Practice HDFS (Hadoop Distributed File System) - 1.6.1 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skillsβ€”perfect for learners of all ages.

games

1.6.1 - HDFS (Hadoop Distributed File System)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does HDFS stand for?

πŸ’‘ Hint: The acronym relates to Hadoop.

Question 2

Easy

Why is replication important in HDFS?

πŸ’‘ Hint: Consider what happens if a machine fails.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the primary purpose of HDFS?

  • To store data locally
  • To provide distributed storage for big data
  • To improve data processing speed

πŸ’‘ Hint: Think about what big data needs in terms of storage.

Question 2

True or False: HDFS allows writing data in an append-only fashion.

  • True
  • False

πŸ’‘ Hint: Consider how data is added to files.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are tasked with designing a big data application that processes user clickstream data. Describe how HDFS can be utilized in your application.

πŸ’‘ Hint: Consider the size and frequency of data generation.

Question 2

Discuss the potential limitations of using HDFS compared to traditional database systems, particularly for certain types of applications.

πŸ’‘ Hint: Think about the differences in data access patterns.

Challenge and get performance evaluation