Hadoop Pig MCQ Questions and Answers

Introduction

Apache Pig is a high-level platform for processing large data sets in Hadoop. It provides a simple scripting language, Pig Latin, which allows for complex data transformations and analyses. This quiz covers essential concepts related to Pig, including its operations, data types, and integration with Hadoop.

1. What is Apache Pig primarily used for in Hadoop?

a) Real-time processing

b) Data storage

c) Data analysis

d) Network configuration

Answer:

c) Data analysis

Explanation:

Apache Pig is used for analyzing large datasets in Hadoop. It uses a scripting language called Pig Latin to simplify writing MapReduce tasks.

2. Which language are Pig scripts written in?

a) Java

b) Python

c) Pig Latin

d) SQL

Answer:

c) Pig Latin

Explanation:

Pig scripts are written in Pig Latin, a high-level language for processing large datasets.

3. What is the main advantage of using Pig over traditional MapReduce?

a) Lower learning curve

b) Real-time processing capabilities

c) More efficient data storage

d) Better network security

Answer:

a) Lower learning curve

Explanation:

Pig has a lower learning curve because it abstracts the complexity of MapReduce programming with its simple scripting language.

4. In Pig, which of the following is a complex data type?

a) int

b) float

c) map

d) chararray

Answer:

c) map

Explanation:

In Pig, 'map' is a complex data type, while int, float, and chararray are simple data types.

5. Which operation does the 'GROUP' command perform in Pig?

a) Filters rows in a dataset

b) Sorts data in ascending order

c) Groups data by a specified column

d) Merges two datasets

Answer:

c) Groups data by a specified column

Explanation:

The 'GROUP' command in Pig groups data by one or more fields.

6. What does the 'LOAD' function do in Pig?

a) Loads data from HDFS into a table

b) Exports data from Pig to HDFS

c) Performs data transformation

d) Loads a UDF (User Defined Function)

Answer:

a) Loads data from HDFS into a table

Explanation:

The 'LOAD' function in Pig loads data from HDFS into a table for processing.

7. What is a Bag in Pig Latin?

a) A collection of tuples

b) A type of data storage

c) A scripting function

d) A data processing engine

Answer:

a) A collection of tuples

Explanation:

In Pig Latin, a Bag is a collection of tuples, which can contain duplicate elements.

8. How does Pig interact with Hadoop's MapReduce?

a) It replaces MapReduce

b) It compiles scripts into MapReduce jobs

c) It runs independently of MapReduce

d) It only analyzes MapReduce log files

Answer:

b) It compiles scripts into MapReduce jobs

Explanation:

Pig converts Pig Latin scripts into MapReduce jobs that run on a Hadoop cluster.

9. Which of the following best describes a Tuple in Pig?

a) A key-value pair

b) A single row of fields

c) A fixed-size array

d) A type of Pig script

Answer:

b) A single row of fields

Explanation:

In Pig, a Tuple represents a single row in a table, consisting of an ordered set of fields.

10. What is the function of the 'FOREACH ... GENERATE' statement in Pig?

a) It loops through each row in a dataset

b) It generates random data samples

c) It creates new tables

d) It filters data based on a condition

Answer:

a) It loops through each row in a dataset

Explanation:

The 'FOREACH ... GENERATE' statement in Pig is used to loop through each row in a dataset and create new tuples.

11. What role does the 'FILTER' command play in Pig?

a) It merges two datasets

b) It divides a dataset into groups

c) It selects rows based on a condition

d) It sorts the dataset

Answer:

c) It selects rows based on a condition

Explanation:

The 'FILTER' command in Pig is used to select rows in a dataset that meet a specified condition.

12. What is UDF in the context of Pig?

a) Unique Data Format

b) User Defined Function

c) Unified Data Framework

d) Universal Data File

Answer:

b) User Defined Function

Explanation:

In Pig, UDF stands for User Defined Function. UDFs allow users to write custom functions to extend Pig's capabilities.

13. Which command is used to view the schema of a table in Pig?

a) DESCRIBE

b) DISPLAY

c) SHOW

d) VIEW

Answer:

a) DESCRIBE

Explanation:

The 'DESCRIBE' command in Pig shows the schema of a table, including the names and data types of its fields.

