What is the MERN stack?

MERN stack is a web development technology stack consisting of MongoDB, Express.js, React.js, and Node.js.

What is MongoDB used for in the MERN stack?

MongoDB is used as the database in the MERN stack.

What does Express.js provide in the MERN stack?

Express.js provides the backend framework in the MERN stack.

What role does React.js play in the MERN stack?

React.js is used for handling the front-end in the MERN stack.

What is Node.js used for in the MERN stack?

Node.js is used as the server-side runtime environment in the MERN stack.

What are some advantages of using MongoDB?

MongoDB offers flexibility, scalability, high availability, high performance, and a flexible schema design.

How does the virtual DOM improve React performance?

The virtual DOM updates only the objects that have changed, rather than the entire DOM, improving performance.

What is JSX in React.js?

JSX is a syntax extension for JavaScript that allows HTML to be written within React.js code.

What are some key features of Node.js?

Node.js is known for being fast, event-driven, and uses JavaScript for both client and server-side scripting.

What are the different data models in MongoDB?

MongoDB has embedded and reference data models for structuring data.

MERN Stack Interview Questions and Answers | MERN Stack Interview 2023 | Simplilearn

01:20:12

https://www.youtube.com/watch?v=j6jWMxlquEI

Summary

TLDRThe video explores the MERN stack, consisting of MongoDB, Express.js, React.js, and Node.js, highlighting its efficiency in building scalable and responsive web applications. It delves into the basics and advanced aspects of each technology, offering insights into industry-relevant interview questions. MongoDB's advantages include flexibility, scalability, and high performance, while Node.js is celebrated for its speed and event-driven architecture. React.js uses JSX for a seamless integration of JavaScript and HTML, improving code readability and debugging. Express.js, part of Node.js, enables swift API development. Practical applications discussed include MongoDB's use cases such as IoT, mobile applications, and large-scale data management, emphasizing its utility in managing vast datasets and processing them effectively.

Takeaways

🚀 MERN stack is efficient for developing scalable web applications.
📚 MongoDB provides flexibility and scalability with its document-based structure.
🖥️ React.js uses JSX, making code easier to read and debug.
🔄 Virtual DOM in React updates only changed elements, enhancing performance.
💻 Node.js is fast and event-driven, suitable for real-time applications.
🔧 Express.js is vital for building quick and robust APIs.
📈 MongoDB excels in handling large volumes of unstructured data.
📱 MERN stack supports both front-end (React.js) and back-end (Node.js, Express.js) development.
💡 Understanding MERN can significantly benefit those pursuing full stack development roles.
🔍 Regular study and practice of interview questions can enhance job prospects.

Timeline

00:00:00 - 00:05:00
The video introduces the MEAN stack as a popular web development stack comprising MongoDB, Express, React, and Node.js, and outlines the basic roles of each technology (MongoDB for databases, Express for backend, React for frontend, and Node.js for server-side runtime). It highlights how these technologies together create highly scalable web applications.
00:05:00 - 00:10:00
It informs viewers about an upcoming segment on frequently asked MEAN stack interview questions. It advises subscribing for updates and suggests a coding bootcamp for immersive learning. The bootcamp covers Java technologies, while also mentioning other topics like Angular, JSPs, and MongoDB.
00:10:00 - 00:15:00
The presenter explains JSX (JavaScript Syntax Extension) used in React.js to bind JavaScript and HTML, simplifying code structure. The concept of the virtual DOM in React, which allows for efficient page updates by only altering changed elements, is introduced. React extensions like Flux and React Native for mobile apps are mentioned.
00:15:00 - 00:20:00
The speaker discusses React components, dividing complex UIs into reusable chunks. They detail "state" in React as a way to track data changes over time, initialized in constructors, allowing pages to render based on current data states. Higher-order components and pure components, which help with reuse and shallow comparison respectively, are also described.
00:20:00 - 00:25:00
React routing is introduced as a means to manage URL paths and deliver components using React modules. The session transitions to a Node.js interview overview with beginner to advanced questions. Node.js is presented as a leading server-side platform due to its open-source, cross-platform JavaScript runtime allowing fast application development.
00:25:00 - 00:30:00
Node.js's foundation on the V8 engine, its high-speed asynchronous I/O operations, and its applications in web, distributed, and network applications are highlighted. The difference between frontend and backend development is explained, with examples of typical technologies used in each realm.
00:30:00 - 00:35:00
The section delves into npm (Node Package Manager), its role in managing online repositories and command line utilities. An overview of Node.js modules is given, explaining how these JavaScript libraries are utilized for server-side tasks, such as setting up a web server using HTTP.
00:35:00 - 00:40:00
Node.js's advantage over traditional back-end technologies like Java and PHP is discussed. Its speed, node package manager resources, suitability for real-time data applications, and ease of code synchronization between client and server due to JavaScript are noted as key benefits.
00:40:00 - 00:45:00
The information on Angular vs Node.js establishes Angular as a client-side framework and Node.js as a server-side one. Databases commonly used with Node.js, particularly MongoDB and MySQL, are discussed, with MongoDB being preferred for its scalability with large data sets.
00:45:00 - 00:50:00
The segment covers popular Node.js libraries like Express.js for quick API development and Mongoose for database connectivity. The pros (fast processing, extensive package availability) and cons (complex callback structure, CPU-intensive operations) of Node.js are examined, with solutions like cloud scaling proposed.
00:50:00 - 00:55:00
Commands relevant to Node.js, particularly for importing external libraries using the "require" function, are elaborated upon. The transition to intermediate Node.js questions includes explanations of event-driven programming, how event loops, emitters, and API functions operate, highlighting synchronous vs asynchronous programming.
00:55:00 - 01:00:00
The video explains Node.js's package.json file's role as a project metadata holder and using URL modules for utility enhancement. Express.js is detailed as a framework facilitating web app creation in Node.js, streams in Node.js accomplish ongoing data reads/writes, and dependency management is outlined.
01:00:00 - 01:05:00
Synchronous/non-blocking APIs in Node.js scale applications effectively by allowing data to be processed without blocking operations. Examples of using async functionality and module exports to encapsulate code for shared use are also covered.
01:05:00 - 01:10:00
MongoDB is introduced as a key NoSQL database, with emphasis on its document-based storage structure, scalability, and schema flexibility. Common MongoDB interview questions focus on its architecture, alternative NoSQL databases, and distinctions from SQL databases.
01:10:00 - 01:15:00
Details on MongoDB's data models (embedded and reference), how indexing expedites query operations, replication and sharding for data availability, and the advantages of MongoDB's flexible schema are provided. Practical questions hone in on tasks like document insertion and handling large files.
01:15:00 - 01:20:12
MongoDB's role in highly available systems, aspects like capped collections for performance, GridFS for large file storage, and aggregation techniques like map-reduce are discussed. The video wraps with typical real-world MongoDB applications and resources for further learning.

Mind Map

Video Q&A

What is the MERN stack?
MERN stack is a web development technology stack consisting of MongoDB, Express.js, React.js, and Node.js.
What is MongoDB used for in the MERN stack?
MongoDB is used as the database in the MERN stack.
What does Express.js provide in the MERN stack?
Express.js provides the backend framework in the MERN stack.
What role does React.js play in the MERN stack?
React.js is used for handling the front-end in the MERN stack.
What is Node.js used for in the MERN stack?
Node.js is used as the server-side runtime environment in the MERN stack.
What are some advantages of using MongoDB?
MongoDB offers flexibility, scalability, high availability, high performance, and a flexible schema design.
How does the virtual DOM improve React performance?
The virtual DOM updates only the objects that have changed, rather than the entire DOM, improving performance.
What is JSX in React.js?
JSX is a syntax extension for JavaScript that allows HTML to be written within React.js code.
What are some key features of Node.js?
Node.js is known for being fast, event-driven, and uses JavaScript for both client and server-side scripting.
What are the different data models in MongoDB?
MongoDB has embedded and reference data models for structuring data.

