Welcome to the Hadoop Libraries and Utilities MCQs Page

Dive deep into the fascinating world of Hadoop Libraries and Utilities with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Hadoop Libraries and Utilities, a crucial aspect of Hadoop. In this section, you will encounter a diverse range of MCQs that cover various aspects of Hadoop Libraries and Utilities, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Hadoop.

Check out the MCQs below to embark on an enriching journey through Hadoop Libraries and Utilities. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Hadoop.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Hadoop Libraries and Utilities. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Hadoop Libraries and Utilities MCQs | Page 16 of 18

Explore more Topics under Hadoop

01

Basics of Hadoop

02

MapReduce Basics

03

Hadoop Distributed File System

04

Hadoop IO

05

MapReduce Development and Features

06

Introduction to Pig

07

Hive and HBase

08

ZooKeeper,Sqoop and Cassandra

09

Hadoop Incubators and Hadoop Development Tools

10

Hadoop Frameworks

Q151.

Point out the correct statement.

Predicates are JSP Expression Language (EL) expressions

Predicates are evaluated in order or appearance until one of them evaluates to true and the corresponding transition is taken

The name attribute in the decision node is the name of the decision node

All of the mentioned

Discuss

Answer: (d).All of the mentioned

Q152.

Point out the wrong statement.

The fork and join nodes must be used in pairs

The fork node assumes concurrent execution paths are children of the same fork node

A join node waits until every concurrent execution path of a previous fork node arrives to it

A fork node splits one path of execution into multiple concurrent paths of execution

Discuss

Answer: (b).The fork node assumes concurrent execution paths are children of the same fork node

Q153.

Point out the correct statement.

Large datasets are incentives for users to come to Hadoop

Data management is a common concern to be offered as a service

Understanding the life-time of a feed will allow for implicit validation of the processing rules

All of the mentioned

Discuss

Answer: (d).All of the mentioned

Q154.

Point out the wrong statement.

Falcon promotes Javascript Programming

Falcon does not do any heavy lifting but delegates to tools with in the Hadoop ecosystem

Falcon handles retry logic and late data processing. Records audit, lineage and metrics

All of the mentioned

Discuss

Answer: (a).Falcon promotes Javascript Programming

Q155.

Point out the correct statement.

Bigtop provides an integrated smoke testing framework, alongside a suite of over 10 test files

Bigtop includes tools and a framework for testing at various levels

Bigtop components supports only one Operating Systems

All of the mentioned

Discuss

Answer: (b).Bigtop includes tools and a framework for testing at various levels

Q156.

Point out the wrong statement.

Bigtop-0.5.0 : Builds the 0.5.0 release

Bigtop-trunk-HBase builds the HCatalog packages only

There are also jobs for building virtual machine images

All of the mentioned

Discuss

Answer: (a).Bigtop-0.5.0 : Builds the 0.5.0 release

Q157.

Point out the correct statement.

With Impala, more users, whether using SQL queries or BI applications, can interact with more data

Technical support for Impala is not available via a Cloudera Enterprise subscription

Impala is proprietary tool for Hadoop

None of the mentioned

Discuss

Answer: (a).With Impala, more users, whether using SQL queries or BI applications, can interact with more data

Q158.

Point out the wrong statement.

For Apache Hive users, Impala utilizes the same metadata, ODBC driver, SQL syntax, and user interface as Hive

Impala provides high latency and low concurrency

Impala also scales linearly, even in multi tenant environments

All of the mentioned

Discuss

Answer: (b).Impala provides high latency and low concurrency

Q159.

Point out the correct statement.

A Storm topology consumes streams of data and processes those streams in arbitrarily complex ways

Apache Storm is a free and open source distributed real-time computation system

Storm integrates with the queueing and database technologies you already use

All of the mentioned

Discuss

Answer: (d).All of the mentioned

Q160.

Point out the wrong statement.

Storm is difficult and can be used with only Java

Storm is fast: a benchmark clocked it at over a million tuples processed per second per node

Storm is scalable, fault-tolerant, guarantees your data will be processed

All of the mentioned

Discuss

Answer: (a).Storm is difficult and can be used with only Java

Page 16 of 18

Welcome to the Hadoop Libraries and Utilities MCQs Page

Hadoop Libraries and Utilities MCQs | Page 16 of 18

Explore more Topics under Hadoop

Basics of Hadoop

MapReduce Basics

Hadoop Distributed File System

Hadoop IO

MapReduce Development and Features

Introduction to Pig

Hive and HBase

ZooKeeper,Sqoop and Cassandra

Hadoop Incubators and Hadoop Development Tools

Hadoop Frameworks

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