This article covers the top Hadoop Interview questions along with the answers. We will discuss Hadoop scenario-based interview questions, Hadoop basic interview questions, as well as experienced Hadoop interview questions for 5 years of experience.  So read on to know all about Hadoop interview questions.

1. What are YARN and HDFS?

HDFS is Hadoop’s storage unit. In a distributed framework, it is responsible for storing various kinds of data as blocks. Master and slave topology is followed.

2. What are the real-time industry applications of Hadoop?

  • Managing traffic on streets
  • Streaming processing

3. What does a “Partitioner MapReduce” do?

A “MapReduce Partitioner” ensures that all of the values of a single key go to the same “reducer,” enabling the map output to be uniformly distributed over the “reducers.”

4. Why does one often delete or add nodes in a Hadoop cluster?

Its use of commodity hardware is one of the most appealing aspects of the Hadoop architecture. In a Hadoop cluster, however, this leads to recurrent “DataNode” crashes.

5. What’s the Hadoop Apache?

As a solution to the “Big Data” concerns, Hadoop appeared. It is part of the Apache project funded by the Foundation for Apache Software.

6. What’s Reducing the Hadoop Map?

The Hadoop MapReduce system is used for processing large data sets in parallel across a Hadoop cluster.

7. How is Hadoop different from other frameworks for parallel computing?

Hadoop is a distributed file system that allows large quantities of information to be stored and managed on a cloud of computers, managing data redundancy.

8. What are the various configuration files for Hadoop?

  • core-site.xml

9. What happens in the HDFS when two clients attempt to access the same file?

HDFS supports unique writes only.

10. Why are we in need of Hadoop?

  • Storage- Since data is so massive, it is very difficult to store such a huge amount of data.
  • Security-Since the data is enormous in size, another challenge is to keep it secure.

11. Explain in MapReduce what shuffling is?

The system’s method of sorting and moving the map outputs to the reducer as inputs are known as the shuffle.

12. What are all the Hadoop modes that can run?

  • Standalone mode
  • Pseudo-distributed mode
  • Completely Distributed Mode

13.What are the differences between regular File System and HDFS?

Data is retained in a single device in the standard FileSystem. In HDFS, data on various systems are distributed and maintained.

14. How does NameNode fix the failures of DataNode?

From each DataNode in the cluster, NameNode receives a Heartbeat regularly, which means that DataNode is working properly.

15. What are Hadoop’s main components?

Hadoop is an open-source software platform for massive datasets for distributed storage and processing. HDFS, MapReduce, and YARN are the Apache Hadoop main components.

16. Explain what cache in the MapReduce System is distributed?

A significant feature supported by the MapReduce system is Distributed Cache. The Distributed Cache is used when you want to share any files across all Hadoop Cluster nodes.

17. Explain the major difference between Input Split and the HDFS block.

A block is the physical representation of information, while the logical representation of information contained in the block is broken. 

18. Why is the fault-tolerant HDFS?

HDFS is fault-tolerant as it replicates knowledge to various DataNodes. By default, three DataNodes can replicate a block of data.

19. When NameNode is down, what would you do?

The NameNode recovery process includes the following steps to set up and run the Hadoop cluster

20. What are the Standalone mode features?

By default, Hadoop runs as a single Java process in a single-node non-distributed mode. The local mode uses the local file system for the operation of input and output.

21. Explain what is in Hadoop JobTracker?

It uses JobTracker in Hadoop to send and monitor MapReduce jobs. On its own JVM operation, the Job Tracker runs

22. What’s Cache Distributed? What are its advantages?

Hadoop distributed cache is a MapReduce system service that caches files when required.  Once a file is cached for a particular job, 

23. What are the two types of metadata that are held by a NameNode server?

  • Disk Metadata 
  • Metadata in RAM 

24. A checkpoint, what is it?

In short, “Checkpointing” is a process in which a FsImage is taken, edited, and compacted into a new FsImage log.

25. What are the Pseudo mode features?

Hadoop can also operate on a single-node in this mode, much like the Standalone mode. The pseudo mode is suitable for both productions and in a testing environment. All the daemons run on the same computer in Pseudo mode.