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Subtitles

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00:00:01
foreign
00:00:09
stack is a popular web development stick
00:00:12
that includes four different
00:00:13
Technologies mongodb crashes reactors
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and node.js mongodb is used for the
00:00:21
database express.js provides the
00:00:23
back-end framework react.js handles the
00:00:25
front and node.js is used as the
00:00:28
server-side runtime environment
00:00:30
so this stack allows for creation of
00:00:32
Highly scalable efficient and responsive
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web application
00:00:36
hello everyone and welcome to Simply
00:00:38
learns YouTube channel today we'll take
00:00:41
you through the most frequently Asked
00:00:43
interview questions in Moon stack web
00:00:45
development in this video tutorial we'll
00:00:48
cover all the Technologies related to
00:00:51
Moon stack but before we begin let me
00:00:54
tell you guys that we have regular
00:00:55
updates on multiple Technologies so if
00:00:58
you are a tech geek in a container Sun
00:01:00
for the latest technological trends then
00:01:02
consider getting subscribed to our
00:01:04
YouTube channel and press that Bell icon
00:01:06
to never miss any updates from Simply
00:01:09
low for those interested in a
00:01:11
comprehensive coding bootcamp we highly
00:01:13
recommend the Caltech coding bootcamp
00:01:15
with this program you can learn to code
00:01:17
and become a full stack developer in
00:01:20
just six months this state-of-the-art
00:01:22
bootcamp will fully immerse you in
00:01:24
accelerated coding training helping you
00:01:27
become a valued software engineer ready
00:01:29
to take on any challenges in the
00:01:31
industry
00:01:32
during this boot camp you will Master
00:01:34
both front-end and back-end Java
00:01:37
Technologies starting with the basics
00:01:39
and progressing to the advanced aspects
00:01:41
of full stack web development
00:01:44
you'll also learn angular spring boot
00:01:46
web services jsps and mongodb to help
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you launch your career as a full stack
00:01:53
developer
00:01:54
for those who are looking to deepen
00:01:55
their understanding of full stack web
00:01:57
development or simply want to become a
00:02:00
full stack developer in a shorter amount
00:02:02
of time a Caltech coding bootcamp is an
00:02:05
excellent option so without wasting any
00:02:07
more time let's hand over this session
00:02:09
to our training export the react is
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interview questions
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now as we know it react.js is as
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important as like in other tools which
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you've already has seen so what is the
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jsx here jsx called JavaScript syntax
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extension
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okay so this syntax extension to the
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JavaScript in reactors is in the way
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how you express
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to bind JS and HTML together to result a
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j6
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content so by using j6 you can write a
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structure in the same file that contains
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the JavaScript code that is something
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more Innovative way because of that
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react.js is creating a more buzz in a
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market
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so jsx actually helps making code more
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easy to understand and debug and avoids
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a lot of boilerplate code okay inside
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the Dom structure
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now the next thing is what is the
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virtual Dom see the virtual Dom is
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representing a Dom in a memory
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okay that is called virtual Dom so
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manipulating the real term is much more
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slower and costly Affair okay because
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you need to repaint the Dom over and
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over the period of time when the user
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changes few things so
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when the state change virtual Dom
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changes and only the objects which are
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in real term
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okay
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update instead of updating the entire
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object so that makes your page to be
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load far more faster
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okay so in Virtual Dom what happens this
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is the real Dom this is a virtual Dom so
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the orange color portions which you're
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seeing that is basically the changes
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which has been made okay these are
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called Changed object okay so virtual
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Dom is basically compare it's to the
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previous state and understand which area
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it needs to send for the updates and
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avoid the other areas
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okay that's what this virtual Dom really
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works
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so what are react extension react
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extensions are many like you talk about
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like in flux it is a third party tool
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which is responsible to attach
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the State Management feature to talk
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about react native which is responsible
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to develop the hybrid mobile
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applications
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in JavaScript so these are two very
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popular and there are many more which
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are available okay so like you talk
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about
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architectural support you talk about
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server side rendering okay so Redux and
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there are lot many other tools are also
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available
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so what is an event in react and how
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you're going to create that so react is
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basically offering the ideas of handing
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the event very fairly easy so let me
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talk about clicking anything you talk
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about taking your mouse somewhere so
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these kind of options generate an event
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so for that we typically say alert and
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you click on this render you click on
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this button in a curly braces you call
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the function to trigger to event
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now what are the components in react
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so friends react components are nothing
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but a call View
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okay like a complex view can be divided
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into the smaller portions
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a complex UI can be distributed further
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to create more better and reusable views
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clear so it splits the user interface
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into the independent pieces of code
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which can be developed and joins
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later on okay so that's how you define
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the component in and react so in angular
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and react in both the areas the word
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component is very much used so the
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component meaning is very simple you
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talk about a view
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so what is the state in a react so state
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is react is nothing but is the one which
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identify what was and what is now okay
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if it stores the value for the specific
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period of time which changes and react
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is basically detecting those
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so it is changing because of some
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actions either taken by the users or by
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the applications okay so keep tracking
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about all those States what it was there
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like in I'm talking about an
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incrementing encounter so that is also
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the state a variable there okay so the
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state object is always initialized in
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the Constructor so it can contains the
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multiple properties so this dot set
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state is used to change the value of the
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state object and set state is
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responsible
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to
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perform the shallow merge between the
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new state and the previous state
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now the state holds the data that a
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component renders to the web page
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certainly because every time the state
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changes so it needs to be stored
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somewhere so this is how the state is
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accessed as you can see this example
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here
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in the Constructor we are defining the
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super props and the states has been
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initialized and you're rendering the
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states there are three different steps
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are involved initialize the state rent
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to the state and update the states
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what is the higher order component and
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pure component react higher components
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are the component which are typically a
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function okay that takes a component and
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return a new component to you by
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manipulating few things that basically
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designed for the reusing
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okay so the higher the components are
