Hadoop: A Comprehensive Guide for Data Science Students

Question 1

Identify the component that is NOT part of the core Hadoop ecosystem:

Accepted Answer

Cassandra

Answer

HDFS

Answer

YARN

Answer

MapReduce

Question 2

Within Hadoop's architecture, which component is responsible for managing resources and scheduling jobs across the cluster?

Accepted Answer

YARN (Yet Another Resource Negotiator)

Answer

HDFS (Hadoop Distributed File System)

Answer

MapReduce

Answer

Hive

Question 3

Which of the following is NOT a core component of the Hadoop ecosystem?

Accepted Answer

Apache Airflow

Answer

Hive

Answer

YARN

Answer

HDFS

Question 4

What is the primary responsibility of the NameNode in HDFS?

Accepted Answer

Managing file system metadata and maintaining file system namespace.

Answer

Storing data blocks across DataNodes.

Answer

Processing data using MapReduce.

Question 5

Which Hadoop component is responsible for distributed data processing using the MapReduce paradigm?

Accepted Answer

MapReduce

Answer

Oozie

Answer

HBase

Answer

ZooKeeper

Question 6

What is a key advantage of utilizing Hadoop for big data processing?

Accepted Answer

Scalability and fault tolerance due to its distributed architecture.

Answer

Ease of use for non-technical users.

Answer

Low cost compared to traditional data processing systems.

Answer

High performance for real-time data analysis.

Question 7

Which programming language is primarily used for developing Hadoop applications and interacting with its APIs?

Accepted Answer

Java

Answer

C++

Answer

R

Answer

Python

Question 8

What is the purpose of the YARN (Yet Another Resource Negotiator) framework in Hadoop?

Accepted Answer

Managing resource allocation and scheduling for Hadoop applications in a flexible and efficient manner.

Answer

Performing data compression and optimization.

Answer

Providing a graphical user interface for Hadoop administration.

Question 9

What is a significant distinction between Hadoop 1 and Hadoop 2?

Accepted Answer

Hadoop 2 introduced YARN for resource management, separating it from the MapReduce framework.

Answer

Hadoop 1 was designed solely for structured data, while Hadoop 2 supports both structured and unstructured data.

Answer

Hadoop 1 had a more user-friendly interface compared to Hadoop 2.

Answer

Hadoop 2 offers significantly faster data processing speeds compared to Hadoop 1.

Question 10

What is the primary function of Apache Hive in the Hadoop ecosystem?

Accepted Answer

Providing a SQL-like interface for querying and manipulating data stored in Hadoop.

Answer

Scheduling and coordinating Hadoop jobs.

Answer

Managing data replication and fault tolerance across Hadoop clusters.

Question 11

Which of the following is an advantage of using Hadoop for data warehousing applications?

Accepted Answer

Cost-effective storage and processing of massive datasets.

Answer

Seamless integration with legacy systems and data sources.

Answer

Real-time data analytics with low latency.

Question 12

Which of the following is **NOT** a component of the Hadoop ecosystem?

Accepted Answer

Spark

Answer

YARN

Answer

MapReduce

Answer

HDFS

Question 13

What is the primary purpose of the MapReduce framework in Hadoop?

Accepted Answer

To process and analyze large datasets in a distributed manner

Answer

To store data in a distributed file system

Answer

To manage resources in a Hadoop cluster

Question 14

Which Hadoop API should you use to interact with HDFS?

Accepted Answer

FileSystem

Answer

Reduce

Answer

Map

Answer

InputFormat

Question 15

What is the primary role of the NameNode in Hadoop?

Accepted Answer

To manage the metadata of the HDFS file system

Answer

To manage the cluster's resources

Answer

To store the actual data blocks

Answer

To schedule MapReduce jobs

Question 16

Explain the difference between a Map task and a Reduce task in MapReduce.

Accepted Answer

Map tasks process individual data records, while Reduce tasks process the intermediate results from the Map tasks.

Answer

Map tasks are executed on the client, while Reduce tasks are executed on the server.

Question 17

What is the main purpose of a JobTracker in Hadoop?

