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MAP REDUCE

Total questions: 18

Worksheet time: 18mins

Name
Class
Date
1.

MapReduce programming model is meant to process small quantities of data.

a)

True

b)

False

2.

MapReduce programming model was introduced by _________.

a)

Microsoft

b)

Google

c)

Manjrasoft

d)

Wipro

3.

MapReduce programming model developed by Google in _________ language.

a)

Python

b)

Ruby

c)

Java

d)

.NET

4.

The computation logic is expressed by two functions. Identify them.

a)

Map

b)

Shuffle

c)

Aggregate

d)

Reduce

5.

Identify the component that handles the "data transfer and data management" in the MapReduce model.

a)

Google File System (GFS)

b)

File System (FS)

c)

Key -> Value Pair

d)

Map & Reduce functions

6.

Output of ___________ is input to ___________ in the mapreduce programming model.

a)

Reduce, Map

b)

Map, Reduce

c)

Map, Partitioner

d)

Reduce, Aggregator

7.

According to Google implementation, there are 2 types of processes. Which are they?

a)

Monitor

b)

Master

c)

Worker

d)

Leader

8.

Identify the correct statement with respect to the master process.

a)

Controls the execution of map task

b)

Controls the execution of reduce task

c)

Reorganizes the intermediate output from the map.

d)

Hosts the execution of map and reduce task.

9.

The worker process hosts the execution of the map and reduce tasks.

a)

True

b)

False

10.
A ________ node acts as the Slave and is responsible for executing a Task assigned to it by the JobTracker.
a)
MapReduce
b)
Mapper
c)
TaskTracker
d)
JobTracker
11.
Point out the correct statement.
a)
MapReduce tries to place the data and the compute as close as possible
b)
Map Task in MapReduce is performed using the Mapper() function
c)
Reduce Task in MapReduce is performed using the Map() function
d)
All of the mentioned
12.
___________ part of the MapReduce is responsible for processing one or more chunks of data and producing the output results.
a)
Maptask
b)
Mapper
c)
Task execution
d)
All of the mentioned
13.
_________ function is responsible for consolidating the results produced by each of the Map() functions/tasks.
a)
Reduce
b)
Map
c)
Reducer
d)
All of the mentioned
14.
Although the Hadoop framework is implemented in Java, MapReduce applications need not be written in ____________
a)
Java
b)
C
c)
C#
d)
None of the mentioned
15.
__________ maps input key/value pairs to a set of intermediate key/value pairs.
a)
Mapper
b)
Reducer
c)
Both Mapper and Reducer
d)
None of the mentioned
16.
The number of maps is usually driven by the total size of ____________
a)
inputs
b)
outputs
c)
tasks
d)
None of the mentioned
17.
Running a ___________ program involves running mapping tasks on many or all of the nodes in our cluster.
a)
MapReduce
b)
Map
c)
Reducer
d)
All of the mentioned
18.
Hadoop I/O Hadoop comes with a set of ________ for data I/O.
a)
methods
b)
commands
c)
classes
d)
none of the mentioned