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typically a function that takes a
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component and return a new component
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okay so to in order to perform some
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reusability
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a pure components are the components
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okay is a variation of react component
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that doesn't
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that does a shallow comparison of props
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and State
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okay shell comparison basically checks
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what the equality
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are we clear now so that's what the main
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job
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going ahead what do we Implement and how
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do you implement react routing so to
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implement a react routing react routing
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also comes with inbuild
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react modules and that particular module
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to import it so
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here we Define the react modules by
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offering the route path where you have a
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call left hand side is the name and the
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right hand side is a component which you
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would like to deliver it now hello this
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is Matthew and we're going to be going
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through some of the simple questions
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that you would be asked during a node.js
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interview what we're going to do is
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we're actually going to break out the
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section into three key areas that'll be
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beginner questions there will be an
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intermediate questions and advanced
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questions and the expectation is as you
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go through this video is that these
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questions could be pushed together as
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you're going through the interview kind
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of think of it like this is if you've
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answered the beginner questions that you
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would get asked at the beginning of the
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interview with confidence and Surety
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then the client is going to then jump to
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those intermediate Advanced questions
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quite quickly and they're looking for
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people who can help them serve and solve
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their problems at that more intermediate
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and advanced level so let's just get
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started so the first question you're
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probably going to be asked is you know
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you know what is node.js you know do you
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know what it's for and essentially
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node.js is one of the most popular if
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not the most popular open source
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cross-platform JavaScript programs and
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it allows you to build out web
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applications that run on the server it's
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extremely flexible it allows you how to
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implement a lot of solutions outside of
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just the the core programming runtime
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and it allows you to build Solutions
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extremely quickly in an open source
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mindset for devops
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it is used essentially for creating
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client-sized web applications we'll see
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this later on and you may want to talk a
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little bit about you know using
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express.js and how you can build out
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apis uh to work with node.js and
00:10:06
connecting to databases such as mongodb
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and that is also really good for being
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able to store a data intensive
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applications that are asynchronous and
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event driven in their model and this is
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important when you're talking about
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creating applications that can scale
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rapidly
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so you can then ask be asked you know
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how does node.js work well node.js
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itself is actually built on the V8
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engine and the V8 JavaScript engine is
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the same engine that runs JavaScript in
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your Chrome web browser extremely fast
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it allows for high output and
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non-blocking through your i o input
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outputs and is is single threaded event
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blue
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so you're going to be a man asked you
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know where can you use node.js and and
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the reality is the applications for
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node.js keep expanding but there are
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some core applications that you can work
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with node.js right now so such as web
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applications distributed system and
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network applications uh probably
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referencing the web applications is a
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really good starting point because here
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you can actually talk about maybe some
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examples that you've done where you're
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building out some of these web
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applications uh indeed one of the things
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that you want to be consistently doing
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and peppering your answers with is
00:11:30
examples of work that you have done now
00:11:33
it doesn't matter if those examples are
00:11:35
purely experimental or training examples
00:11:38
that you've done the fact that you've
00:11:40
actually worked with node.js and created
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a distributed system or a web
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application is really valuable because
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it shows that the person that you're
00:11:49
meeting with that you have knowledge and
00:11:51
understanding and practical experience
00:11:54
of applying the theory of working with
00:11:57
new Js with the practice of working with
00:12:00
node.js
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so we asked about you know your answer
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and essentially the io refers to the
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transfer of data in and out of a system
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and that's really it you know there's a
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reason why Google calls that conference
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IO it's the transfer of data in and out
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of our brains at that conference the
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application is same here it's about
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moving data in and out of systems
00:12:23
through using node.js and that every um
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event can be tracked and whether it's on
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a physical device a network or files
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within a system again it's input and
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output
00:12:36
so let's go through and you know you're
00:12:38
going to be asked you know can you
00:12:39
explain the difference between front end
00:12:41
and back-end development and this is a
00:12:43
question that I can ask a lot when I'm
00:12:47
meeting with clients and you know people
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get really confused about what is the
00:12:51
difference between front-end and
00:12:52
back-end development bottom line front
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end is what gets resolved inside of your
00:12:57
web browser or the app on your mobile
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device backend is what gets resolved
00:13:04
essentially um what we call the the back
00:13:06
office or server-side applications but
00:13:09
it's becoming more and more synonymous
00:13:11
for what gets run in the cloud
00:13:14
so web applications
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um really get a lot of the functionality
00:13:19
of the web application gets run in the
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front end and I think with CSS HTML5 uh
00:13:24
client-side JavaScript so we can get
00:13:26
right on the front end everything else
00:13:27
such as connecting to a database gets
00:13:30
run behind the scenes in the back end
00:13:33
and so you know anything that's going to
00:13:36
have like Graphics is going to be on the
00:13:37
front end uh apis are going to be run on
00:13:40
the back end and then just finally some
00:13:43
of the scripting languages are using on
00:13:45
the front end so HTML CSS JavaScript
00:13:48
those are all Common Core scripting
00:13:51
languages that you would use you can use
00:13:53
Frameworks such as angularjs and
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react.js or view those would be a
00:13:58
front-end Frameworks uh back-end
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Frameworks will include Java PHP Python
00:14:04
and node.js are some of the back-end
00:14:06
Technologies you'd also throw in their
00:14:08
dot net as well and it's just a whole
00:14:12
you know Litany of front-end and
00:14:14
back-end Technologies and Frameworks
00:14:16
that you can use and this is a actually
00:14:18
a good point to kind of explain the
00:14:22
experience you have outside of just
00:14:23
working with node.js but other
00:14:25
technologies that you've been working
00:14:27
with that potentially that the client is
00:14:29
also using
00:14:31
so another question you're going to be
00:14:33
asked when you're looking at node.js is
00:14:35
you know can you tell me about npm and
00:14:37
so when somebody asks you what is npm
00:14:39
the first thing you're going to respond
00:14:40
is do you mean node package manager and
00:14:43
the reason why you want to respond like
00:14:45
that is that you want to qualify that
00:14:47
question with understanding that you
00:14:49
know what they're talking about but you
00:14:50
want them to verify that and so node
00:14:53
packet manager is npm
00:14:55
and it's responsible for packaging all
00:14:57
of your modules that you're working with
00:14:59
in node.js and we have a whole series of
00:15:02
videos that we've done on node.js and
00:15:05
every single one of them includes
00:15:07
references to npm
00:15:10
so you're going to be asked you know so
00:15:12
okay you tell me um what it is you know
00:15:14
can you go into a little bit more um
00:15:16