14. How are Pig Latin scripts typically executed?

a) In a web browser

b) On a Pig server

c) In a Hadoop cluster

d) Through a Java application

Answer:

c) In a Hadoop cluster

Explanation:

Pig Latin scripts are executed in a Hadoop cluster, where they are translated into MapReduce jobs.

15. Which data model does Pig primarily use?

a) Graph-based

b) Relational

c) Document-oriented

d) Key-value

Answer:

b) Relational

Explanation:

Pig uses a relational data model, working with data sets similar to tables in a relational database.

16. What is the main difference between the 'STORE' and 'DUMP' commands in Pig?

a) STORE writes data to HDFS, while DUMP displays it on the screen

b) STORE creates a new table, while DUMP deletes one

c) STORE sorts data, while DUMP groups data

d) STORE filters data, while DUMP merges data

Answer:

a) STORE writes data to HDFS, while DUMP displays it on the screen

Explanation:

The 'STORE' command in Pig writes data to HDFS, while 'DUMP' displays the data on the screen.

17. What is Pig's execution environment called?

a) Pig Server

b) Grunt shell

c) Hive terminal

d) Hadoop console

Answer:

b) Grunt shell

Explanation:

The Grunt shell is the interactive command-line interface for running Pig scripts and commands.

18. What is the significance of a 'JOIN' operation in Pig?

a) It divides a dataset into smaller parts

b) It combines two datasets based on a common field

c) It performs mathematical operations on a dataset

d) It filters out specific rows from a dataset

Answer:

b) It combines two datasets based on a common field

Explanation:

The 'JOIN' operation in Pig combines two datasets based on a common field, similar to the SQL JOIN.

19. What does 'COGROUP' do in Pig Latin?

a) It groups multiple tables by a common field

b) It sorts data within a single table

c) It combines data from different Hadoop clusters

d) It creates a complex data structure

Answer:

a) It groups multiple tables by a common field

Explanation:

The 'COGROUP' operation in Pig groups two or more tables by a common field, creating a new table with the grouped data.

20. How can Pig scripts be optimized for performance?

a) By increasing memory allocation

b) By minimizing the use of UDFs

c) By using efficient data types and operations

d) By reducing the size of the input data

Answer:

c) By using efficient data types and operations

Explanation:

Pig scripts can be optimized by using efficient data types, reducing data skew, and choosing operations that minimize data processing and network transfer.

21. What does the 'SPLIT' command do in Pig?

a) It divides a dataset into multiple tables based on conditions

b) It merges multiple datasets into one

c) It sorts the data in ascending order

d) It filters out unwanted data from the dataset

Answer:

a) It divides a dataset into multiple tables based on conditions

Explanation:

The 'SPLIT' command in Pig divides a single dataset into multiple tables based on specific conditions.

22. What is the primary use of the 'UNION' operation in Pig?

a) To perform calculations

b) To combine two or more datasets into one

c) To filter data based on conditions

d) To transform the data type of a field

Answer:

b) To combine two or more datasets into one

Explanation:

The 'UNION' operation in Pig combines two or more datasets into one, concatenating their records.

23. Which of the following is a correct use of the 'LIMIT' operator in Pig?

a) To limit the number of reducers

b) To restrict the number of rows in the output

c) To define the maximum value of a field

d) To specify the minimum memory usage

Answer:

b) To restrict the number of rows in the output

Explanation:

The 'LIMIT' operator in Pig limits the output to a specified number of rows.

24. In Pig, what is the role of the 'DISTINCT' operator?

a) To sort data uniquely

b) To merge similar datasets

c) To remove duplicate rows from a dataset

d) To create a new data type

Answer:

c) To remove duplicate rows from a dataset

Explanation:

The 'DISTINCT' operator in Pig removes duplicate rows from a dataset, ensuring that each row in the output is unique.

25. How does Pig handle null values in its operations?

a) It treats nulls as zeros

b) It automatically removes null values

c) It treats nulls as empty strings

d) It supports operations on null values

Answer:

d) It supports operations on null values

Explanation:

Pig supports operations on null values, treating them differently from other values and providing functions to handle nulls effectively.

Conclusion

Understanding Apache Pig and its operations is crucial for efficient data processing in Hadoop. By mastering Pig Latin and its various commands, users can perform complex data transformations with ease. This quiz aimed to test your knowledge of Pig’s core concepts and operations, reinforcing your understanding of this powerful tool in the Hadoop ecosystem.