MongoDB Interview Questions and Answers- Part 4

Answer:

• Replication creates extra copies or clones data and allows for automatic failover to another node.
• Sharding facilitates horizontal data writes scaling by partitioning data across multiple servers with a shard key.

Sharding usually sits on the top of replication. Shards are replica sets with a router in front. Your app will connect to a router, issue queries, and then decides which Shard or replica set to forward things onto.

Answer:

The serverStatus() renders a lot of information about a MongoDB Server. One can get explicit information about the number of connections made to a server by running this command db.serverStatus().connections from any MongoDB Shell connected to a server.

Answer:

Despite having many advantages, MongoDB has some limitations like:

• Joins not Supported- MongoDB does not support joins like a relational database. Besides, you can deploy joins functionality by coding it manually but, it may slow down the execution and affect the overall performance.
• High Memory Usage- MongoDB stores key names for every value pair. Also, because of no join functionality, there remains data redundancy. It increases unnecessary memory usage.
• Limited Data Size- You can have a document size in MongoDB, but not more than 16MB.
• Limited Nesting- One cannot perform documents’ nesting for more than a hundred levels.

Answer:

The following are a few advantages of MongoDB over relational databases:

1. MongoDB is a schema-less database. It means that we don’t need to design a schema of the database when using MongoDB. This saves plenty of time. Thus, the code we write defines a schema.
2. No complex joins are required in MongoDB. There is no relationship amongst data in MongoDB.
3. It is very easy to scale, set up, and install MongoDB.
4. The document query language supported by MongoDB is simple and easy to understand compared to SQL queries.
5. As MongoDB uses JSON format to store data, it becomes easy to store objects and arrays.
6. MongoDB is open-source and free to use.
7. MongoDB performs better in contrast to other relational databases.
8. It eliminates the need for mapping application objects to database objects.
9. MongoDB deploys the internal memory for storage that enables faster data access.

Answer:

The explain() command is used to provide information on the query plans. Below are the possible models in the explain() method:

• queryPlanner
• executionStats
• allPlansExecution

Answer:

GridFS in MongoDB is a special specification for retrieving and storing files that exceed the size limit (16MB) of the BSON-document. The major functionality of this GridFS is to divide a file into smaller segments and further store each segment as a separate document rather than storing them into a single document.

Answer:

1. Key-Value Stores
   • It is based on Amazon’s Dynamo paper and distributed hash tables.
   • It was created to manage a large amount of data and store schema-free data.
   • It simplifies the process of data insertion and retrieval.
   • Key-Value Stores data as a hash table where all keys are unique and the value can be a JSON, string, BLOB, etc.
   • Values can be stored against the lists, strings, stored sets and hashes sets as a key.
   • Collections, associative dictionaries, and arrays can be used as key-value stores.
2. Document Stores
   • It is a collection of documents where a document is a collection of key-value types. All data stored (key-values) in documents can be accessed with the keys.
   • All documents are independent.
   • Documents are schema-free; thus, they are easy to modify and flexible.
   • Collections are used to store documents to group different data types.
   • Documents may have nested documents, several different key-array pairs, or key-value pairs.
3. Column-Oriented
   • Column-oriented databases were designed to work on columns where each column is treated separately. All values are stored contiguously for every column.
   • The database stores data in column-specific files with the same data type.
   • In this database, query processors operate on columns; it boosts the query performance as it can access specific column data. It also gives a performance on aggregation queries.
   • All data related to a single column is ideal for compression because of the same type.
   • Column-oriented databases are designed similar to arrays with three-dimension; the row identifier is the first dimension, while a combination of the column identifier with family is the second, and a timestamp is the third.
4. Graph Network
   • It stores data in a graph-like structure.
   • This database is used for storing commonly changing data.
   • Graph databases can represent any data. It provides high accessibility as it deploys indexes for lookups.
   • A graph database means a collection of one or multiple edges and nodes.
   • Every node represents an entity such as a business or student, and every edge connects two nodes representing the relationship between them.
   • A unique identifier is used to define each edge and node.
   • The graph can be traversed in the depth-first or breadth-first fashion. Starting from arbitrary or start node.

Answer:

The ACID properties are interpreted by any relational DBMS in the following ways:

• Atomicity requires that every transaction gets executed in its entirety or fails without a change being applied.
• Consistency requires that a database only passes from the valid state to another one without intermediate points.
• Isolation requires that if a transaction is executed concurrently, the result is equivalent to the serial execution. A transaction cannot view the partial result of an application of another one.
• Durability means that the results of a committed transaction are permanent, even if a database crashes immediately or in case of a power loss.

MongoDB has always supported the ACID transactions in a document and, when leveraging a document model appropriately, many applications don’t require ACID guarantees across multiple documents.

Answer:

WiredTiger is the default storage engine in MongoDB since version 3.2. It provides features like compression, document-level locking, and improved concurrency control, which enhance MongoDB’s performance and scalability.

Answer:

The aggregation framework is a powerful tool in MongoDB for data transformation and analysis. It provides a way to process and compute data on the server side using a pipeline of operations, such as filtering, grouping, sorting, and projecting.

Answer:

MongoDB achieves high availability through features like replica sets. A replica set consists of multiple MongoDB instances, where one is the primary and others are secondary. If the primary fails, a secondary can be elected as the new primary, ensuring continuous availability.

Answer:

Indexing in MongoDB is the process of creating data structures to improve the speed of data retrieval operations. Indexes are crucial for efficiently querying data. MongoDB automatically creates an index on the _id field, and you can create custom indexes to optimize queries.

Answer:

BSON stands for Binary JSON. It is a binary-encoded serialization format used to store and transmit data in MongoDB. BSON is efficient in terms of storage and parsing, making it suitable for MongoDB’s data storage needs.

Answer:

Mongo shell does not have built-in functions for exporting, importing, backup, or restore. However, MongoDB has created several utility scripts that can be used to get data in or out of the database in bulk without the need for scripting work or complex GUIs 1. These utility scripts include:

• mongoexport: Used to export data from a MongoDB instance to a JSON or CSV file.
• mongoimport: Used to import data from a JSON or CSV file to a MongoDB instance.
• mongodump: Used to create a binary export of the contents of a MongoDB instance.
• mongorestore: Used to restore data from a binary export created by mongodump.

Answer:

MongoDB is a NoSQL database, while SQL databases are relational databases. MongoDB stores data in a flexible, schema-less format, whereas SQL databases use structured schemas. MongoDB is horizontally scalable, while SQL databases are vertically scalable.

Answer:

A document in MongoDB is a basic unit of data storage. It is similar to a record or row in a relational database and is represented in BSON format, which is a binary-encoded serialization of JSON-like documents.

Answer:

An ObjectId is a 12-byte identifier used as a primary key in MongoDB documents. It consists of a timestamp, a machine identifier, a process identifier, and a counter. ObjectId values are unique across the collection and are automatically generated by MongoDB when a new document is inserted.

Answer:

MongoDB introduced multi-document transactions in version 4.0. Transactions allow developers to perform multiple operations on multiple documents in a collection in an all-or-nothing manner, ensuring data consistency and integrity.

Answer:

MongoDB Atlas is a fully managed database service provided by MongoDB, Inc. It allows users to deploy and manage MongoDB databases in the cloud, handling tasks such as scaling, backups, and security. MongoDB Atlas simplifies database administration and is available on major cloud providers.

Answer:

In MongoDB, the limit() method is used to specify the maximum number of documents that should be returned in the result set of a query. It is often used in conjunction with other query methods like find() to control the number of documents retrieved from a collection.