details you know so you can provide two
00:15:18
main functionalities and so one of them
00:15:21
is being able to manage online
00:15:23
repositories or modules and packages
00:15:26
um so you can go to like
00:15:28
search.nodejs.org and you can find a
00:15:30
packages that you can install Into Your
00:15:33
solution such as express.js and it also
00:15:37
provides a command line utility that
00:15:39
allows you to manage your packages very
00:15:42
quickly through terminal window or
00:15:44
command line
00:15:45
I use vs code a lot Visual Studio code
00:15:49
and it has a command line utility built
00:15:51
right into it that allows me to interact
00:15:53
with npm
00:15:55
so what are some of the modules in
00:15:57
node.js and so you know modules
00:16:01
um in node.js they're essentially like
00:16:03
JavaScript libraries so you can think of
00:16:06
some of the JavaScript libraries that
00:16:08
you may have used the functionality is
00:16:11
somewhat the same but they're designed
00:16:13
for node.js and to run on the server and
00:16:16
there are ways in which you can go ahead
00:16:17
and create some of those modules so for
00:16:21
instance if we're creating a web server
00:16:23
you can actually use the require
00:16:26
commands to be able to require that the
00:16:29
server be there so the example we have
00:16:32
on the right hand side shows that we
00:16:34
really do need to have HTTP which is a
00:16:37
web server and we require that to be
00:16:39
installed and so that if you're running
00:16:42
that npm package it will actually
00:16:45
install the HTTP server and then you can
00:16:48
actually write some code to actually
00:16:49
then listen on the localhost port 2000
00:16:54
for where you'll be running your app
00:16:55
application
00:16:57
and there are just you know there's a
00:16:59
whole bunch of modules like I come with
00:17:01
node.js now right out of the gate and
00:17:05
here are some of the modules that you
00:17:06
have and we also referenced that just
00:17:08
earlier on HTTP is a core module for uh
00:17:11
running a web server uh you have a
00:17:15
utility function that is useful for
00:17:17
developers to assess features within
00:17:20
your node.js project you have a URL
00:17:23
module for any URL passing you'd be
00:17:26
doing
00:17:26
and you also have a stream which allows
00:17:30
you to be able to stream data in and out
00:17:33
of your system and be able to manage how
00:17:35
that's been worked and then zlib which
00:17:37
allows you to compress and decompress
00:17:39
files so that you can keep your storage
00:17:42
of files to a minimum
00:17:45
so a question you're going to be asked
00:17:48
is you know why is node.js being
00:17:50
preferred over back-end Technologies
00:17:52
such as Java and PHP and particularly
00:17:55
with gyro it's a very mature stable
00:17:57
language it's been around for more than
00:17:58
20 years you know PHP
00:18:00
um runs some of them the most powerful
00:18:03
and largest websites out there such as
00:18:06
Facebook so why would you use node.js
00:18:09
well the first response is kind of a
00:18:12
gimme but it is really fast and if you
00:18:15
watched any of the videos that we've
00:18:18
done on node.js building out Solutions
00:18:20
and developing the solutions you'll see
00:18:23
just how fast it is the second is the
00:18:27
really kind of the secret sauce with
00:18:30
node.js is the node package manager and
00:18:33
no package manager allows you to install
00:18:36
additional functionality such as Express
00:18:40
or as a database into your
00:18:43
solution really quick green and there's
00:18:46
over 50 000 bundles available for node
00:18:49
package manager
00:18:51
if you're building out a real-time
00:18:54
application that's data intensive and
00:18:57
you need to have apis quickly developed
00:19:00
then node.js is another great it's
00:19:03
really the great solution for you it
00:19:05
allows you to build out these Solutions
00:19:07
really quickly
00:19:09
and there is a easy synchronization
00:19:12
between the server and the client due to
00:19:15
the code base
00:19:18
and then finally because the structure
00:19:21
of node.js is Javascript if you are
00:19:25
making the pivot from being a front-end
00:19:27
web developer to node.js it's just going
00:19:30
to make it a lot easier for you to pick
00:19:32
up node.js because you have that common
00:19:35
language of JavaScript and on top of
00:19:37
that JavaScript is the world's most
00:19:39
popular scripting language
00:19:42
so let's talk about some of the
00:19:44
differences between angular node.js and
00:19:47
so and the reason why this question may
00:19:49
come up is the person interviewing you
00:19:51
is seeing whether or not you do know the
00:19:54
difference between a front-end framework
00:19:57
and a back-end framework and this is one
00:20:00
of those questions where you can go well
00:20:02
there are differences but the
00:20:04
differences are because they complement
00:20:06
each other so angular is a front-end
00:20:08
development framework whereas node.js is
00:20:11
a server side and framework are the
00:20:14
differences though between the actual
00:20:15
Frameworks themselves is that angular is
00:20:17
written in typescript which is a
00:20:19
modification of JavaScript node.js is
00:20:22
written in C and C plus plus
00:20:24
anger is used for building out single
00:20:27
play client-side web applications and so
00:20:31
that's a keyword there is client-side
00:20:34
whereas node.js is about building out
00:20:37
fast and scalable server-side Network
00:20:40
applications uh so uh again the two
00:20:44
complement each other
00:20:46
uh angular splits web applications into
00:20:48
the MVC and model view control
00:20:50
components whereas node.js generates a
00:20:54
lot of database crazy it does more than
00:20:56
that as well but you can think of
00:20:58
node.js as that glued to your database
00:21:02
let's talk a little bit about when
00:21:04
you're connecting to a database with
00:21:06
node.js and so you're going to probably
00:21:08
be asking what is the most popular
00:21:11
database used with node.js and there are
00:21:15
a couple mongodb is largely the most
00:21:18
popular nosql cross-platform database
00:21:21
MySQL is also very popular and that's a
00:21:24
more traditional relational database
00:21:27
you would go with mongodb for really
00:21:30
more modern solutions when you're
00:21:33
looking at creating an application
00:21:34
that's going to really scale into just
00:21:37
managing masses and masses of data that
00:21:42
has to be created red updated and
00:21:46
deleted very very quickly
00:21:50
for some of the other popular libraries
00:21:53
that you use for node.js express.js is a
00:21:56
very popular one and I really like
00:21:58
working with express.js allows me to
00:22:00
build out web applications really
00:22:02
quickly more importantly it allows me to
00:22:05
build out apis very quickly and which
00:22:08
you know apis are essentially web
00:22:10
applications themselves but being able
00:22:12
to do that very quickly with a framework
00:22:14
like express.js is very useful uh
00:22:17
Mongoose is an application that makes
00:22:19
connecting to a database really
00:22:22
easy so here is an example of express.js
00:22:26
which is a in itself really a flexible
00:22:28
but a solution that you can do lots with
00:22:31
and Mongoose which is a more focused
00:22:34
solution which allows you know to you
00:22:37
make it easier to connect to your
00:22:39
databases
00:22:41
so you know what are the pros and cons
00:22:43
of working with node.js there's lots of
00:22:46
ways we explain this earlier on that you
00:22:47
can actually build out applications that
00:22:50
run on the cloud why would you you know
00:22:53
what's uh the pros and cons so a pro is
00:22:56
that node.js is extremely faster
00:23:00
processing thing an event based model uh
00:23:03
it really is fast I can't is if you have
00:23:06
something that is a very heavy
00:23:08
computational task it's not so good at
00:23:11
that now I will caveat that this is that
00:23:14
node.js is getting better all the time
00:23:17
and so you might have to be provide an
00:23:20
example of what a very heavy
00:23:22
computational task is and that may be uh
00:23:25
calculating a risk on an insurance
00:23:28
application against many many variables
00:23:32
that maybe something that's seen as
00:23:34
computationally very heavy but what you
00:23:36
can do in that example is you can then
00:23:38
offload the task to another Solution
00:23:42
that's designed for it and use apis to
00:23:44
pass the data back and forth
00:23:46
Pro JavaScript is used for building out
00:23:50
your applications with node.js great
00:23:53
lots of people know JavaScript
00:23:56
a restriction and again this is evolving
00:23:59
as JavaScript itself evolves is that
00:24:02
when you do a callback you may end up
00:24:05
doing lots of nested callbacks
00:24:07
um if you're doing something that's very
00:24:09
complicated again another way around the
00:24:12
con and so this is one of the things
00:24:13
that I always look for is if you have a
00:24:16
blocker or a barrier
00:24:18
how do you get around that barrier and
00:24:21
so for instance when you're talking uh
00:24:23
to your recruiter
00:24:25
you can say look the reason why I use
00:24:27
node.js is that it's fast it's event but
00:24:29
it's driven I can use JavaScript there
00:24:32
are some challenges and but what I do to
00:24:35
get around those challenges are and
00:24:36
that's where you can say that you know
00:24:38
you may run the complex script off and
00:24:41
you may write that in net or Java or PHP
00:24:45
and then use an API to do the response
00:24:48
back into node.js so you get the
00:24:50
benefits of Both Worlds but minimize the
00:24:53
investment in having to manage a complex
00:24:56
environment such as Java versus a
00:24:59
relatively simple environment with
00:25:01
node.js the node package manager makes
00:25:04
it extremely easy to access just an
00:25:07
awful lot of functionality with over 50
00:25:11
000 packages there's a package for that
00:25:13
so from being able to have a tool that
00:25:18
creates unique identifiers that you
00:25:20
might need to have for generating
00:25:22
content that gets posted into a database
00:25:24
through to being able to connect to
00:25:27
databases through you know to running so
00:25:30
many different solutions and the npm
00:25:32
package manager with its access to so
00:25:34
many different packages makes it great
00:25:36
for
00:25:38
um getting access to all that content
00:25:39
now Khan is working with relational
00:25:43
databases with node.js isn't as easy as
00:25:46
a nosql database now you can do it and
00:25:50
there are ways around that and what I
00:25:53
would do when this question comes up is
00:25:55
always kind of pivot to say hey this is
00:25:58
how you can actually then get around
00:26:00
building out that application
00:26:05
designed for streaming huge amounts of
00:26:07
data in and out a con is that node.js is
00:26:11
single threaded and so it can be CPU
00:26:13
intensive but again there are ways
00:26:15
around that and a good way around that
00:26:17
is scaling Your solution and elastic
00:26:20
environments such as the cloud
00:26:22
so what is the command used to import an
00:26:25
external library and so to import an
00:26:28
external Library the command is the
00:26:30
require command so an example we have
00:26:33
here is uh you can assign a variable and
00:26:36
the variable is going to be for HTTP and
00:26:38
you're going to then require the HTTP
00:26:41
service and that means that the
00:26:44
application itself won't run unless the
00:26:46
external Library the HTTP library is
00:26:49
installed
00:26:50
okay so those were our introductory uh
00:26:53
questions for node.js this kind of pivot
00:26:55
and take a look at the intermediate
00:26:58
questions that you would be asked
00:27:00
so what does event driven programming
00:27:03
mean so event driven programming means
00:27:06
that if something happens something else
00:27:08
will happen in response so for instance
00:27:10
if you click a mouse that Mouse click is
00:27:13
an event that means something has to
00:27:15
respond to that event just think of it
00:27:18
as cause and effect it's just the basic
00:27:20
motion of physics so that's what event
00:27:23
driven programming means
00:27:25
you also look at it as a callback
00:27:28
function so that when an element is
00:27:31
executed something will happen in
00:27:33
response
00:27:35
so what is an event Loop in node.js so
00:27:39
an event Loop in node.js is when you do
00:27:41
an asynchronous call and what that
00:27:45
essentially means is that you are
00:27:47
sending out data and then a non-blocking
00:27:50
input output from node.js is pulling
00:27:54
data back in
00:27:56
what is an event emitter in node.js so
00:28:01
an event meta has really two areas of
00:28:03
focus one is that it manages uh the
00:28:06
classes that hold all the objects uh
00:28:08
within your event and we have an example
00:28:11
of this on the right hand side and then
00:28:14
whenever an event actually is thrown the
00:28:17
functions are then called on that event
00:28:19
synchronously so for instance we have in
00:28:22
our example on the right hand side we
00:28:25
create an event and then we have the
00:28:28
functions and that executed in a series
00:28:31
from that event
00:28:34
so let's talk about the API functions in
00:28:37
node.js so there are two types one is an
00:28:40
asynchronous non-blocking function and
00:28:43
the second is a synchronous blocking
00:28:46
function and the difference between the
00:28:47
two of them is asynchronous is that
00:28:49
there is no structure to the order if I
00:28:52
have the API is resolved synchronous
00:28:56
means that when the feedback from the
00:28:58
API is received you have to execute the
00:29:01
response in a series for how the
00:29:05
response is sent to you
00:29:07
so what is a package Json file so the
00:29:12
package Json file is at the heart of our
00:29:15
node.js package when we actually will