Accepted Answer

To track the progress of MapReduce jobs and manage resource allocation

Answer

To process and analyze large datasets

Answer

To store the metadata of the HDFS file system

Question 18

Hadoop's distributed processing model is known as:

Accepted Answer

MapReduce

Answer

Divide and Conquer

Answer

SpreadProcessing

Question 19

In Hadoop, the NameNode is primarily responsible for managing:

Accepted Answer

Metadata and file system operations

Answer

Map and reduce task execution

Answer

Data block storage

Answer

Client requests

Question 20

Which Hadoop component is responsible for overseeing task scheduling and resource allocation?

Accepted Answer

JobTracker

Answer

Namenode

Answer

TaskTracker

Answer

DataNode

Question 21

HDFS, a component of Hadoop, primarily serves as a:

Accepted Answer

Distributed storage system for large data sets

Answer

Data processing and analysis engine

Answer

Data replication handler

Answer

Data security provider

Question 22

A key advantage of using Hadoop for Big Data processing is its:

Accepted Answer

Scalability and fault tolerance

Answer

Low cost and open-source nature

Answer

Ease of data integration

Answer

Exceptional processing speeds

Question 23

The primary architectural difference between Hadoop 1.x and Hadoop 2.x lies in the introduction of:

Accepted Answer

YARN architecture in Hadoop 2.x

Answer

Support for larger data sets in Hadoop 2.x

Answer

Enhanced security features in Hadoop 2.x

Answer

Faster processing speeds in Hadoop 2.x

Question 24

To transfer data from the local file system to HDFS, the appropriate Hadoop command is:

Accepted Answer

hadoop fs -copyFromLocal

Answer

hadoop fs -upload

Answer

hadoop copy

Question 25

In Hadoop, the command 'set rwx -R' is used to:

Accepted Answer

Recursively set read-write-execute permissions

Answer

Delete files and directories

Answer

Copy files and directories

Answer

List files and directories

Question 26

What is the key advantage of using Hadoop for big data analytics compared to traditional data management systems?

Accepted Answer

Distributed processing and high fault tolerance

Answer

Enhanced data security

Answer

Unlimited storage capacity

Answer

Seamless data integration

Question 27

Which of the following is a fundamental concept in Hadoop's distributed file system (HDFS)?

Accepted Answer

Data blocks

Answer

Hive queries

Answer

MapReduce tasks

Answer

JobScheduler

Question 28

Hadoop utilizes a specific programming model for data processing. Which one is it?

Accepted Answer

MapReduce

Answer

Pig

Answer

Hive

Question 29

ZooKeeper plays a crucial role in a Hadoop cluster. What is its primary function?

Accepted Answer

Coordination and synchronization of cluster components

Answer

Storing and managing data

Answer

Scheduling and managing jobs

Question 30

Within Hadoop's ecosystem, what is the primary purpose of HBase?

Accepted Answer

A NoSQL database optimized for handling large-scale data

Answer

A distributed file system for storing data

Answer

A query language for analyzing data

Answer

A tool for managing Hadoop clusters

Question 31

When using Hadoop, one potential challenge that organizations may encounter is:

Accepted Answer

Complexity and demanding resource requirements

Answer

Support for a narrow range of data types

Answer

Insufficient data security measures

Answer

Limited real-time processing capabilities

Question 32

Hadoop can be effectively integrated with cloud computing platforms. What is the primary benefit of this integration?

Accepted Answer

Elasticity and cost efficiency

Answer

Reduced hardware maintenance responsibilities

Answer

Uncompromising data integrity

Answer

Enhanced data privacy protection

Question 33

Which Hadoop component manages the distributed storage of data?

Accepted Answer

Hadoop Distributed File System (HDFS)

Answer

Hive

Answer

YARN

Answer

MapReduce

Question 34

In Hadoop MapReduce, tasks are divided and processed in which manner?

Accepted Answer

Batch processing (offline)

Answer

Stream processing (continuous)

Answer

Online transaction processing (OLTP)

Answer

Interactive processing (real-time)

Question 35

Which Hadoop tool specializes in data warehousing and querying large datasets using a SQL-like language?

