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HDFS Architecture and Programming

Karthik Shyamsunder

The course “HDFS Architecture and Programming” offers a comprehensive understanding of the Hadoop Distributed File System (HDFS) architecture, components, and advanced programming techniques. You will gain practical experience in setting up and configuring Hadoop for Java development, while mastering key concepts such as file and directory CRUD operations, data compression, and serialization. By the end of the course, you will be proficient in using HDFS to handle large-scale data processing, enabling you to build scalable, high-availability solutions.

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The course “HDFS Architecture and Programming” offers a comprehensive understanding of the Hadoop Distributed File System (HDFS) architecture, components, and advanced programming techniques. You will gain practical experience in setting up and configuring Hadoop for Java development, while mastering key concepts such as file and directory CRUD operations, data compression, and serialization. By the end of the course, you will be proficient in using HDFS to handle large-scale data processing, enabling you to build scalable, high-availability solutions.

What sets this course apart is its hands-on approach, where you will work directly with HDFS, writing client programs and applying advanced techniques such as using Sequence and Map Files for specialized data storage. Whether you're new to Hadoop or looking to refine your existing skills, this course equips you with the tools and knowledge to become proficient in HDFS programming, making you a valuable asset in the field of Big Data.

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What's inside

Syllabus

Course Introduction
This course provides a comprehensive understanding of Hadoop Distributed File System (HDFS) architecture and its key components. Students will gain hands-on experience with HDFS, learning how to set up Java programming environments and configure Hadoop. The course covers essential topics such as the HDFS programming model, file and directory CRUD operations, and compression techniques. You will also explore serialization, deserialization, and specialized file structures like Sequence and Map Files. By the end of the course, You will be equipped to leverage HDFS for scalable, highly available big data solutions.
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HDFS Architecture
In this module, we will cover the working model and architecture behind Hadoop Distributed File System (HDFS) 1.0 and the capabilities and deficiencies of HDFS 1.0 architecture.
HDFS Programming Basics
In this module, we will cover HDFS programming concepts, HDFS API, and steps to write an HDFS client program for CRUD (Create, Read, Update and Delete) on files.
HDFS Programming Advanced
In this module, we will cover HDFS advanced programming concepts, such as CRUD on directories, compression, serialization and deserialization, and file-based data structures like sequence files.

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in HDFS Architecture and Programming with these activities:
Review Distributed Systems Concepts
Reinforce your understanding of distributed systems principles, which are fundamental to HDFS architecture and design.
Browse courses on Distributed Systems
Show steps
  • Review key concepts like CAP theorem and consistency models.
  • Study examples of distributed file systems.
Review: Understanding Distributed Systems
Gain a broader understanding of distributed systems principles that underpin HDFS.
View Understanding Distributed Systems, Second... on Amazon
Show steps
  • Read the chapters related to distributed file systems and data management.
  • Reflect on how these concepts apply to HDFS.
Review: Hadoop: The Definitive Guide
Deepen your understanding of HDFS architecture and programming by studying a comprehensive guide.
View Hadoop: The Definitive Guide: Storage and... on Amazon
Show steps
  • Read the chapters related to HDFS architecture and programming.
  • Experiment with the code examples provided in the book.
Four other activities
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Show all seven activities
Practice HDFS CRUD Operations
Solidify your understanding of HDFS programming by practicing CRUD operations on files and directories.
Show steps
  • Write Java programs to create, read, update, and delete files in HDFS.
  • Test your programs with different file sizes and data types.
  • Implement error handling and exception management.
Create a Blog Post on HDFS Compression Techniques
Reinforce your understanding of HDFS compression by writing a blog post explaining different compression techniques and their trade-offs.
Show steps
  • Research different compression codecs supported by HDFS.
  • Write a blog post explaining the benefits and drawbacks of each codec.
  • Include code examples demonstrating how to use each codec.
Build a Simple Data Pipeline with HDFS
Apply your HDFS knowledge by building a data pipeline that ingests, processes, and stores data in HDFS.
Show steps
  • Design a data pipeline that reads data from a source, transforms it, and writes it to HDFS.
  • Implement the pipeline using Java and the HDFS API.
  • Test the pipeline with a large dataset.
Contribute to an Open-Source Hadoop Project
Deepen your understanding of HDFS by contributing to an open-source Hadoop project.
Show steps
  • Identify an open-source Hadoop project that interests you.
  • Explore the project's codebase and documentation.
  • Contribute by fixing bugs, writing documentation, or adding new features.

Career center

Learners who complete HDFS Architecture and Programming will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in HDFS Architecture and Programming.
Cover image
Hadoop: The Definitive Guide
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Comprehensive guide to Hadoop, covering HDFS in detail. It provides a deep dive into the architecture, programming models, and administration of Hadoop. It valuable reference for understanding the underlying principles and practical applications of HDFS. This book is commonly used as a textbook in academic institutions.
Hadoop: The Definitive Guide: Storage and Analysis...
Paperback
$$
Hadoop: The Definitive Guide
Paperback
$$
Hadoop: The Definitive Guide
Kindle Edition
$$
Hadoop: The Definitive Guide
Paperback
$$
Cover image
Understanding Distributed Systems
Save
Provides a high-level overview of distributed systems concepts, which are essential for understanding HDFS. It covers topics such as fault tolerance, consistency, and scalability. It valuable resource for gaining a broader perspective on the challenges and solutions in distributed computing. This book is more valuable as additional reading than it is as a current reference.
Understanding Distributed Systems, Second Edition:...
Paperback
$$
Understanding Distributed Systems: What every...
Paperback
$$
Understanding Distributed Systems, Second Edition:...
Kindle Edition
$$
Understanding Distributed Systems: What every...
Kindle Edition
$$

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Effort
3 weeks of study, 4-5 hours/week
Level
Intermediate
Via
Coursera
Institution
Johns Hopkins University
Instructor
Karthik Shyamsunder
Session
March 17, 2025 - April 14, 2025
Language
English
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