In this blog, we’ll look at the most common Hadoop interview questions and their answers to help you do well in your interview.These interview questions will help you stand out and get ready for jobs in the Big Data world. They cover topics like:

• Hadoop Cluster

• HDFS (Hadoop Distributed File System)

• MapReduce

• Hive

• HBase

What are the basic differences between a relational database and HDFS?

A relational database stores data in tables, with rows and columns, and it’s great for handling small to medium amounts of structured data. It allows quick access, updates, and easy searching using a language called SQL. It’s good for big files like videos, pictures, or logs.is made to store and manage huge amounts of data, even if it's not organized

What is Hadoop and what are its components?

Hadoop is a tool made to help us work with Big Data. When Big Data became too large and complicated for normal computers to handle, Apache Hadoop was created as a solution.

Hadoop has two main parts:

• HDFS (Hadoop Distributed File System): This is the storage part. It breaks big files into smaller blocks and stores them across many computers.

• YARN (Yet Another Resource Negotiator): This is the processing part. It handles tasks like running programs and managing computer resources.

1. What are HDFS and YARN?

HDFS is where all the data is stored in Hadoop. It spreads the data across many machines, and it uses a system called master and slave:

• Name Node: This is the master. It keeps track of where all the pieces of data are and stores information like block size and copies.

• Data Node: These are the slaves. They store the actual data. NameNode tells them what to do.

2. What are the main parts of Hadoop, and how do they help in running a group of computers?

🗂 HDFS Daemons (Storage Helpers)

• NameNode – This is the master. It watches over all the files and remembers where each piece of a file is saved on the different computers.

• DataNode – These are the slaves. They actually store the data blocks. They follow instructions from the Name Node.

⚙️ YARN Daemons (Processing Helpers)

• ResourceManager – This is the master for processing. It decides how jobs (tasks) should be shared and run on different machines.

• NodeManager – These are the workers that run the actual tasks. They talk to the Resource Manager.

🧾 JobHistoryServer

• This daemon keeps track of jobs that are already done. It stores information about past jobs, which is helpful for checking results

3.Network Attached Storage (NAS)

is a type of storage that connects to a network and lets different computers access files from one main place. It can be a special machine or software used to store and share files.

4.The main differences between Hadoop 1 and Hadoop 2

In Hadoop 1, there was only one NameNode, and if it stopped working, the whole system would fail. But in Hadoop 2, there are two NameNodes: one Active and one Passive

5. What are active and passive NameNodes?
In a Hadoop system that uses High Availability (HA), there are two important computers called NameNodes. One is the Active NameNode, which is doing all the work and managing the system.

6. Why does one remove or add nodes in a Hadoop cluster often?
In Hadoop, data is stored across many regular computers called DataNodes. These computers can crash or break easily, so sometimes we need to remove (decommission) the broken ones.

7. What happens when two clients try to access the same file in HDFS?
In HDFS, only one person (client) is allowed to write to a file at a time.

8. How does NameNode handle DataNode failures?
The NameNode keeps checking if DataNodes are working by getting regular signals called heartbeats.

9. What will you do when the NameNode is down?
If the NameNode stops working, we can use a saved file called FsImage, which keeps a copy of important information (metadata).

10. What is a checkpoint?
A checkpoint is like saving your game progress. It takes important files used by the NameNode and puts them into one big file to save time.

11. How is HDFS fault tolerant?
HDFS keeps extra copies of data (usually 3) on different computers

12. Can NameNode and DataNode be normal computers?
DataNodes can be regular computers because they just store data. But the NameNode is very important and needs to remember a lot of things.

13. Why is HDFS better for big files, not many small files?
HDFS works better when storing big files. If there are too many small files.

14. What is a block in HDFS?
A block is the smallest piece of data stored in HDFS.

15. What does the 'jps' command do?
The 'jps' command shows which Hadoop parts are running on your computer.

16. What is Rack Awareness in Hadoop?
Rack Awareness helps the NameNode choose smart places to store data on different computers.

17. What is speculative execution in Hadoop?
Sometimes a task takes too long, so Hadoop runs the same task on another computer.

18. How can I restart the NameNode or all Hadoop parts?
To restart just the NameNode, you can stop and start it using special commands.

19. What makes an HDFS Block and an Input Split not the same?

An HDFS Block is how the data is physically stored on computers.

20. What are the 3 modes in which Hadoop can run?

1. Standalone mode: All parts run on one computer like a normal program.

2. Pseudo-distributed mode: Hadoop runs like it would in real life but still on one machine.

21. What is MapReduce and how do you run it?
MapReduce is a way to handle big data using many computers at the same time.

22. What settings are needed in MapReduce?
To run MapReduce, you need to tell the system where to find the input data and where to store the output.

How to obtain Hadoop certification? 

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Certified Information Systems Security Professional® (CISSP)

AWS Certified Solutions Architect

Google Certified Professional Cloud Architect 

Big Data Certification

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In the rapidly changing IT landscape today, certification is no longer optional but obligatory. It demonstrates you are competent and capable of leading and producing results. Get certified, stay ahead, and be the professional top companies wish to hire.

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