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Hadoop Ecosystem Fundamentals: MapReduce, Pig, Hive Basics

Total questions: 40

Worksheet time: 20mins

Name
Class
Date
1.

MapReduce focuses on ________, while Hive focuses on ________.

a)

Real-time processing; Batch analytics

b)

Batch processing; Data warehousing and querying

c)

Data visualization; ETL operations

d)

Data streaming; File storage

2.

Which Hadoop component provides a high-level abstraction over MapReduce jobs?

a)

Pig and Hive

b)

YARN and HDFS

c)

HBase and Sqoop

d)

Oozie and Flume

3.

Pig Latin scripts are internally converted into:

a)

HiveQL queries

b)

MapReduce jobs

c)

SQL queries

d)

NoSQL tables

4.

MapReduce handles data at the ______ level, while Hive manages it at the ______ level.

a)

Record; Table

b)

File; Block

c)

Job; Cluster

d)

Node; Directory

5.

Which one is declarative in nature?

a)

MapReduce

b)

Pig Latin

c)

HiveQL

d)

Both B and C

6.

Pig is mainly designed for _______, whereas MapReduce is for _______.

a)

Simple queries; complex operations

b)

ETL operations; custom logic

c)

OLTP systems; OLAP systems

d)

Data transfer; resource management

7.

In Hive, every query is internally executed as:

a)

SQL job

b)

MapReduce job

c)

Spark job

d)

Shell command

8.

Which of the following allows schema-on-read processing?

a)

MapReduce only

b)

Hive and Pig

c)

HBase

d)

YARN

9.

The shuffle and sort process in MapReduce is conceptually similar to which phase in Hive?

a)

Query optimization

b)

Data grouping and aggregation

c)

File loading

d)

Schema definition

10.

MapReduce’s Combiner function is similar to which operation in Hive?

a)

GROUP BY

b)

ORDER BY

c)

DISTINCT

d)

JOIN

11.

Which component of Hadoop handles job scheduling and resource management?

a)

JobTracker

b)

YARN

c)

Hive Driver

d)

Pig Compiler

12.

Hive and Pig both rely on which Hadoop component for execution?

a)

HDFS

b)

YARN

c)

MapReduce

d)

All of the above

13.

In MapReduce, data is divided into:

a)

Tables

b)

Input Splits

c)

Column Families

d)

Records

14.

In HBase, data is stored in:

a)

Rows and Columns

b)

Key-Value pairs

c)

Column Families and Qualifiers

d)

All of the above

15.

Which tool among the following is a NoSQL database?

a)

Hive

b)

Pig

c)

HBase

d)

MapReduce

16.

The ResourceManager in YARN is analogous to which component in classic MapReduce?

a)

NameNode

b)

JobTracker

c)

TaskTracker

d)

DataNode

17.

Hive Metastore stores:

a)

Data files

b)

Table schemas and metadata

c)

HDFS block information

d)

Reducer output

18.

Pig and Hive differ mainly in that:

a)

Pig is procedural; Hive is declarative

b)

Pig is declarative; Hive is procedural

c)

Pig uses SQL; Hive uses JSON

d)

Pig runs on Spark; Hive runs on HDFS

19.

MapReduce processes are written in:

a)

SQL

b)

Java or Python

c)

Pig Latin

d)

Shell scripts

20.

Hive and Pig were both developed to:

a)

Simplify MapReduce programming

b)

Replace HDFS

c)

Manage data nodes

d)

Monitor Hadoop clusters

21.

In MapReduce, Mapper output is stored:

a)

Temporarily on local disk

b)

Directly in HDFS

c)

In Hive tables

d)

In the Pig Engine

22.

The Reducer stage in MapReduce is equivalent to which SQL operation?

a)

SELECT

b)

GROUP BY / AGGREGATE

c)

UPDATE

d)

INSERT

23.

In Pig, the "FOREACH" statement is similar to which MapReduce component?

a)

Mapper

b)

Reducer

c)

Combiner

d)

JobTracker

24.

In Hive, "INSERT OVERWRITE" corresponds to which MapReduce phase?

a)

Shuffle and Sort

b)

Final Output Writing

c)

Map Phase

d)

Split Phase

25.

HBase differs from Hive in that HBase provides:

a)

Real-time read/write access

b)

Batch SQL querying

c)

Text analytics

d)

Job scheduling

26.

MapReduce is process-oriented, while Hive and Pig are:

a)

Data-oriented

b)

Cluster-oriented

c)

Job-oriented

d)

Schema-oriented

27.

Which tool is best suited for ETL operations?

a)

Hive

b)

Pig

c)

HBase

d)

MapReduce

28.

Hive’s query execution engine interacts with:

a)

YARN

b)

HDFS

c)

Metastore

d)

None of the above

29.

In a typical Hadoop ecosystem, MapReduce handles which responsibility?

a)

Processing

b)

Storage

c)

Query execution

d)

Data modeling

30.

Pig Latin is easier to use than MapReduce primarily because:

a)

It has GUI

b)

It uses fewer lines of code

c)

It is compiled in Java

d)

It stores results in JSON

31.

HBase is typically used when:

a)

Data is structured and static

b)

Fast, random read/write operations are needed

c)

Data is small

d)

SQL queries are required

32.

Hive is most suitable for:

a)

Online Transaction Processing (OLTP)

b)

Online Analytical Processing (OLAP)

c)

Real-time streaming

d)

File transfers

33.

MapReduce and YARN together form the:

a)

Hadoop Execution Framework

b)

Hadoop Storage Layer

c)

Hadoop Management System

d)

HBase Engine

34.

Pig’s DUMP command corresponds to which step in MapReduce?

a)

OutputFormat write

b)

Map phase

c)

Combiner

d)

Job initialization

35.

In Hive, CREATE TABLE corresponds to which MapReduce function?

a)

InputFormat definition

b)

Reducer aggregation

c)

Shuffle setup

d)

Job scheduling

36.

Which of the following is not directly dependent on MapReduce?

a)

Hive

b)

Pig

c)

HBase

d)

None of the above

37.

Which component can connect Hive to HBase?

a)

Hive-HBase Handler

b)

Hive Metastore

c)

Pig Engine

d)

JobTracker

38.

MapReduce can fail due to which of the following?

a)

Node failure

b)

Network bottlenecks

c)

Data corruption

d)

All of the above

39.

Which tool is mainly procedural and used for data transformation?

a)

Hive

b)

Pig

c)

HBase

d)

YARN

40.

When comparing MapReduce and Hive, Hive is:

a)

Faster for large-scale iterative jobs

b)

Slower but easier to use

c)

Real-time oriented

d)

Built for stream processing

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