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MCQs on Big Data Analytics

Total questions: 25

Worksheet time: 13mins

Name
Class
Date
1.

The main goal of MapReduce is to:

a)

Scale vertically by upgrading hardware

b)

Simplify distributed data processing

c)

Replace relational databases

d)

Provide encryption for data

2.

The "Word Count" program in MapReduce produces:

a)

Total number of characters

b)

List of words and their occurrence counts

c)

Sentence length analysis

d)

Document similarity scores

3.

Which company originally described the MapReduce paradigm?

a)

Yahoo

b)

IBM

c)

Google

d)

Facebook

4.

Hadoop's implementation of MapReduce is primarily written in:

a)

Python

b)

Java

c)

Scala

d)

C++

5.

Which distributed filesystem is used by Hadoop?

a)

FAT32

b)

NTFS

c)

HDFS

d)

ZFS

6.

Which of the following is a user component of MapReduce?

a)

Input Splitter

b)

Master

c)

Mapper

d)

Output Committer

7.

The default input split size in Hadoop MapReduce is:

a)

16 MB

b)

32 MB

c)

64 MB

d)

128 MB

8.

The reducer ensures that:

a)

All outputs are encrypted

b)

Keys are distributed randomly

c)

All values with the same key go to the same reducer

d)

Each key is assigned to multiple reducers

9.

Which component reduces the output of each mapper before sending it to reducers?

a)

Combiner

b)

Input Splitter

c)

Partitioner

d)

Master

10.

The default partitioner uses:

a)

Random assignment

b)

Round-robin distribution

c)

Key.hashCode() % number_of_reducers

d)

Key length

11.

The input splitter divides data into:

a)

Random chunks

b)

64MB logical boundaries by default

c)

1MB files

d)

Variable-sized packets

12.

Mapper input and output are represented as:

a)

XML documents

b)

pairs

c)

JSON objects

d)

Tables

13.

In the Word Count example, the Mapper emits:

a)

b)

c)

d)

14.

Reducer's main role is to:

a)

Filter invalid keys

b)

Collect and aggregate values by key

c)

Compress the outputs

d)

Distribute tasks

15.

The output committer is responsible for:

a)

Scheduling tasks

b)

Splitting inputs

c)

Writing reducer results to files

d)

Monitoring tasks

16.

If a mapper fails during execution, the framework:

a)

Stops the entire job

b)

Restarts the job from the beginning

c)

Kills the task and re-runs it with the same input

d)

Ignores the failed task

17.

The master schedules computations:

a)

Far from the data

b)

Randomly across nodes

c)

As close to the data as possible

d)

Based on user preference

18.

Which tool allows workflows as Directed Acyclic Graphs (DAGs)?

a)

Hive

b)

Oozie

c)

Pig

d)

Sqoop

19.

In matrix-vector multiplication using MapReduce, the mapper emits:

a)

b)

c)

d)

20.

Before running a MapReduce job, if the output folder already exists in HDFS, you must:

a)

Rename it

b)

Overwrite it directly

c)

Remove it using hdfs dfs -rm -r

d)

Move it to another directory

21.

In the runtime coordination phase, which component logs job details like ID and submission time?

a)

NodeManager

b)

ResourceManager

c)

JobHistoryServer

d)

ApplicationMaster

22.

During task execution, shuffle and sort ensure that:

a)

Keys are grouped together before reducing

b)

Data is compressed

c)

All outputs are encrypted

d)

Inputs are concatenated

23.

NodeManagers send ______ to ResourceManager to confirm task status.

a)

Requests

b)

Heartbeats

c)

Counters

d)

Snapshots

24.

In Hadoop + Spark integration, MNIST dataset is stored in HDFS in which format?

a)

CSV

b)

NPZ

c)

TXT

d)

JSON

25.

In the MNIST example, the PySpark ML pipeline trains which model?

a)

Decision Tree

b)

Logistic Regression

c)

Random Forest

d)

K-Means