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BigData-Hadoop

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

What are the main components of Hadoop Ecosystem?

a)

MapReduce, HDFS, YARN

b)

MLlib, GraphX

c)

Gelly, Table, CEP

d)

None of the mentioned

2.

________________is a resource management platform responsible for managing compute resources in the cluster and using them in order to schedule users and applications.

a)

Hadoop Common

b)

Hadoop Distributed File System (HDFS)

c)

Hadoop YARN

d)

Hadoop MapReduce

3.

Which of the following tool is designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.

a)

Apache Sqoop

b)

Pig

c)

Mahout

d)

Flume

4.

Consider the following statements:


Statement 1: The Job Tracker is hosted inside the master and it receives the job execution request from the client.


Statement 2: Task tracker is the MapReduce component on the slave machine as there are multiple slave machines.

a)

Only statement 1 is true

b)

Only statement 2 is true

c)

Both statements are true

d)

Both statements are false

5.

_____________is the slave/worker node and holds the user data in the form of Data Blocks.

a)

NameNode

b)

DataNode

c)

Data block

d)

Replication

6.

The number of maps in MapReduce is usually driven by the total size of________________

a)

Inputs

b)

Outputs

c)

Tasks

d)

None of the mentioned

7.

_______________function processes a key/value pair to generate a set of intermediate key/value pairs.

a)

Map

b)

Reduce

c)

Both Map and Reduce

d)

None of the mentioned

8.

True or False ?


The main duties of task tracker are to break down the receive job that is big computations in small parts, allocate the partial computations that is tasks to the slave nodes monitoring the progress and report of task execution from the slave.

a)

True

b)

False

9.

Point out the correct statement in context of YARN:

a)

YARN extends the power of Hadoop to incumbent and new technologies found within the data center

b)

YARN is highly scalable

c)

YARN enhances a Hadoop compute cluster in many ways

d)

All of the mentioned

10.

Apache Hadoop YARN stands for:

a)

Yet Another Reserve Negotiator

b)

Yet Another Resource Network

c)

Yet Another Resource Negotiator

d)

Yet Another Resource Manager

11.

For which of the following operations is NO communication with the NameNode required?

a)

A client writing a file to HDFS.

b)

A client requesting the filename of a given block of data.

c)

A client reading a block of data from the cluster.

d)

A client reading a file from the cluster.

12.

Which of the following components reside on a NameNode?

a)

Filenames, blocks and checksums

b)

Blocks and heartbeat messages

c)

Filenames, block locations

d)

Blocks and block locations

13.

Which of the following statements are true about key/value pairs in Hadoop?


a)

A map() function can emit up to a maximum number of key/value pairs (depending on the Hadoop environment).

b)

A map() function can emit anything between zero and an unlimited number of key/value pairs.

c)

A reduce() function can iterate over key/value pairs multiple times.

d)

A call to reduce() is guaranteed to receive key/value pairs from only one key.

14.

A ________ serves as the master and there is only one NameNode per cluster.

a)

Data Node

b)

NameNode

c)

Data block

d)

Replication

15.

HDFS works in a __________ fashion

a)

master-worker

b)

master-slave

c)

worker/slave

d)

worker/master

16.

________ NameNode is used when the Primary NameNode goes down.

a)

Rack

b)

Data

c)

Secondary

d)

Name

17.

The need for data replication can arise in various scenarios like ____________

a)

Replication Factor is changed

b)

DataNode goes down

c)

Data Blocks get corrupted

d)

All of the mentioned

18.

HDFS is implemented in _____________ programming language.

a)

Scala

b)

C++

c)

Java

d)

C

19.

________ is a programming model designed for processing large volumes of data in parallel by dividing the work into a set of independent tasks.

a)

Hive

b)

MapReduce

c)

Pig

d)

Lucene

20.

Output of the mapper is first written on the local disk for sorting and _________ process.

a)

shuffling

b)

secondary sorting

c)

forking

d)

reducing