Suggested Certification for MongoDB

Oracle NoSQL Database Cloud Training and Certification, MongoDB Associate Developer Exam
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Recommended Book 5 for MongoDB

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Interview Questions and Answers

Sharding is a method of horizontally scaling a MongoDB deployment. It involves distributing data across multiple machines (shards) to improve performance and storage capacity.

Replica sets are groups of MongoDB servers that maintain the same data set, providing redundancy and high availability. One server acts as the primary, and the others act as secondaries, automatically replicating data from the primary. If the primary fails, a secondary automatically takes over.

You can back up a MongoDB database using the `mongodump` utility, which creates a binary export of the database. You can restore the database using the `mongorestore` utility, which imports the data from the backup files.

You can update data using the `db..updateOne(query, update, options)` or `db..updateMany(query, update, options)` methods. The `query` parameter specifies the documents to update, and the `update` parameter specifies the modifications to make.

You can delete data using the `db..deleteOne(query)` or `db..deleteMany(query)` methods. The `query` parameter specifies the documents to delete.

You can create an index using the `db..createIndex(keys, options)` method. `keys` specifies the fields to index, and `options` provides additional configurations.

Aggregation pipelines are a framework for data aggregation in MongoDB. They consist of a series of stages that process the data, such as filtering, grouping, and transforming it. Aggregation pipelines are used to perform complex queries and generate reports.

The MongoDB shell is an interactive JavaScript interface that allows you to interact with a MongoDB database from the command line. You can use it to create, read, update, and delete data.

You can create a database by using the `use ` command in the MongoDB shell. This will switch to the specified database, and if it doesnt exist, it will be created when you first insert data into it.

You can create a collection implicitly when you insert a document into it using `db..insertOne()` or `db..insertMany()`. Alternatively, you can explicitly create a collection using `db.createCollection()`.

You can insert a single document using `db..insertOne(document)` or multiple documents using `db..insertMany([document1, document2, ...])`.

You can query data using the `db..find(query, projection)` method. The `query` parameter specifies the selection criteria, and the `projection` parameter specifies which fields to return.

MongoDB indexes are data structures that improve the speed of read operations on a collection. They are important because they allow MongoDB to quickly locate documents that match a query, rather than scanning the entire collection. Without indexes, queries can be slow, especially on large collections.

Installation varies depending on the operating system. Generally, you download the MongoDB package, extract it, configure environment variables, and run the MongoDB server (mongod). The MongoDB website provides detailed instructions for each OS.

You can connect using the `mongo` shell (command-line interface) or a MongoDB driver specific to your programming language. The connection string typically includes the hostname, port, and database name.

A MongoDB document is a set of key-value pairs. Documents are similar to JSON objects and are the basic unit of data in MongoDB.

A MongoDB collection is a group of MongoDB documents. It is analogous to a table in a relational database.

MongoDB is a NoSQL document database that stores data in flexible, JSON-like documents. It is designed for scalability, performance, and ease of use.

Key features include its document-oriented data model, flexible schema, horizontal scalability, high availability, support for complex queries, and indexing capabilities.

MongoDB uses a flexible schema (NoSQL) compared to the rigid schema of relational databases (SQL). MongoDB scales horizontally, while relational databases typically scale vertically. MongoDB uses a document-oriented data model, whereas relational databases use a table-based model. SQL requires pre-defined schemas, while MongoDB schemas can evolve over time.