Accepted Answer

Hive

Answer

Pig

Answer

Sqoop

Answer

HBase

Question 36

What is the primary responsibility of the NameNode in Hadoop's HDFS?

Accepted Answer

Managing the metadata of files and directories in the file system

Answer

Providing fault tolerance and data replication

Answer

Scheduling and executing MapReduce jobs

Answer

Storing the actual data blocks

Question 37

Which Hadoop component is responsible for resource management and job scheduling?

Accepted Answer

YARN

Answer

Hive

Answer

HDFS

Answer

MapReduce

Question 38

What is a key advantage of using Hadoop for large-scale data processing?

Accepted Answer

Its scalability and fault tolerance capabilities

Answer

High performance for small datasets

Answer

Ease of data integration

Answer

Low cost of implementation

Question 39

Which element in Hadoop is utilized for data compression?

Accepted Answer

Codec

Answer

Partitioner

Answer

Serialization Framework

Answer

Splitter

Question 40

Which Hadoop tool provides interactive, low-latency SQL querying capabilities for big data analysis?

Accepted Answer

Apache Hive Interactive Query Facility (Hive LLAP)

Answer

Apache Sqoop

Answer

Apache Flume

Answer

Apache Pig

Question 41

What is the main purpose of the Hadoop RPC framework?

Accepted Answer

To facilitate communication between Hadoop components and services

Answer

To schedule and execute MapReduce jobs

Answer

To manage data storage and retrieval

Question 42

What is the primary function of the NameNode in a Hadoop cluster?

Accepted Answer

Manages the file system metadata and directs data access.

Answer

Processes data in parallel across multiple nodes.

Answer

Stores actual data blocks in the cluster.

Question 43

Which of the following is NOT a core component of the Hadoop framework?

Accepted Answer

Spark

Answer

Yarn

Answer

HDFS

Answer

MapReduce

Question 44

What is the primary advantage of using HDFS for storing large datasets?

Accepted Answer

Distributed storage enables scalability and fault tolerance.

Answer

Offers advanced data querying capabilities.

Answer

Provides high-performance real-time data processing.

Question 45

In the MapReduce programming model, what is the primary purpose of the Map phase?

Accepted Answer

Transforming input data into key-value pairs.

Answer

Merging intermediate results from multiple mappers.

Answer

Performing final aggregations on the data.

Answer

Storing processed data in the Hadoop Distributed File System.

Question 46

Which scenario is a suitable application for Hadoop?

Accepted Answer

Analyzing website logs to identify user behavior patterns.

Answer

Processing real-time financial transactions.

Answer

Managing a small database for a local business.

Question 47

What is the main benefit of using YARN (Yet Another Resource Negotiator) in Hadoop?

Accepted Answer

It allows for running various applications on the same Hadoop cluster.

Answer

It provides high-speed data transfer between nodes.

Answer

It ensures data integrity by replicating data across multiple nodes.

Question 48

What is the fundamental difference between a DataNode and a NodeManager in Hadoop?

Accepted Answer

DataNode stores data blocks, while NodeManager manages resources for application execution.

Answer

DataNode is a core Hadoop component, while NodeManager is optional.

Answer

DataNode is responsible for data processing, while NodeManager handles data storage.

Question 49

Why is data replication used in HDFS?

Accepted Answer

To ensure data availability and fault tolerance in case of node failures.

Answer

To accelerate data processing by distributing data across multiple nodes.

Answer

To encrypt data for enhanced security.

Question 50

How does Hadoop handle data processing for extremely large datasets?

Accepted Answer

By dividing the data into smaller chunks and processing them in parallel on multiple nodes.

Answer

By using advanced algorithms to compress the data before processing.

Answer

By storing the data in a centralized database for efficient access.

Question 51

What is a key advantage of using Hadoop over traditional database systems for managing big data?

Accepted Answer

Scalability and cost-effectiveness for storing and processing massive amounts of data.

Answer

High-performance real-time data analysis.

Answer

Advanced data querying capabilities with structured query languages.