00:29:18
initialize a solution a folder to be in
00:29:21
node.js package
00:29:24
you'll find that the package itself
00:29:25
holds all of the metadata that's
00:29:28
particular to the project you're working
00:29:30
on such as project name version
00:29:33
requirements it is you have to have it
00:29:35
installed in the root of the directory
00:29:37
for the project and again look at any of
00:29:42
the videos that we have on nodejs we do
00:29:44
have demonstrations within those videos
00:29:47
that actually then go through and break
00:29:49
out how to create that root package and
00:29:54
you'll see how you can actually then go
00:29:55
ahead and update the instructions or the
00:29:58
metadata within the package so here we
00:30:01
have an example of what that metadata
00:30:03
looks like so again this kind of
00:30:05
continues that question of what is a
00:30:07
packet Json file and you may be asked
00:30:09
you know what is the metadata and why is
00:30:12
it important and the metadata is a basic
00:30:16
Json collection of pairing of key
00:30:21
details such as name version description
00:30:23
and then and the custom version that you
00:30:26
put so for instance under name you could
00:30:29
create a name for your project there
00:30:30
can't be any spaces what is the version
00:30:33
and the description and what is the main
00:30:36
or starting path and for the solution
00:30:39
typically that would be index.js but it
00:30:42
could be anything.js but index.js is
00:30:46
typical simply because
00:30:48
index.html is the starting point for a
00:30:51
typical web application
00:30:53
so how would you use a URL module in
00:30:57
node.js
00:30:59
so with a URL module what it allows you
00:31:01
to do is really two things one is that
00:31:03
it provides the resolution passing of a
00:31:07
URLs for Utilities in your application
00:31:10
and then it allows you to extend your
00:31:14
module with built-in Solutions and split
00:31:17
up the web address into a readable
00:31:19
format
00:31:20
so in this example we have the URL and
00:31:25
the response it would would give for
00:31:28
that URL which will then be a year and
00:31:32
month and it'll be in a readable format
00:31:35
so they would read out as 2020 and then
00:31:39
the month
00:31:41
so what is express.js and you've heard
00:31:44
me mentioned this a couple of times in
00:31:45
the video and we actually have a
00:31:46
separate video on express.js
00:31:49
um I would express.js is a web
00:31:51
application framework that allows you to
00:31:52
build out Web Solutions for both mobile
00:31:56
and traditional desktop right inside of
00:32:00
node.js so it's very easy to use
00:32:03
being able to install and web.js is as
00:32:06
simple as requiring Express to be
00:32:08
installed in the example that we have
00:32:10
here on the screen it's a full solution
00:32:13
of showing how to actually build out a
00:32:16
solution with web.js so in this example
00:32:19
you start off the first two lines
00:32:22
required Express to be installed and the
00:32:25
store comes from node packet manager
00:32:27
then we have a simple application that
00:32:29
will then send to the browser window a
00:32:33
hello world message confirming that
00:32:35
Express is up and running and then the
00:32:39
third block of content starting with
00:32:40
vars server actually will Define the
00:32:44
port where your application is going to
00:32:46
run so in this instance the port is
00:32:49
going to run on localhost and the port
00:32:54
will be Port 8081 and so you can
00:32:57
actually go to localhost colon 8081 and
00:33:00
when you do that that will trigger the
00:33:02
Apple application that will forward up
00:33:05
the message hello world and it's all
00:33:07
coming from express.js
00:33:10
so what are streams in node.js so
00:33:14
streams are objects that allow you to
00:33:17
read and write data continuously back
00:33:20
and forth within your application and
00:33:22
there's really four different types of
00:33:24
streams there's readable writable duplex
00:33:27
and transform
00:33:31
the readable one stream through which
00:33:33
data can be read
00:33:35
the writable streams that you can
00:33:37
actually write to a duplex is a stream
00:33:40
where it is both readable and writable
00:33:44
and transform our streams that can be
00:33:47
manipulated the data while it is being
00:33:50
read or written
00:33:53
so how do you update and delete a
00:33:56
dependency so say for instance we want
00:33:59
to install something like Express so if
00:34:02
you wanted to install Express what you
00:34:04
would do is you would just write them
00:34:06
inside of your project you want to go to
00:34:09
terminal window and write in the command
00:34:12
npm install Express
00:34:15
if you want to update the dependencies
00:34:19
within your node package manager to
00:34:21
update all of them all you have to do is
00:34:23
write the command npm update all
00:34:26
dependencies
00:34:27
and then if you want to explicitly
00:34:29
uninstall a dependency such as
00:34:32
express.js that's using the uninstall
00:34:35
command and so that would again be going
00:34:38
to terminal window and you would type
00:34:40
npm uninstall Express
00:34:43
and again it's really easy to create a
00:34:46
simple server in node.js that will run a
00:34:49
simple command the HTTP service is
00:34:52
actually built into node.js you don't
00:34:55
need to use express.js I typically use
00:34:57
express.js when I want to do a web
00:34:59
server because typically what I find is
00:35:01
that I will want to go and do something
00:35:03
more complicated but if you want to do
00:35:04
something that illustrates just the core
00:35:07
functionality within node.js you can
00:35:09
actually just require the core HTTP
00:35:12
service that actually comes as part of
00:35:14
node.js and then you can actually then
00:35:16
go ahead and tell it to create a service
00:35:20
and then to write in plain text I
00:35:25
command or text string such as in this
00:35:28
case it'll be hello world and that would
00:35:30
pop out and then the final line is to
00:35:33
then listen that if you go to a web
00:35:36
browser that's on
00:35:39
port127.0.01 or localhost and go to Port
00:35:43
colon 8080 once you actually go to that
00:35:47
that will trigger this application and
00:35:48
you'll get the text hello world pop up
00:35:51
on your screen
00:35:52
so explain synchronous and non-blocking
00:35:55
apis in node.js
00:35:58
so all the apis in node.js are
00:36:03
asynchronous which means that they are
00:36:04
non-blocking which means you can run
00:36:06
them continuously and scale around that
00:36:10
which is just fantastic it's one of the
00:36:12
reasons why node.js can scale so fast
00:36:14
and the eighth means that the apis can
00:36:17
return data send data after it's been
00:36:19
called and really increase the
00:36:22
efficiency of events as they are
00:36:24
triggered Within node.js
00:36:27
so how do you implement async and you
00:36:30
know JS and so the example that we have
00:36:32
on the left hand side allows us to
00:36:35
trigger async and it's using the async
00:36:38
function and as you can see in this
00:36:40
example it's actually something that can
00:36:42
be done very quickly in this example
00:36:44
we're actually making a command to logo
00:36:47
host and an app that's running on Port
00:36:50
3000 and then depending on what we get
00:36:54
if there's an error message and then
00:36:56
we'll have error message go to the
00:36:58
console log which is the terminal window
00:37:00
and if we get a response to an
00:37:03
application then we'll actually get a
00:37:06
positive response which would be fetched
00:37:08
response so again very quick and easy
00:37:12
that you use the async function to be
00:37:15
able to build out and you to get your
00:37:18
asynchronous code
00:37:21
so what is the purpose of module exports
00:37:24
so a module export is a way to
00:37:27
encapsulate your the entire code for a
00:37:30
solution in a single package and a
00:37:32
single file and then you can then share
00:37:35
that with other developers so you're all
00:37:38
working from the same environment
00:37:41
so what is a callback function in
00:37:44
node.js a callback function is
00:37:46
essentially that once you run and you've
00:37:49
triggered an event mongodb has
00:37:51
consistently been ranked as one of the
00:37:53
top five nosql database Management
00:37:54
Systems so if you're someone who's
00:37:56
applying for a position in database
00:37:58
management roles you will almost
00:37:59
certainly be working with mongodb at
00:38:01
some point now whether you are upgrading
00:38:03
your skills or interviewing for a
00:38:05
database management position using
00:38:06
mongodb it's a good idea to be familiar
00:38:09
with the most frequently Asked mongodb
00:38:11
interview questions and answers in the
00:38:13
latter case it is beneficial for you to
00:38:15
prepare for the interview so that you
00:38:17
are not God off guard even if you are
00:38:19
just interested in learning about
00:38:20
mongodb for the sake of upskilling keep
00:38:23
in mind that acquiring this kind of
00:38:25
knowledge may lead you to looking for a
00:38:27
better job which means you'll be facing
00:38:29
an interview sooner on that note hey
00:38:31
everyone welcome to simple Channel I
00:38:34
hope you guys are doing good and staying
00:38:36
safe in this tutorial we'll be
00:38:38
discussing some specially curated
00:38:39
mongodb interview questions that you
00:38:41
must Master to crack your next interview
00:38:43
so without any further Ado let's get
00:38:46
started with today's topic well but
00:38:48
before we begin if you're new to the
00:38:49
channel and haven't subscribed already
00:38:51
consider getting subscribed to our
00:38:52
Channel simply code to stay updated with
00:38:54
all the latest tech content and hit that
00:38:56
Bell icon to never miss an update from
00:38:58
us so let's get started with today's
00:39:00
tutorial so firstly let us discuss the
00:39:02
agenda now this mongodb interview
00:39:04
question is intended to give you a
00:39:06
general idea of the types of interview
00:39:08
questions you might face now we'll be
00:39:10
covering some theoretical as well as
00:39:12
practical questions in this tutorial now
00:39:14
typically recruiters begin with simple
00:39:16
questions and gradually increase the
00:39:18
difficulty level so in this mongodb
00:39:20
interview questions tutorial we'll start
00:39:22
with the basics and the progress to more
00:39:25
complex questions now before we begin
00:39:27
with the types of questions that are
00:39:28
being asked here's a simple and quick
00:39:31
tip for everyone who is watching this
00:39:33
video now make sure you have the never
00:39:35
give up attitude I know it's that time
00:39:37
of the year where placements are going
00:39:39
in a rampant way but and I know you
00:39:42
might be giving interviews uh regularly
00:39:45
and what if you uh didn't get an offer
00:39:48
in one of the interviews from that so
00:39:50
make sure you have that attitude of
00:39:52
never give up and prepare for your next
00:39:54
interview and whenever you're giving an
00:39:55
interview make sure you are interactive
00:39:57
being interactive is one of the most
00:39:59
best or best way you can say in order to
00:40:02
get uh you know hired by the recruiter
00:40:04
so make sure you're conversing properly
00:40:06
with the interviewer while asking the
00:40:08
questions and finally behave
00:40:09
professionally which is another key
00:40:12
aspect while giving an interview so let
00:40:14
us now discuss the first question which
00:40:16
is the basic question which will be
00:40:18
asked which is explain what is mongodb
00:40:20
and its features so this is how you can
00:40:23
answer mongodb is basically an open
00:40:25
source cross platform nosql document
00:40:27
oriented database management system now
00:40:30
noise sculpin can be utilized as a
00:40:33
substitute for traditional relational
00:40:34
databases like SQL and MySQL which is
00:40:38
dependent on the SQL language right so
00:40:40
if you want to work with large data sets
00:40:43
of distributed data then nosql databases
00:40:45
may be quite supportive which are used
00:40:47
to store large volumes of data in the
00:40:50
form of documents which will offer the
00:40:52
developers the flexibility to work with
00:40:54
the evolving data models as there is no
00:40:56
fixed schema in this now relational
00:40:58
databases such as MySQL and Oracle store
00:41:01
data in tables and rows right they are
00:41:04
based on a branch of a theory known as
00:41:06
relational databases now these
00:41:08
relational databases are structured and
00:41:10
tables can be linked with each other via
00:41:12
a foreign key which is a property of
00:41:15
relational database which is asset
00:41:17
property which is being Satisfied by the
00:41:19
relational database but whereas the
00:41:22
mongodb being a documented oriented
00:41:25
database it can handle only that sort of
00:41:28
information and store as well as
00:41:30
retrieve information from these
00:41:31
documents only it provides the
00:41:33
flexibility as well as scalability that
00:41:35
you want with the querying and indexing
00:41:37
according to your requirement this
00:41:39
mongodb basically is based on json-like
00:41:42
documents where we store all the
00:41:43
information in that so this is how you
00:41:45
can answer the question which is what is
00:41:47
mongodb and its features
00:41:50
well the next question is what are some
00:41:53
alternative nosql databases to mongodb
00:41:56
now we have various Alternatives from
00:41:58
mongodb such as Cassandra Apache
00:42:00
Cassandra is a free and open source
00:42:03
distributed nosql database management
00:42:05
system which is again similar to that of
00:42:07
mongodb to handle large amounts of
00:42:09
unstructured data across the servers
00:42:12
providing High availability with no
00:42:14
single point of failure Apache Cassandra
00:42:17
is a database which can be a right
00:42:19
choice when you need scalability and
