Managing a database is becoming increasingly complex now due to the vast amount of data being produced continuously. Therefore a number of database management systems have been released. One of these is MongoDB which was released in 2009. Despite being relatively new in the field, it is doing extremely well. Usually, organizations don’t prefer to switch their database management systems. But MongoDB made a lot of companies switch their systems due to its ease of usage. This is the reason why MongoDB developers are in great demand these days.
But to achieve your aim and become a MongoDB developer, you need to prepare from the very beginning. The competition is so fierce now that you can’t succeed without making an edge over others. But with preparation and the right directions, you can beat that competition. And to help with your interview, we have prepared this comprehensive collection of MongoDB Interview Questions.
MongoDB is an open-source database management system for NoSQL. It is a cross-platform and document-oriented database. It is written in C++ language. It ditches the conventional table-based relational databases and uses documents like JSON instead with optional schemas. It’s based on the concept of document and collection. Extreme scalability is provided by MongoDB through its features like sorting, range queries, indexes, aggregations, etc.
Some of the main characteristics of MongoDB are given below-
A document in MongoDB is a collection of keys along with their values arranged in an orderly manner. A map, directory, or hash is used to represent it. Objects represent the document in JavaScript, such as {“greeting”: “Hello World!”}. Multiple keys and values are contained in a complex document, such as {“greeting”: “Hello World!”, “views”: 2}.
A collection in MongoDB refers to a set of documents. Just like the document is analogous to a relational database’s row, a collection is analogous to a table. They can have diverse shapes and schemas. An example is-
{"greeting": "Hello World!", "views": 2}
{"signoff": "Have a good day"}
Replication is used for keeping identical copies of our data on multiple servers. This is helpful when something goes wrong with one or more servers. In such scenarios, the data remains safe. And the Replica set is used for such replication in MongoDB. A replica set contains a primary server and multiple secondary servers. In case of the primary server crash, a new primary is selected from the secondary servers themselves.
Primary Nodes | Secondary nodes |
We can write as well as read in these types of nodes, also called master nodes. Write operations can be accepted by only one node since it’s a single replication master. | Secondary nodes are also referred to as slave nodes. This is because they allow only reading replicated from the primary nodes. |
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Splitting up data across multiple servers is easy in MongoDB since it is a document-based model. MongoDB loads and balances the data across a cluster. Then the documents are redistributed automatically. An interface is provided by the query router of mongo between the sharded cluster and client applications. The metadata and settings are stored in the Config servers for clusters. There is a separate config server for each sharded cluster.
A query can be performed using the find method in MongoDB. A subset of documents from a whole set of documents is returned by MongoDB. From no document to the whole collection, we can have anything we want. The first argument of find is the query criterion which is used to determine the document that is to be returned.
There are two types of geospatial indexes in MongoDB- 2d and 2dsphere. Spherical geometries that model the earth’s surface based on the WGS84 datum are used by the 2dsphere indexes. This works on the model of the earth as an oblate spheroid where the poles are flat. More accurate measures of distance are provided by 2dsphere than 2d indexes since it takes into account the earth’s shape. 2d indexes are, on the other hand, used for storing points on a 2-dimensional plane.
A transaction refers to the logical processing unit of a database capable of including multiple write operations or read operations. This ensures consistency in MongoDB. There are two types of APIs provided by MongoDB for using transactions-
●Core API- It has syntax like a relational database. For example- start_transaction and commit_transaction.
● Call-back API- This one is recommended for transactions. The transaction is started, executed, and committed by it. The error handling logic is automatically incorporated by it.
There is a wide array of data types supported by MongoDB. It includes several additional data types along with the keys and values of JSON. The main ones are as follows-
a) Null- {“x”: null}
b) Number- {“x”: 5}
c) Boolean- {“x”: false}
d) Date- {“x”: new Date()}
e) String- {“x”: “foobar”}
f) Array- {“x”: [“d”, “e”, “f”]}
g) Binary data
h) Embedded document- {“x”: {“foo” : “bar”}}
These are new tools for data visualization in MongoDB. It is the best visualization method. We don’t even need to write any code in Python or Java to represent the database in the form of charts. MongoDB provides the following two types of implementations-
We can interact with MongoDB using this JavaScript shell through a command line. Administrative functions like exploring MongoDB or inspecting an instance can be performed using this shell. The following commands need to be run to start a shell-
$ mongod
$mongo
MongoDB shell version: 4.2.0
connecting to: test
>
The basic math works as follows-
>x=100;
100
>x/5;
20
MongoDB is used to build scalable business and internet applications. It should be chosen when a person wants-
The value is set by “$set” if there doesn’t exist a field value. This helps extremely to add keys defined by users and update schemas. Example–
>db.users.findOne()
{
“_id”: ObjectId(“eafadf”)
“name”: “dinesh”,
“age”: 30,
“sex”: “male”,
“location”: “India”
}
Now field can be added as follows-
>db.users.updateOne({“_id”: ObjectId(“eafadf”)},
…{“$set”: {“favorite color”: “Blue”}})
Importing, exporting, restoring, and backing up are not included in the mongo shell functions. But there are methods defined by MongoDB for the purpose which doesn’t need scripting complex GUIs. Hence, there are many utility scripts available to get bulk data in and out of the database. Some of these are mentioned below-
The storage size of the data and indexes contained server is 2 GB in MongoDB’s 32-bit version. That’s why MongoDB can’t be deployed for production work on the machines with the 32-bit model. On the other hand, there is no restriction on the deployment of MongoDB’s 64-bit version to the storage size. Hence, 64-bit operating systems are generally recommended.
The embedded data model is used when-
a) There are “contains” relationships among the entities.
b) There are one-to-many relationships among entities. The child or the “many” documents are displayed in relationships in the context of documents belonging to the parents.
And a normalized data model is used when-
a) The duplication of data results from embedding, and sufficient read advantages are not there to take benefit.
b) More tough many-to-many relationships are to be represented.
c) The huge hierarchical data sets are to be modelled.
It is a special type of collection in MongoDB. The collection size can be restricted in this type. Its syntax goes like- db.createCollection(<collection_name>, {capped: Boolean, autoIndexId: Boolean, max: Number, size: Number}).
The given fields are there in the syntax of Capped Collection-
Basis for comparison | MongoDB | RDBMS |
Definition | This is a non-relational database management system. | This is a database system that is relational. |
Working | It works with table relationships using rows and columns. | It is a document-based database system that works using documents and fields. |
Performance | The performance is increased with the processors’ rise. | The performance is increased with the RAM capacity rise. |
Scalability | It is both vertically and horizontally scalable. | It is scalable only vertically. |
Query Language | BSON is used by it to query the database. | SQL is used by it to query the database. |
Hierarchical Data Storage | There is a built-in provision available for storing hierarchical data. | Storing hierarchical data is a bit tough here. |
JavaScript Support | The JavaScript-based clients are supported by it to query the database. | The JavaScript-based clients are not supported by it to query the database. |
There are many kinds of indexes supported by MongoDB. Some of them are listed below-
MongoDB is a highly advanced database management system that is rich with features such as sharding and indexing. But that doesn’t compromise its smooth functioning. Therefore it is in high demand these days in the industry. There is ample space for you to grow in this field. That’s why make sure that you grab this opportunity this time only. These MongoDB interview Questions are for taking you one step closer to your dream job and company. Now, leave no stone unturned in its preparation and come out with flying colours from the interview process.
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