Hadoop Quiz - Multiple Choice Questions (MCQ)

Welcome to the Hadoop Quiz! Hadoop is an open-source framework that allows distributed storage and processing of big data. If you're preparing for an exam, or interview, or just looking to refresh your Hadoop knowledge, you're in the right place! Here is a compilation of 25 multiple-choice questions (MCQs) that cover the fundamental concepts of Hadoop.

1. What does HDFS stand for?

a) High-Definition File System

b) Hadoop Distributed File System

c) Hadoop Data Federation Service

d) High-Dynamic File System

Answer:

b) Hadoop Distributed File System

Explanation:

HDFS stands for Hadoop Distributed File System. It is designed to store a large volume of data across multiple machines in a Hadoop cluster.

2. What is the default block size in HDFS?

a) 32 MB

b) 64 MB

c) 128 MB

d) 256 MB

Answer:

c) 128 MB

Explanation:

The default block size in HDFS is 128 MB. This large block size facilitates the storage and processing of big data.

3. Who is the primary developer of Hadoop?

a) Microsoft

b) IBM

c) Apache Software Foundation

d) Google

Answer:

c) Apache Software Foundation

Explanation:

The Apache Software Foundation is the primary developer of Hadoop. The project is open-source and community-driven.

4. Which of the following is not a core component of Hadoop?

a) HDFS

b) MapReduce

c) YARN

d) Spark

Answer:

d) Spark

Explanation:

Spark is not a core component of Hadoop. While it can run on Hadoop and process data from HDFS, it is a separate project.

5. What does YARN stand for?

a) Yet Another Resource Navigator

b) Yet Another Resource Negotiator

c) You Are Really Near

d) Yarn Aims to Reuse Nodes

Answer:

b) Yet Another Resource Negotiator

Explanation:

YARN stands for Yet Another Resource Negotiator. It is the resource management layer for Hadoop, managing and scheduling resources across the cluster.

6. What is the purpose of the JobTracker in Hadoop?

a) To store data

b) To manage resources

c) To schedule and track MapReduce jobs

d) To distribute data blocks

Answer:

c) To schedule and track MapReduce jobs

Explanation:

The JobTracker is responsible for scheduling and keeping track of MapReduce jobs in a Hadoop cluster. It allocates resources and monitors job execution.

7. What is a DataNode in HDFS?

a) A node that stores actual data blocks

b) A node that manages metadata

c) A node responsible for job tracking

d) A node responsible for resource management

Answer:

a) A node that stores actual data blocks

Explanation:

A DataNode in HDFS is responsible for storing the actual data blocks. Data nodes are the workhorses of HDFS, providing storage and data retrieval services.

8. What is the NameNode responsible for in HDFS?

a) Storing actual data blocks

b) Managing metadata and namespace

c) Job scheduling

d) Resource management

Answer:

b) Managing metadata and namespace

Explanation:

The NameNode manages metadata and the namespace of the HDFS. It keeps track of the file system tree and metadata for all the files and directories.

9. What programming model does Hadoop use for processing large data sets?

a) Divide and Rule

b) Master-Slave

c) MapReduce

d) None of the above

Answer:

c) MapReduce

Explanation:

Hadoop uses the MapReduce programming model for distributed data processing. It involves a Mapper phase for filtering and sorting data and a Reducer phase for summarizing the data.

10. What is the primary language for developing Hadoop?

a) Python

b) Java

c) C++

d) Ruby

Answer:

b) Java

Explanation:

Hadoop is primarily written in Java, and the core libraries are Java-based. Although you can write MapReduce programs in other languages, Java is the most commonly used.

11. Which of the following can be used for data serialization in Hadoop?

a) Hive

b) Pig

c) Avro

d) YARN

Answer:

c) Avro

Explanation:

Avro is a framework for data serialization in Hadoop. It provides functionalities for data serialization and deserialization in a compact and efficient binary or JSON format.

12. Which Hadoop ecosystem component is used as a data warehousing tool?

a) Hive

b) Flume

c) ZooKeeper

d) Sqoop

Answer:

a) Hive

Explanation:

Hive is used as a data warehousing tool in the Hadoop ecosystem. It facilitates querying and managing large datasets residing in distributed storage using an SQL-like language called HiveQL.

13. What is the role of ZooKeeper in the Hadoop ecosystem?

a) Data Serialization

b) Stream Processing

c) Cluster Coordination

d) Scripting Platform

Answer:

c) Cluster Coordination

Explanation:

ZooKeeper is used for cluster coordination in Hadoop. It provides distributed synchronization, maintains configuration information, and provides group services.

