documents in the result set and retrieve them one at a time.
Q: How do you limit the number of documents returned in a query in MongoDB?
A: You can limit the number of documents returned in a query in MongoDB using the limit() method. The syntax is as follows:
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db.collection.find({query}).limit(n)
where collection is the name of the collection, query is the filter for the documents to retrieve, and n is the maximum number of documents to return.
Q: How do you sort the results of a query in MongoDB?
A: You can sort the results of a query in MongoDB using the sort() method. The syntax is as follows:
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db.collection.find({query}).sort({field: 1})
where collection is the name of the collection, query is the filter for the documents to retrieve, field is the name of the field to sort by, and 1 specifies ascending order.
Q: What is the aggregation pipeline in MongoDB?
A: The aggregation pipeline is a framework for performing data aggregation operations in MongoDB. It consists of a series of stages that process and transform the data, such as filtering, grouping, sorting, and projecting.
Q: How do you drop a collection in MongoDB?
A: You can drop a collection in MongoDB using the drop() method. The syntax is as follows:
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db.collection.drop()
where collection is the name of the collection to drop.
Q: How do you connect to MongoDB from a client application?
A: You can connect to MongoDB from a client application using the MongoDB driver for your programming language. The driver provides methods for connecting to a MongoDB server, executing queries, and retrieving results.
Q: What is the role of the primary node in a replica set?
A: The primary node in a replica set is responsible for handling all write operations and managing the replication of data to the secondary nodes. It is the only node that can accept write operations, while the secondary nodes can only accept read operations.
Q: What is sharding in MongoDB?
A: Sharding is a method of distributing data across multiple servers in MongoDB. It allows you to horizontally scale your database by partitioning data into smaller chunks called shards.
Q: How do you enable sharding in MongoDB?
A: To enable sharding in MongoDB, you need to perform the following steps:
Start a MongoDB instance as a config server.
Start one or more MongoDB instances as shard servers.
Connect to the config server and run the sh.enableSharding() command.
Define the shard key for each collection you want to shard using the sh.shardCollection() command.
Q: What is the role of the config server in MongoDB sharding?
A: The config server in MongoDB sharding is responsible for storing the metadata about the sharded data. It tracks the location of each shard and the range of the shard key values for each chunk of data.
Q: What is a shard key in MongoDB?
A: A shard key in MongoDB is a field or combination of fields used to partition data across multiple shards in a sharded cluster. It determines how data is distributed among the shards.
Q: How do you add a shard to a MongoDB cluster?
A: To add a shard to a MongoDB cluster, you need to perform the following steps:
Start a MongoDB instance as a shard server.
Connect to the config server and run the sh.addShard() command to add the new shard to the cluster.
Q: How do you remove a shard from a MongoDB cluster?
A: To remove a shard from a MongoDB cluster, you need to perform the following steps:
Connect to the config server and run the sh.removeShard() command to remove the shard from the cluster.
Wait for MongoDB to move all data from the removed shard to the remaining shards.
Stop the MongoDB instance running on the removed shard.
Q: What is a covered query in MongoDB?
A: A covered query in MongoDB is a query that can be satisfied entirely using the indexes in a collection. It does not need to access the actual documents in the collection, which can improve query performance.
Q: How do you create an index in MongoDB?
A: You can create an index in MongoDB using the createIndex() method. The syntax is as follows:
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db.collection.createIndex({field: 1})
where collection is the name of the collection, field is the name of the field to index, and 1 specifies ascending order.
Q: What is the difference between a single-field index and a compound index in MongoDB?
A: A single-field index in MongoDB indexes a single field in a collection, while a compound index indexes multiple fields together. Compound indexes can be more efficient for queries that involve multiple fields.
Q: How do you drop an index in MongoDB?
A: You can drop an index in MongoDB using the dropIndex() method. The syntax is as follows:
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db.collection.dropIndex({field: 1})
where collection is the name of the collection, field is the name of the indexed field, and 1 specifies ascending order.
Q: What is the difference between a replica set and a sharded cluster in MongoDB?
A: A replica set is a group of MongoDB servers that maintain the same data set for high availability and data redundancy. A sharded cluster, on the other hand, is a group of MongoDB servers that partition data and distribute it across multiple shards for horizontal scaling.
Q: How do you create a replica set in MongoDB?
A: To create a replica set in MongoDB, you need to perform the following steps:
Start multiple MongoDB instances on different servers.
Connect to one of the instances and run the rs.initiate() command to initiate the replica set.
Add the other instances to the replica set using the rs.add() command.
Q: What is the role of the primary node in a MongoDB replica set?
A: The primary node in a MongoDB replica set is the node that accepts all write operations and propagates changes to the secondary nodes. It also serves as the default node for read operations if there are no read preferences specified.
Q: What is the role of the secondary node in a MongoDB replica set?
A: The secondary node in a MongoDB replica set is a read-only node that replicates data from the primary node. It can serve as a failover node in case the primary node goes down.
Q: What is a read concern in MongoDB?
A: A read concern in MongoDB specifies the level of consistency guarantee for read operations. It determines how long a read operation waits for data to be replicated to the secondary nodes before returning results.
Q: What is a write concern in MongoDB?
A: A write concern in MongoDB specifies the level of acknowledgement required for write operations. It determines how many nodes must confirm a write operation before returning a success response to the client.
Q: How do you perform a backup and restore in MongoDB?
A: You can perform a backup and restore in MongoDB using the mongodump and mongorestore utilities. mongodump creates a binary export of the data in a MongoDB instance, while mongorestore restores the data from the export to a MongoDB instance.
Q: What is the aggregation pipeline in MongoDB?
A: The aggregation pipeline in MongoDB is a framework for data aggregation and transformation. It consists of a series of stages that apply different operations to a collection to transform or filter the data.
Q: How do you use the aggregation pipeline in MongoDB?
A: You can use the aggregation pipeline in MongoDB by chaining together multiple stages using the $pipeline operator. Each stage can perform a different operation on the input documents, such as filtering, sorting, grouping, or projecting.
Q:- What is the difference between a collection and a document in Mongo DB?
A: A collection in MongoDB is a group of related documents that share a common schema. A document, on the other hand, is a single data record in a collection that consists of key-value pairs.