00:42:21
also High availability without
00:42:22
compromising performance next we have
00:42:25
redis redis is actually another uh
00:42:28
popular nosql database which is an open
00:42:30
source which is implemented as a
00:42:33
distributed key value store with
00:42:34
optional durability it can be also used
00:42:37
as a catchy Adam message broker also we
00:42:40
have other types other popular noise
00:42:42
databases like Amazon Dyno dynamodb
00:42:45
Apache headspace and neo4j now HPS again
00:42:48
is an open source non-relational uh
00:42:50
distributed database guys it is
00:42:52
generally written in JavaScript and it
00:42:54
is also developed as part of the Apache
00:42:56
software foundation so these are some of
00:42:59
the examples and can be used in
00:43:01
alternative to mongodb
00:43:03
all right let us now move to the next
00:43:05
question which is what type of nosql
00:43:08
database is mongodb now in general we
00:43:11
have four different types of categories
00:43:13
when we talk about in which category
00:43:15
mongodb comes under so basically we have
00:43:17
key value column based document database
00:43:20
and graph database now when I talk about
00:43:23
key value these database store data as
00:43:25
an index key and value pairs this
00:43:28
database is stored data in a schema-less
00:43:30
way example of a key value data store
00:43:33
include Cassandra redis dynamodb and Etc
00:43:36
next we have column based now column
00:43:39
based or column store type of database
00:43:41
is the one where these databases are
00:43:44
designed to store data as Columns of
00:43:46
data rather than as rows as data if it
00:43:49
stores in a row type of data it becomes
00:43:51
a traditional which is not a noise
00:43:53
database right so again example of a
00:43:56
column store databases are hbase even
00:43:58
Cassandra comes under the column based
00:44:01
as well next we have the document data
00:44:03
database which is actually the type of
00:44:06
nosql database that we are looking for
00:44:07
which is mongodb now document databases
00:44:10
had designed to store documents with
00:44:12
each document having a unique key and
00:44:15
popular document databases are couch
00:44:17
base and mongodb and finally we also
00:44:19
have a graph type of database where they
00:44:22
are based on graph Theory so these
00:44:24
databases are basically designed for
00:44:26
data which needs to be represented as
00:44:28
graphs so the data that is present in
00:44:31
this sort of database is interconnected
00:44:33
with multiple number of relationship
00:44:36
between them in in the form of graphs
00:44:38
and trees and a popular graph database
00:44:41
is neo4j as well as big data so this is
00:44:45
what mongodb is and it comes under the
00:44:48
document database type of noise scale
00:44:50
database the next question is how does
00:44:53
mongodb store data now data in mongodb
00:44:56
is stored in based on documents or the
00:44:58
Json style data structures documents
00:45:01
contain one or more fields and each
00:45:04
field contains a value of a specific
00:45:06
data type so mongodb stores data records
00:45:09
as documents which are in the form of
00:45:11
based on documents which are gathered
00:45:13
together in collections so these
00:45:16
documents as we said earlier has a sub
00:45:19
specific data types including let's say
00:45:21
arrays normal General data and these
00:45:24
documents tend to share a similar
00:45:26
structure which are organized as
00:45:28
collection so you can say a group of
00:45:30
documents are kept in a collection it
00:45:33
may be helpful to think of documents as
00:45:34
in a comparison to the rows in a
00:45:37
relational database so fields are
00:45:39
similar to columns and collections are
00:45:41
similar to tables in mySQL database
00:45:44
which is again a no it's a relational
00:45:46
database so this is how mongodb stores
00:45:48
data the next question is mongodb is a
00:45:52
schemailers database if yes how do you
00:45:55
create schema in mongodb now the scheme
00:45:57
of a data base describes the structure
00:45:59
of the data to be stored right in a
00:46:01
relational database the schema defines
00:46:03
its tables its fields in each table and
00:46:07
the relationship between each field and
00:46:09
each table so if you take SQL as an
00:46:12
example which is a schema based database
00:46:15
right so in schema is defined by the
00:46:16
tables and the fields that is the
00:46:19
columns and rows that are present in it
00:46:20
and the relation between them
00:46:23
on the other hand we have mongodb now in
00:46:26
documented oriented databases like
00:46:28
mongodb data is stored in collections of
00:46:31
key value pairs now given that Json is a
00:46:34
schema free data structure and that
00:46:36
mongodb depends on it it would be more
00:46:38
accurate to say that it has a
00:46:40
dynamically typed data so whenever you
00:46:42
create an insert a document to create a
00:46:45
schema it will automatically create one
00:46:47
for you so whenever a document is added
00:46:49
the database will automatically create
00:46:51
the corresponding collection
00:46:53
the next question is how is mongodb
00:46:56
different from SQL and better than MySQL
00:46:58
now mongodb is again a documented
00:47:01
oriented nosql database which is used to
00:47:03
store high volume of data and which
00:47:05
needs to process your huge data in a
00:47:08
quick session now it is a database that
00:47:10
came into picture around the mid 2000s
00:47:13
and it is again considered into the
00:47:15
category of a nosql database whereas
00:47:17
when you take SQL SQL is a programming
00:47:20
language used to communicate with and
00:47:22
manipulate relational databases for
00:47:24
example MySQL now there are quite
00:47:28
differences between both of these
00:47:30
databases basis right being being one as
00:47:33
a relational database the other being
00:47:34
relational and non-relational database
00:47:37
there are quite differences between them
00:47:38
so for example if you take the structure
00:47:40
in SQL data is represented in tables
00:47:43
whereas the data is represented in
00:47:44
documents and this further documents are
00:47:46
stored in collections now schema again
00:47:49
SQL has a predefined schema so whenever
00:47:51
you are creating a table you need to
00:47:53
predefine its schema whereas mongodb
00:47:56
does not have the implications of
00:47:58
specifying any schema before working on
00:48:00
it so it has basically a dynamic schema
00:48:02
next we have this scalability the data
00:48:05
in SQL can be vertically scalable and
00:48:07
when it comes to mongodb both horizontal
00:48:10
and vertical scalable of scaling of data
00:48:12
is possible when I talk about
00:48:14
transactions SQL also supports Atomic
00:48:16
operations and follows asset properties
00:48:18
whereas Bongo DB does not have proper
00:48:21
support for transactions and it follows
00:48:23
cap theorem and finally the type of
00:48:25
operations now some operations that we
00:48:29
perform in relational databases like SQL
00:48:32
for example SQL supports join operation
00:48:34
whereas we don't have the same sort of
00:48:37
join operation and mongodb so in this
00:48:40
way mongodb is different from SQL and in
00:48:43
some ways it is better than MySQL in
00:48:46
terms of processing a lot of
00:48:47
unstructured data and also has certain
00:48:49
features like replication sharding and
00:48:53
mapreduce and some of more critical
00:48:55
features that are not present in MySQL
00:48:58
well the next question is what are the
00:49:00
different data models in mongodb now
00:49:03
data models are categorized into two
00:49:05
types the first one is embedded data
00:49:07
model the next one is referent data
00:49:09
model now if I talk about Emirate data
00:49:11
model embedded documents capture
00:49:13
relationship between data by storing
00:49:15
related data in a single document
00:49:17
structure whereas reference data models
00:49:20
store the relationship between data by
00:49:23
including any links or references from
00:49:25
one document to another
00:49:27
moving on to the next question the next
00:49:29
question is how does indexing Works in
00:49:32
mongodb now a good indexing strategy be
00:49:35
it a relational database or a nosql
00:49:38
database it is essential for ensuring
00:49:40
that your database returns your results
00:49:42
as quickly as possible now mongodb
00:49:45
indexing is a special data structure on
00:49:47
which the index is created to hold the
00:49:49
data of a specific fields in a document
00:49:52
now in the absence of indexing in
00:49:54
mongodb there is a need to scan every
00:49:56
collection which is basically a
00:49:58
collection scan so mongodb indexes make
00:50:01
it unnecessary to perform a collection
00:50:03
scan which involves looking through
00:50:05
every document in collection from
00:50:07
matches to your query it also provides
00:50:09
effective indexing strategy now any
00:50:11
collection in mongodb can have one or
00:50:14
more indexes and those indexes can be
00:50:16
made on one or more multiple Fields And
00:50:18
even through throughout a mongodb
00:50:20
database so you need a good indexing
00:50:22
strategy to quickly add let's say
00:50:24
effectively access the data you required
00:50:27
from it and it also provide search
00:50:28
efficiency now indexing is a necessary
00:50:31
operation in mongodb which will bring
00:50:33
search efficiency in various execution
00:50:36
of statements so this is how indexing
00:50:38
Works in mongodb
00:50:41
so moving on to the next question what
00:50:43
is mongodb replication and sharding now
00:50:46
if I talk about replication replication
00:50:48
means duplicating the same data across
00:50:51
multiple mongodb servers so the main use
00:50:53
of replication is the data is available
00:50:56
at an instant way that is high
00:50:58
availability of data and it also
00:51:00
supports data redundancy and multiple
00:51:03
copies of of the data are being saved
00:51:06
across servers and also it provides data
00:51:09
recovery and backup options as well so
00:51:12
in a nutshell you can say that database
00:51:13
replication is the process of copying
00:51:16
data from one database in one server to
00:51:20
another database in another server
00:51:22
ensuring that the same data is available
00:51:24
on more than one mongodb server so again
00:51:28
the main purpose of using replication is
00:51:30
data redundancy and high availability so
00:51:33
by keeping data several copies or
00:51:35
replica stored on physically separate
00:51:37
servers it will ensure that the data is
00:51:40
protected and it is also accessible
00:51:43
whenever we need and also by generating
00:51:45
multiple copies of your data replication
00:51:47
enables you to increase data
00:51:49
availability which is also another
00:51:50
important factor this is especially
00:51:52
helpful if a server fails so in that
00:51:55
case you can use the replication and
00:51:57
finally you can also recover the data
00:52:00
that is lost due to any uninterrupted or
00:52:02
any hardware failure issues
00:52:05
now if I talk about sharding sharding is
00:52:08
also similar to that of replication but
00:52:10
it is a method of Distributing data
00:52:12
across multiple databases and mongodb
00:52:15
supports this deployment of data with
00:52:18
having large data sets and high
00:52:20
throughput via sharding
00:52:22
so let's take an example so you can give
00:52:24
an example to the recruiter like this
00:52:27
let's say I have a database having 2
00:52:29
million users and it has a capacity
00:52:31
which is 2 million records now what I'm
00:52:34
doing is I'm basically Distributing the
00:52:36
data across multiple databases and I'm
00:52:38
storing different data in different
00:52:41
databases now we have two machines which
00:52:43
has one million user capacity and
00:52:45
another one million user capacity
00:52:48
so in this way you can add more and more
00:52:51
multiple databases in order to store
00:52:53
your data
00:52:55
so by adding more capacity to a single
00:52:58
server such as adding more memory and
00:53:00
processing units or adding more RAM on a
00:53:02
single server that can be done using
00:53:05
sharding
00:53:06
let us now to move on to the next
00:53:08
question which is explain horizontal and
00:53:10
vertical scaling now vertical scaling
00:53:12
refers to adding more resources like CPU
00:53:15
Ram or any hardware or hard drive disk
00:53:19
space to your server which is again a
00:53:21
database or an application server which
00:53:23
is done on demand on the other hand
00:53:26
horizontal scaling refers or involves
00:53:28
adding more processing units or physical
00:53:30
machines to your server or databases now
00:53:33
mongodb which is a nosql database
00:53:36
handles horizontal scaling through
00:53:37
sharding so in a nutshell you can say
00:53:40
that vertical scaling can be used in
00:53:41
order to increase or decrease the
00:53:43
capacity of existing Services whereas
00:53:45
horizontal scaling adds more resources
00:53:47
like virtual machines to your system to
00:53:50
spread out the workload across them the
00:53:52
next question is when should we embed
00:53:54
one document with another so you should
00:53:56
consider embedded document that is sub
00:53:58
document whenever you rely on these four
00:54:02
factors that is when the relationship is
00:54:04
one to few that is it can be one two one
00:54:06
too many but not one to one so for
00:54:09
unlimited use case you should start
00:54:11
considering separating sub documents
00:54:13
into another collection the next
00:54:15
situation is when retrieval is likely to
00:54:17
happen together which will improve the
00:54:20
performance in such case you can embed
00:54:22
one document with another the next
00:54:24
factor is when updates are likely to
00:54:26
happen at the same time you can use this
00:54:29
multi-document transaction by embedding
00:54:31
data model and finally when the field is
00:54:34
rarely updated in such case you can use
00:54:37