14. Which tool can be used to import/export data from RDBMS to HDFS?

a) Hive

b) Flume

c) Oozie

d) Sqoop

Answer:

d) Sqoop

Explanation:

Sqoop is a tool designed to transfer data between Hadoop and relational database systems. It facilitates the import and export of data between HDFS and RDBMS.

15. Which of the following is not a function of the NameNode?

a) Store the data block

b) Manage the file system namespace

c) Keep metadata information

d) Handle client requests

Answer:

a) Store the data block

Explanation:

The NameNode does not store actual data blocks. Instead, it manages the file system namespace, keeps metadata information, and handles client requests related to these tasks.

16. What is the replication factor in HDFS?

a) The block size of the data

b) The number of copies of a data block stored in HDFS

c) The number of nodes in a cluster

d) The amount of data that can be stored in a DataNode

Answer:

b) The number of copies of a data block stored in HDFS

Explanation:

The replication factor in HDFS refers to the number of copies of a data block that are stored. By default, this number is set to three, ensuring data reliability and fault tolerance.

17. Which of the following is a scheduler in Hadoop?

a) Sqoop

b) Oozie

c) Flume

d) Hive

Answer:

b) Oozie

Explanation:

Oozie is a scheduler in Hadoop. It's a server-based workflow scheduling system to manage Hadoop jobs.

18. Which daemon is responsible for MapReduce job submission and distribution?

a) DataNode

b) NameNode

c) ResourceManager

d) NodeManager

Answer:

c) ResourceManager

Explanation:

ResourceManager is responsible for the allocation of resources and the management of job submissions in a Hadoop cluster. It plays a pivotal role in the distribution and scheduling of MapReduce tasks.

19. What is a Combiner in Hadoop?

a) A program that combines data from various sources

b) A mini-reducer that operates on the output of the mapper

c) A tool to combine several MapReduce jobs

d) A process to combine NameNode and DataNode functionalities

Answer:

b) A mini-reducer that operates on the output of the mapper

Explanation:

A Combiner in Hadoop acts as a local reducer, operating on the output of the Mapper phase, before the data is passed to the actual Reducer. It helps in reducing the amount of data that needs to be transferred across the network.

20. In which directory Hadoop is installed by default?

a) /usr/local/hadoop

b) /home/hadoop

c) /opt/hadoop

d) /usr/hadoop

Answer:

a) /usr/local/hadoop

Explanation:

By default, Hadoop is installed in the /usr/local/hadoop directory. However, this can be changed based on user preferences or system requirements.

21. Which of the following is responsible for storing large datasets in a distributed environment?

a) MapReduce

b) HBase

c) Hive

d) Pig

Answer:

b) HBase

Explanation:

HBase is a distributed column-oriented database built on top of HDFS (Hadoop Distributed File System). It's designed to store large datasets in a distributed environment, providing real-time read/write access.

22. In a Hadoop cluster, if a DataNode fails:

a) Data will be lost

b) JobTracker will be notified

c) NameNode will re-replicate the data block to other nodes

d) ResourceManager will restart the DataNode

Answer:

c) NameNode will re-replicate the data block to other nodes

Explanation:

In Hadoop's HDFS, data is protected through replication. If a DataNode fails, the NameNode is aware of this and will ensure that the data blocks from the failed node are re-replicated to other available nodes to maintain the system's fault tolerance.

23. Which scripting language is used by Pig?

a) HiveQL

b) Java

c) Pig Latin

d) Python

Answer:

c) Pig Latin

Explanation:

Pig uses a high-level scripting language called "Pig Latin". It's designed for processing and analyzing large datasets in Hadoop.

24. What does "speculative execution" in Hadoop mean?

a) Executing a backup plan if the main execution plan fails

b) Running the same task on multiple nodes to account for node failures

c) Predicting the execution time for tasks

d) Running multiple different tasks on the same node

Answer:

b) Running the same task on multiple nodes to account for node failures

Explanation:

Speculative execution in Hadoop is a mechanism to enhance the reliability and speed of the system. If certain nodes are executing tasks slower than expected, Hadoop might redundantly execute another instance of the same task on another node. The task that finishes first will be accepted.

25. What is the role of a "Shuffler" in a MapReduce job?

a) It connects mappers to the reducers

b) It sorts and groups the keys of the intermediate output from the mapper

c) It combines the output of multiple mappers

d) It distributes data blocks across the DataNodes

Answer:

b) It sorts and groups the keys of the intermediate output from the mapper

Explanation:

In the MapReduce paradigm, after the map phase and before the reduce phase, there is an essential step called the shuffle and sort. The shuffling phase is responsible for sorting and grouping the keys of the intermediate output from the mapper before they are presented to the reducer.