What is Hadoop - Practice Questions & Exercises

Challenge - 5 Problems

🧠 Conceptual

intermediate

What is the primary purpose of Hadoop?

Hadoop is a popular tool in data science. What is its main use?

A To write small scripts for data cleaning on a single computer.

B To store and process large data sets across many computers.

C To create visual charts and graphs from data.

D To build websites and web applications.

💡 Hint

Think about handling very big data that one computer cannot manage alone.

Hadoop helps store and process huge amounts of data by spreading it over many computers working together.

🧠 Conceptual

intermediate

Which component of Hadoop manages data storage?

Hadoop has parts that handle storage and parts that handle processing. Which part stores the data?

A MapReduce

B YARN

C HDFS (Hadoop Distributed File System)

D Hive

💡 Hint

Think about the file system that spreads data across computers.

HDFS is the storage system in Hadoop that splits and saves data across many machines.

🧠 Conceptual

advanced

What role does YARN play in Hadoop?

Hadoop uses YARN as one of its components. What is YARN's main job?

A It manages and schedules computing resources for processing tasks.

B It stores data across the cluster.

C It creates visual reports from data.

D It cleans and formats raw data.

💡 Hint

Think about how Hadoop decides which computer does what work.

YARN manages resources and schedules tasks so Hadoop can process data efficiently across many machines.

🧠 Conceptual

advanced

Which statement best describes MapReduce in Hadoop?

MapReduce is a key part of Hadoop. What does it do?

A It processes data by dividing tasks into map and reduce steps.

B It manages user access and security.

C It visualizes data trends and patterns.

D It stores data in a distributed way.

💡 Hint

Think about how Hadoop breaks down big jobs into smaller pieces to process.

MapReduce splits data processing into two steps: mapping (filtering and sorting) and reducing (summarizing results).

🧠 Conceptual

expert

Why is Hadoop considered fault-tolerant?

Hadoop is known for fault tolerance. What feature makes it fault-tolerant?

A It requires manual backup of data by users.

B It uses a single powerful computer to avoid failures.

C It deletes data after processing to save space.

D It stores multiple copies of data across different machines.

💡 Hint

Think about how Hadoop protects data if one machine breaks.

Hadoop keeps several copies of data on different machines so if one fails, data is not lost.