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Hadoop Mock Interview QA

The document is a mock interview guide for Hadoop developers, covering essential questions and answers about Hadoop's framework, core components, and functionalities. Key topics include the roles of NameNode and DataNode, differences between Hadoop versions, YARN, and optimization techniques for MapReduce jobs. It also discusses fault tolerance, execution modes, and various ecosystem components.

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aakashsapkal122
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11 views2 pages

Hadoop Mock Interview QA

The document is a mock interview guide for Hadoop developers, covering essential questions and answers about Hadoop's framework, core components, and functionalities. Key topics include the roles of NameNode and DataNode, differences between Hadoop versions, YARN, and optimization techniques for MapReduce jobs. It also discusses fault tolerance, execution modes, and various ecosystem components.

Uploaded by

aakashsapkal122
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as PDF, TXT or read online on Scribd
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Hadoop Developer Mock Interview - Q&A

1. What is Hadoop?

Answer: Hadoop is an open-source framework for storing and processing big data in a distributed

manner using commodity hardware. It includes HDFS for storage and MapReduce for processing.

2. What are the core components of Hadoop?

Answer: HDFS, MapReduce, YARN, and Hadoop Common.

3. What is the role of NameNode and DataNode?

Answer: NameNode manages metadata, and DataNode stores the actual data blocks.

4. What is MapReduce?

Answer: A programming model for processing large data sets with a map function and a reduce

function.

5. Difference between Hadoop 1.x and 2.x?

Answer: Hadoop 1.x uses JobTracker for resource management; Hadoop 2.x uses YARN, which

separates resource management and job scheduling.

6. What is YARN?

Answer: YARN stands for Yet Another Resource Negotiator. It manages resources and scheduling

of jobs across the cluster.

7. What is a Combiner?

Answer: A Combiner is a mini-reducer used to reduce the amount of data transferred to the

reducers.

8. What is speculative execution?

Answer: A mechanism to re-run slow tasks on other nodes to reduce overall job execution time.

9. What is the default block size in HDFS?

Answer: 128MB (can be configured).


10. Name some Hadoop ecosystem components.

Answer: Hive, Pig, HBase, Sqoop, Flume, Oozie, Zookeeper, etc.

11. How does Hadoop provide fault tolerance?

Answer: By replicating data blocks across multiple DataNodes. If a node fails, data can be retrieved

from replicas.

12. What is a Partitioner?

Answer: A component that decides which reducer will receive a particular intermediate key-value

pair.

13. What are the different modes Hadoop can run in?

Answer: Standalone mode, Pseudo-distributed mode, Fully distributed mode.

14. What is the role of ApplicationMaster?

Answer: Manages the execution of a single application in YARN, including resource negotiation and

task monitoring.

15. How do you optimize a MapReduce job?

Answer: Use combiners, tune number of reducers, avoid small files, and proper memory

configuration.

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