the embedded document
00:54:39
well let us now move on to the next
00:54:40
question which is what are replica cells
00:54:43
and explain primary and secondary
00:54:45
replica sets in mongodb the process of
00:54:48
replication as we discussed earlier is
00:54:51
done via using replica sets in simple
00:54:54
words it is a group of mongod processes
00:54:57
to keep the same data across different
00:54:59
servers now a replica set is basically a
00:55:03
collection of related mongodb nodes
00:55:05
which must have three notes at least now
00:55:08
one of them must be a primary and the
00:55:10
rest secondary ones and a replication
00:55:12
structure can have up to 50 nodes so the
00:55:16
main types of nodes that we have is
00:55:18
primary and the secondary or you can
00:55:20
call it them as primary and secondary
00:55:22
replica sets now when I talk about
00:55:24
primary replica set it is the primer is
00:55:27
the member in the replica set that
00:55:29
receives the write and read operations
00:55:31
but read operations can be pointed out
00:55:33
to secondary nodes changing the
00:55:35
configuration at the moment to perform
00:55:37
the query beside is the replica set can
00:55:40
have only one primary node at most and
00:55:43
talking about secondary the secondary is
00:55:45
the node where the data is replicated to
00:55:48
maintain a copy a replica set can have
00:55:50
one or more secondary nodes and the
00:55:53
clients cannot write data to secondary
00:55:55
ones only they can read from them and if
00:55:58
at all there is any failed node it works
00:56:01
as a secondary node again until it is
00:56:03
until a new primary node will be
00:56:06
replaced with that so this is what a
00:56:09
replica set means and the type of
00:56:11
replica set which is the primary and
00:56:13
secondary I hope you understood this
00:56:15
so moving on to the next question which
00:56:17
is what is the use of capped collections
00:56:21
now the size of collection in mongodb is
00:56:23
typically unrestricted right so the
00:56:25
collection increases its size as more
00:56:27
documents are being added to that now a
00:56:30
capped collection is a special type of
00:56:32
collection that has either a fixed
00:56:34
number of documents in a collection or
00:56:36
fixed number of elements so it creates
00:56:39
new documents by overriding the oldest
00:56:42
documents present in that collection so
00:56:44
collections can have maximum size or
00:56:47
document counts that prevent them from
00:56:49
growing beyond the maximum threshold
00:56:51
that is being allocated and all capped
00:56:54
collections must specify a maximum size
00:56:56
and may also specify a maximum document
00:56:59
count only now mongodb removes older
00:57:02
documents if a collection reaches the
00:57:04
maximum size limit before it reaches the
00:57:06
maximum document count so overall the
00:57:09
structure and functionality of a capped
00:57:12
collection supports high performance for
00:57:14
credit operations like create read and
00:57:17
delete so this is what cap collection
00:57:20
says and some of it characteristics and
00:57:22
why we use it
00:57:24
let us now move on to the next question
00:57:25
which is how can you store images videos
00:57:28
and other large files now we often need
00:57:31
to store files in our databases but
00:57:33
mongodb sometimes or it doesn't let you
00:57:36
store any file larger than 16 MB in a
00:57:39
normal document so what you have to do
00:57:41
instead mongodb has a functionality
00:57:43
specifically for storing large files and
00:57:45
it goes by the name gridfs yes you have
00:57:48
heard it right grid FS is a driver
00:57:50
specification for uploading and
00:57:52
retrieval of mongodb files which are
00:57:54
larger than 16 MP in order to store
00:57:56
images videos and other large files it
00:58:00
is one of the most popular
00:58:01
specifications and it it has a size
00:58:04
limit of more than 16 MB so you can
00:58:07
store images videos that have size more
00:58:09
than of 16 MB now chunks of files like
00:58:13
be it and audio it update of PDF file or
00:58:16
anything it is being streamed as a
00:58:18
chunks so these are streamed into the
00:58:21
database and each chunk is limited 255
00:58:25
KB in this size this means that the last
00:58:28
chunk is normally either equal to or
00:58:30
less than 255 KB so whenever you read
00:58:32
from grade FS the driver resembles all
00:58:35
the chunks as needed this means that you
00:58:37
can read sections of a file as per your
00:58:40
query range
00:58:42
so I hope you understood uh what is grid
00:58:44
fs and what is the process to store
00:58:47
images videos and other large files
00:58:49
which is of more than 16 MB so basically
00:58:51
the interviewer want to know that
00:58:53
whether you are not familiar with the
00:58:55
concept of grid FS so that is the reason
00:58:58
he might ask you this question so you
00:59:00
have to be well prepared for it
00:59:02
well the next question is explain
00:59:03
aggregation in mongodb mongodb
00:59:06
aggregation process the data records
00:59:08
during an aggregation operation and
00:59:10
returns a single competent result just
00:59:13
like any other operations that are
00:59:15
performed in a relational database
00:59:16
similar to that aggregation is also used
00:59:18
in order to act on a group of values
00:59:21
from multiple documents present in a
00:59:23
collection to perform operations for
00:59:25
this grouped values and return a single
00:59:27
competed results now it actually groups
00:59:31
multiple documents which applies an
00:59:33
aggregation operation and it is
00:59:35
basically returning as the particular
00:59:37
value that we want from that operation
00:59:40
now there are various ways on how you
00:59:42
can perform aggregation we have three
00:59:44
different ways of carrying the
00:59:46
aggregation process in mongodb the first
00:59:48
one is aggregation pipeline next we have
00:59:51
mapreduce and finally we have single
00:59:53
purpose aggregation so you can further
00:59:56
explain each of these aggregation uh
00:59:58
depending upon the interviewer's
01:00:00
preference so basically I will
01:00:01
irrigation process in mongodb is modeled
01:00:04
on the concepts of data processing
01:00:06
pipeline so multiple document enter the
01:00:09
pipeline and then these documents are
01:00:11
being transformed into the aggregated
01:00:13
results next we have the map reduce as
01:00:16
the name suggests it does to operation
01:00:17
which is mapping and then reducing that
01:00:20
operation so it will map each document
01:00:23
and process along with one or more
01:00:25
objects for each document and reduce
01:00:28
phase in which output of map operations
01:00:31
are being combined together and finally
01:00:33
we have single purpose aggregation
01:00:35
operation where these operations
01:00:37
aggregate all the documents from a
01:00:39
single collection in mongodb now even
01:00:42
though they provide a simple access to
01:00:44
the basic aggregation operations they
01:00:47
lack the flexibility that are being
01:00:49
provided by the aggregation Pipeline and
01:00:51
map reduce operation
01:00:54
so these are the three uh aggregation
01:00:57
pipeline method which they go through
01:00:59
first is basically the math stage which
01:01:01
will filter the records or the documents
01:01:03
we need to work with uh and next it
01:01:06
performs the group operation which
01:01:08
basically is the aggregation and finally
01:01:10
it will sort the data so it will sort
01:01:12
the resulting documents the way we
01:01:14
require that is an ascending and
01:01:16
descending order now just like uh any
01:01:19
other operations given by aggregation in
01:01:21
mongodb we also have five different
01:01:23
types of operations that we can perform
01:01:25
which is sum which will add up the
01:01:28
values of every document next we have
01:01:30
average which will complete the average
01:01:31
value of every document and we have Min
01:01:34
which returns a minimum value from a
01:01:36
document and we have Max which will
01:01:38
written the maximum value within a
01:01:40
collection and finally we have Push
01:01:42
which will add the value to an array in
01:01:44
the document moving on to the next
01:01:46
question what is mean by ID field in
01:01:49
mongodb ide is the field that uniquely
01:01:52
identifies a document present in the
01:01:54
mongod EB collection so when you are
01:01:56
trying to insert a new document into the
01:01:58
database mongodb will automatically
01:02:02
create a unique ID field which will have
01:02:05
a unique value to its name now by
01:02:07
default mongodb creates a unique index
01:02:09
for the ID field during the creation of
01:02:12
any collection and the ID field is
01:02:14
always the first field in the document
01:02:16
and if the server receives a document
01:02:18
that does not have any ID field first
01:02:20
then the server will move the field at
01:02:22
the beginning and also ID field can be
01:02:25
avoided in the document that you want to
01:02:27
return by setting the value of the ID
01:02:29
field as 0 in the query
01:02:32
so what are some utilities for backup
01:02:34
and restoring in mongodb now by default
01:02:38
mongodb shell does not include any
01:02:40
import export of data or even
01:02:42
duplication or retrieval of uh data from
01:02:46
other uh you know applications but
01:02:48
however mongodb provides the utilities
01:02:51
and database tools to take backup and
01:02:54
perform the restore operations now
01:02:56
mainly we have four type of backup and
01:02:58
restoring options which are import
01:03:01
export term and malware
01:03:04
restore so you can use one of these
01:03:06
utilities like Dom import export
01:03:10
and restore to move your data in and out
01:03:13
of your mongodb database now the most
01:03:15
commonly used are mongodum and
01:03:18
restore the mongodon utility creates a
01:03:20
binary backup you know of a mongodb
01:03:22
database the mongodom tool is the
01:03:25
preferred method of dumping data from
01:03:27
your Source mongodb deployment and if
01:03:29
you're trying uh to restore the data
01:03:32
that you have basically deleted or
01:03:34
dumped you can use the Monger register
01:03:36
in order to fetch back the data that you
01:03:39
have dumped
01:03:42
so the next question is can you explain
01:03:44
about mapreduce process in mongodb
01:03:48
mapreduce is basically a data processing
01:03:51
Paradigm for condensing large volumes of
01:03:53
data into useful aggregated results so
01:03:57
basically mongodb provides the map
01:03:58
reduce features for only aggregation
01:04:00
purposes and generally there are two
01:04:03
phases of the map reduce as you can see
01:04:05
in the name which is mapping and
01:04:06
reducing so in the first phase each
01:04:09
document is processed and emits common
01:04:11
and redundant part of the document to
01:04:13
pass a unique record for the next phase
01:04:16
and in the next phase all the unique
01:04:18
part gets together and aggregated to
01:04:20
produce a single result and finally we
01:04:23
have a query here we'll pass the query
01:04:25
to filter the resultant set so with the
01:04:28
help of map reduce user can perform
01:04:30
sorting filtering and document
01:04:32
modification as per their need
01:04:35
so moving on to the next question which
01:04:37
is how does mongodb Ensure High
01:04:39
availability of data
01:04:42
in general High availability refers to
01:04:45
the uh you know Improvement of a system
01:04:47
or any applications availability by
01:04:49
minimizing the downtime caused by
01:04:51
routine maintenance or any hardware
01:04:54
related uh you know issues so mongodb
01:04:57
automatically stores copy sets and
01:04:59
multiple copies of data distributed
01:05:01
across servers and data centers now in
01:05:05
general mongodb is one such database
01:05:07
which can provide High availability for
01:05:09
the users by using features like
01:05:11
replication and sharding now in
01:05:13
replication the replica sets help
01:05:15
prevent website downtime using native
01:05:17
duplication and automatic failures now
01:05:20
mongodb has a great support for high
01:05:22
availability without no thought through
01:05:25
replication set but replica set is not
01:05:27
enough for a production ready system
01:05:29
that is it requires a bit of planning in
01:05:32
order to deploy this so sometimes it
01:05:35
might be an issue but in most of the
01:05:37
cases if the system crashes or the
01:05:39
hardware or software faces any issues uh
01:05:41
you know ODB in the data mongodb helps
01:05:44
you recover and backup your data in the
01:05:47
system
01:05:49
so the next question is what is the role
01:05:51
of profiler in mongodb now so far we
01:05:54
have discussed some of the basic to
01:05:56
moderate uh level questions guys now
01:05:58
from here on you will find some
01:06:00
practical as well as you know advanced
01:06:02
level questions so you might need to
01:06:05
focus a little bit and even if you're
01:06:07
not confident and if you don't know the
01:06:09
answer which we are discussing now you
01:06:11
can directly tell to the recruiter of
01:06:13
the interviewer that you do not know the
01:06:16
answer but you hope that you have an
01:06:17
idea on this and you can work on that
01:06:19
and you can get back to him so again
01:06:22
let's get back to the question which is
01:06:23
what is the role of profiler in mongodb
01:06:26
now database profiler is used to collect
01:06:28
information regarding the queries which
01:06:30
are executed on an individual database
01:06:32
instance so basically this uh profiler
01:06:36
in mongodb database allows you to
01:06:37
collect performance data about
01:06:39
operations occurring on a mongodb
01:06:42
instance
01:06:47
the next question is can we use regular
01:06:49
expressions in mongodb now in SQL we do
01:06:52
have regular Expressions where we need
01:06:54
uh where we write a query to find
01:06:57
certain patterns that are present in our
01:06:59
database table right in a similar way
01:07:02
regular expressions are also used to