26. What is the heartbeat in HDFS? Explain

If the Name node or job tracker does not respond to the signal, Heartbeat is referred to as a signal used between a data node and Name node, and between task tracker and job tracker, then some problems with the data node or task tracker are considered

27. In Hadoop, what are the most frequent input formats?

  • Text Input Format
  • Key-Value Input Format
  • Sequence File Input Format

28. What does a Hadoop SequenceFile look like?

SequenceFile is a flat-file used extensively in MapReduce I/O formats that include binary key-value pairs. The map outputs are stored internally as a SequenceFile.

29. What is the difference between high availability and a federation?

There is no restriction to the number of NameNodes in the HDFS Federation and the NameNodes are not connected. There are two NameNodes in HDFS High Availability that are connected. 

30. How is HDFS tolerant of faults?

The NameNode replicates the data to several Data Nodes while data is stored over HDFS. The default factor for replication is 3.

31. What are the Fully-Distributed mode characteristics?

In this mode, all daemons are executed on separate nodes that form a multi-node cluster. Thus for Master and Slave, we make distinct nodes.

32. Explain what combiners are in a MapReduce job, and when do you use a combiner?

Combiners are used to increase the MapReduce Program’s performance. With the aid of combiners that need to be passed through to the reducers, the volume of data can be decreased.

33. In Hadoop, what is the position of a JobTracker?

The primary role of a JobTracker is resource management, resource availability monitoring, and work life cycle management.

34. How are “reducers” communicating with each other?

The programming model “MapReduce” does not allow “reducers” to interact with each other. “Reducers” are running isolated.

35. Could NameNode and DataNode be hardware for commodities?

The clever answer to this question would be as it stores data and is needed in a large number, DataNodes are commodity hardware such as personal computers and laptops.

36. Hadoop 2 and Hadoop 3 to compare?

  • The minimum supported version of Java for Hadoop 2 is Java 7, while Java 8 is for Hadoop 3.
  • Hadoop 2, replication fault tolerance management. Although. Hadoop 3 manages it with coding by Erasure.

37. When a data node fails, what happens?

  • Failure found by Jobtracker and namenode
  • All activities on the failed node are re-scheduled
  • Namenode replicates the data of the user to another node.

38. What is the use of a Hadoop RecordReader?

Although a slice of work is described by InputSplit, it does not explain how to access it. This is where the RecordReader class enters the image, which takes the byte-oriented information from its source.

39. In HDFS, how does rack perception work?

HDFS Rack Awareness refers to various Data Nodes’ information and how it is spread through a Hadoop Cluster’s racks.

40. For applications that have massive data sets, why are we using HDFS and not when there are a lot of small files?

Compared to a small volume of data spread through several files, HDFS is more suitable for large numbers of data sets in a single file.

41. In Hadoop, what is Safe mode?

In Apache Hadoop, Safemode is the NameNode maintenance condition. HDFS clusters are read-only during Safemode and do not repeat or erase blocks.

42. Explain what Speculative Compliance is?

A certain number of duplicate tasks are launched during Speculative Execution in Hadoop. Multiple copies of the same map or reduction task may be performed using Speculative Execution on a separate slave node.

43. What firms use Hadoop?

Yahoo; Facebook; Amazon; Netflix; Adobe; eBay; Spotify; Twitter; and Adobe.

44. How do you reboot NameNode and all the Hadoop daemons?

You can use ./sbin / to interrupt the NameNode command, and then use ./sbin/ to resume the NameNode command.

45. What command will enable you to find the block status and the health of the FileSystem?

hdfs fsck <path> -files -blocks

hdfs fsck / -files –blocks –locations > dfs-fsck.log

46.What does the command ‘jps’ do?

The command ‘jps’ allows us to check whether or not the Hadoop daemons are going.

47. What is the issue with small Hadoop files?

For limited data, Hadoop is not suited. The ability to support random reading of small files is missing in Hadoop HDFS. The small HDFS file is smaller than the size of the HDFS block.

48. Explain what a mapper’s basic parameters are?

  • Text and LongWritable
  • IntWritable and Text

49. What happens if you store too many small files on HDFS in a cluster?

A lot of metadata files are created by storing many small files on HDFS. It is a challenge to store these metadata in the RAM as each file, block, or directory requires 150 bytes of metadata. 

50. In Hadoop, how do you describe ‘Rack Awareness’?

Based on rack concepts, Rack Knowledge is the algorithm in which the “NameNode” defines how blocks and their replicas are positioned to reduce network traffic between “Data Nodes” within the same rack.


We hope these Hadoop Interview Questions and Answers help you understand the subject thoroughly and crack a Haddop interview successfully! 

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