01:07:04
match patterns in a document just like
01:07:06
finding a pattern in an SQL tables so
01:07:09
regular expression basically provides
01:07:11
patterns a sequence of characters for
01:07:13
matching and defining a search pattern
01:07:15
and also retrieving an unidentified
01:07:17
field using a certain pattern becomes
01:07:20
easily within a document and querying a
01:07:22
database in order to find a smaller
01:07:24
subset of data within a collection we
01:07:27
can use regular expression so regex
01:07:29
operator in mongodb provides regular
01:07:32
expression capabilities from pattern
01:07:34
matching strings in the queries and the
01:07:36
syntax is followed as DB dot collection
01:07:39
name dot file mention the field name and
01:07:42
mention the reex keyword and mention the
01:07:44
pattern now the pattern can be of any uh
01:07:48
of your choice
01:07:51
so the next question is how do you
01:07:53
search for documents in which a specific
01:07:55
field has one or more values now you can
01:07:58
say this is a bit of practical question
01:08:00
guys the interviewer wants to know
01:08:02
whether you are not uh whether or not
01:08:05
you are comfortable and have an idea of
01:08:08
using various operators in mongodb so
01:08:11
you can use the DB dot collection file
01:08:13
operation and also use a query operator
01:08:16
which is dollar in in order to specify
01:08:18
the field and the values that you want
01:08:20
to retrieve or you want to search for
01:08:22
inert document so for example I have
01:08:24
given an example which says that in
01:08:26
order to return all employees whose
01:08:29
title is product manager or executive
01:08:31
director in such case the query would be
01:08:34
DB dot employees dot find mention the
01:08:37
field which is title mention the uh in
01:08:39
which is a query operator here mention
01:08:41
the product manager and executive
01:08:43
director which we are trying to find so
01:08:45
if there is any record or the person who
01:08:49
is associated associated with this title
01:08:51
of product manager or executive director
01:08:54
it will retrieve the record now we have
01:08:56
a person name whose first name is Rahul
01:08:58
and last name is Kumar whose ages 29 and
01:09:01
title is product manager so this is how
01:09:04
you can search for a document with a
01:09:06
specific field which has one or more
01:09:08
values
01:09:11
so the next question is which command
01:09:13
are used to insert single and multiple
01:09:15
documents into a collection now we
01:09:18
basically have two types of commands
01:09:20
which is DB dot collection dot insert1
01:09:22
which will insert a single document into
01:09:24
a mongodb collection and it returns a
01:09:27
document containing the inserted
01:09:28
documents ID field and next we have the
01:09:31
same uh command but the keyword changes
01:09:35
which is insert mini which is insert a
01:09:37
single or even multiple records uh into
01:09:40
a mongodb collection again it returns a
01:09:43
document containing each inserted
01:09:45
document's ID
01:09:48
well the next question is what is the
01:09:50
difference between
01:09:51
all and in operator in mongodb now both
01:09:55
all and in operator are used to filter
01:09:57
documents in a sub array based on a
01:10:00
conditional statement so but there are
01:10:03
some differences or subtle differences
01:10:05
between all and in operator now when I
01:10:08
talk about all operator all operator
01:10:10
retrieves all the documents which
01:10:12
contains a subset of the value we pass
01:10:14
and this subset might be in any order
01:10:17
but whereas in operator retrieves all
01:10:20
the documents which contains the either
01:10:23
of the values we pass
01:10:25
moving on what is the next question is
01:10:28
both rights and rates become faster when
01:10:31
you add more slaves to replica set as
01:10:34
the statement true or false explain the
01:10:36
reason well this statement is false now
01:10:38
a replica set can only have a primary uh
01:10:42
at any particular time that is having a
01:10:44
one master with other nodes the
01:10:46
secondary nodes being slaves so all
01:10:49
right operations are performed only on
01:10:51
the master node read operations on the
01:10:53
other hand can be performed on any
01:10:55
instance which can be a slave or a
01:10:57
master node so as a result adding more
01:11:00
slaves to a replica set accelerates only
01:11:02
reads operation and nods the and not the
01:11:05
rights operation so the statement is not
01:11:09
valid and it is a false statement we
01:11:11
cannot uh you know write and read both
01:11:13
uh operation when you add more slave to
01:11:16
replica set
01:11:18
the next question is what is Shard e and
01:11:21
mention the components of mongodb
01:11:22
sharded cluster now what is a short key
01:11:25
chart key is used by mongodb to
01:11:27
distribute the documents of a collection
01:11:29
across charts now on charting a mongodb
01:11:32
data set a Shard key is automatically
01:11:35
created by default so the short key can
01:11:37
be in the form of indexed field or
01:11:39
indexed compound fields that will be
01:11:41
used to distribute the data among the
01:11:43
shots generally The Shard key is used to
01:11:46
distribute the mongodb's collections
01:11:48
documents across all the shots where the
01:11:50
key consists of a single field or
01:11:52
multiple fields in every document now
01:11:54
the idea is to have multiple replica set
01:11:57
with multiple primaries which would
01:11:59
basically divide data and load it among
01:12:01
themselves and each of these replica set
01:12:04
is called as shard
01:12:06
chat basically has three components
01:12:09
which is basically Shard Mongoose and
01:12:13
config serger all this together
01:12:15
comprises of a mongodb sharded cluster
01:12:19
now when I talk about Shard what is a
01:12:21
Shard Shard contains a subset of the
01:12:24
sharded data okay A Shard is basically a
01:12:28
single mongodb server or a replica set
01:12:30
that stores a partition of the
01:12:32
application data that you have divided
01:12:34
now next we have the mongos Mongoose
01:12:38
router or the it is a router of
01:12:40
operations now because each chart
01:12:42
contains only part of the cluster data
01:12:45
you need something to root operations to
01:12:47
the appropriate charts that's where
01:12:49
mongos comes in the Mongoose process is
01:12:52
a router that directs all the reads
01:12:54
writes and commands to the appropriate
01:12:57
shard in this way mongos provides client
01:13:00
with a single point of contact with the
01:13:02
cluster and finally we have config
01:13:04
servers now Mongo's process are
01:13:07
basically a durable should be durable
01:13:10
that means it must be in a position to
01:13:13
store the metadata in order to properly
01:13:16
manage the cluster right which we have
01:13:19
formed with the short key so that's the
01:13:21
job of the config server this metadata
01:13:24
includes the cluster configuration the
01:13:27
location of each database collection and
01:13:30
the particular range of data there so
01:13:32
this is what basically shark Key is and
01:13:35
multiple components that are included in
01:13:37
the mongodb sharded cluster
01:13:41
so moving on to the next question which
01:13:43
is the joint plus is a key feature of
01:13:45
relational database systems what is the
01:13:47
mongodb equivalent if any and are there
01:13:50
any limitations now whenever we hear
01:13:52
about joints we have like different
01:13:55
operations like inner join after join
01:13:58
left join and uh you know cross join so
01:14:02
similarly we have a question here that
01:14:04
means if we talk about no SQL that means
01:14:06
we do not have no joints that means we
01:14:08
do have joints or we do not have joints
01:14:10
that's the main question but the thing
01:14:12
is we have a joint equivalent in mongodb
01:14:15
also which is the lookup operator which
01:14:18
is a significant disadvantages that is
01:14:21
it does not work in charted collection
01:14:23
right so it's worth noting that rather
01:14:25
than looking for a direct equivalent to
01:14:27
join mongodb developers often simply
01:14:30
denormalize the data and which
01:14:33
eliminates the need for a join you know
01:14:35
operation in a mongodb database so in a
01:14:38
nutshell you can say it performs an
01:14:40
outer join to a collection in the same
01:14:43
database to filter the documents from
01:14:45
The Joint collection for processing now
01:14:47
the lookup operator adds a new array
01:14:50
field to each input document and this
01:14:52
new array field contains the matching
01:14:54
documents from The Joint collection
01:14:59
so the next question is mention some
01:15:00
pros and cons of normalizing data in
01:15:03
mongodb database now normalizing data is
01:15:06
a key factor in relational database but
01:15:08
what about mongodb now updated documents
01:15:11
is fast for raw normalized data and it
01:15:13
is relatively so slower for denormalized
01:15:16
data well on the other hand reading
01:15:18
documents is fast in denormalized data
01:15:20
and slower for normalized data so
01:15:23
denormalized data is hard to keep in
01:15:25
sync and takes up more space so rdbms
01:15:28
generally have this organic support
01:15:31
for normalization and a lot of data to
01:15:34
be managed as a separate entity whereas
01:15:36
nosql dbmss like mongodb do not have
01:15:40
this active support for normalization
01:15:44
so the next question is what are the
01:15:46
advantages of using mongodb now there
01:15:49
are various advantages of using mongodb
01:15:51
for example it is an open source DB that
01:15:54
is it is ready readily available for
01:15:56
everyone to download and perform the
01:15:58
operations right away and it is also
01:16:00
easy to use the syntax is also user
01:16:03
friendly just like SQL it is also highly
01:16:06
flexible which allows you to store and
01:16:08
work on different data types and allows
01:16:11
you to store unstructured data of
01:16:12
different types in one or more documents
01:16:14
and the security is also a Paramount
01:16:17
Feature for any user right so mongodb
01:16:19
provides Advanced security features as
01:16:22
well and we also talked about high
01:16:24
availability in our previous question
01:16:25
and it also has reliable indexing for a
01:16:28
faster retrieval of data it has a
01:16:30
flexible schema design unlike the uh
01:16:33
predefined schema in relational
01:16:35
databases so this flexible or the
01:16:38
dynamic schema design allows you to meet
01:16:40
the ever-changing conditions of the Big
01:16:42
Data applications uh you know with the
01:16:45
vast amount of data that is being
01:16:46
incorporated into the documents you can
01:16:49
have a better Edge on the data if you're
01:16:52
working on large scale applications then
01:16:54
moment DB can be a great choice for you
01:16:56
with all this it also gives you high
01:16:59
performance which is another key feature
01:17:01
of mongodb and one of its greatest
01:17:04
advantage of a noiseql database
01:17:06
and that gives us the last question of
01:17:09
our interview question uh which is what
01:17:12
are some applications of mongodb now
01:17:15
mongodb being a nosql database is widely
01:17:18
popular in many uh sectors nowadays and
01:17:21
some of the major applications or
01:17:23
real-time use case of mongodb is it is
01:17:26
used in iot which is internet of things
01:17:28
with the world rapidly uh advancing in
01:17:32
uh you know in technology iot plays a
01:17:34
crucial role and it is important that we
01:17:37
uh as a user you know have these uh
01:17:41
intention to store that data and have
01:17:44
that data predicted in any sense now the
01:17:46
data is only getting larger and larger
01:17:49
and we also heard this phrase that data
01:17:52
is the new oil so with the coming in the
01:17:54
coming years the data is exceptionally
01:17:56
going to rise and we need mongodbs to
01:17:59
store this uh huge or huge volumes of
01:18:02
data into our uh databases right so it
01:18:06
is one of the applications of mongodb
01:18:08
and we also have mobile applications and
01:18:10
in order to perform real-time analysis
01:18:12
and we also have uh it is also used in
01:18:15
catalog management content management
01:18:17
and for product management and various
01:18:20
others sectors as well now companies
01:18:23
also like to use noise databases uh
01:18:26
because of its flexible uh design and
01:18:30
the need of you know storing data
01:18:33
without any uh predefined schema makes
01:18:36
it a best nosql database like companies
01:18:41
like eBay Shutterfly New York Times
01:18:44
Verizon and many other big companies use
01:18:47
uh mongodb nowadays and also the one of
01:18:50
the real life application or use cases
01:18:54
the best example you can give is aadhar
01:18:56
card which is India's unique
01:18:58
identification which is uh based on
01:19:00
identifying a person's you know identity
01:19:04
so the other uses mongodb to store this
01:19:06
massive amounts of demographic and
01:19:08
biography biometric data of over more
01:19:11
than 1.5 billion uh you Indian users so
01:19:15
other users mongodb in order to store
01:19:17
the images QR code details you know the
01:19:21
personal details of the user in its
01:19:23
database so these are some of the
01:19:25
applications of well that's a wrap on a
01:19:27
moon stack interview question we hope
01:19:30
you found this video informative and
01:19:32
helpful by now you should have a good
01:19:34
understanding of the different types of
01:19:36
interview questions frequently Asked in
01:19:38
month interviews
01:19:40
and if you are interested in learning
01:19:41
more about web development there are
01:19:44
plenty of resources available online you
01:19:46
can also check out our website for more
01:19:48
information on full stack web
01:19:50
development training courses and
01:19:52
certifications
01:19:53
thank you for watching and we'll see you
01:19:56
next time
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