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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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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Provides hands-on experience with HDFS, allowing learners to write client programs and apply advanced techniques for specialized data storage, which is essential for big data processing
Covers essential topics such as the HDFS programming model, file and directory CRUD operations, and compression techniques, which are fundamental for managing data within HDFS
Explores serialization, deserialization, and specialized file structures like Sequence and Map Files, which are useful for optimizing data storage and retrieval in big data applications
Teaches how to set up Java programming environments and configure Hadoop, which is a practical skill for developing HDFS-based applications
Focuses on HDFS 1.0 architecture, so learners should be aware that there are newer versions of HDFS with potentially different features and capabilities
Requires learners to set up and configure Hadoop for Java development, which may require specific software versions and configurations that are not explicitly detailed

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Reviews summary

Hdfs architecture and programming overview

According to learners, this course provides a solid foundation in HDFS architecture and programming fundamentals. Students appreciate the hands-on approach, particularly the practice with the HDFS Java API and CRUD operations. The inclusion of advanced topics like serialization and sequence files is seen as valuable. However, a key concern is the course's apparent focus on HDFS 1.0 architecture, which some find outdated in the current Big Data landscape. While it covers core HDFS concepts well, learners note the limited scope, wishing for coverage of other Hadoop components or newer technologies.
Covers advanced topics like serialization.
"Interested in the modules on serialization and sequence files."
"Glad they included compression techniques."
"The advanced programming module seems valuable."
Provides a solid grounding in HDFS basics.
"Seems like a good course for understanding the core architecture."
"Covers the fundamental CRUD operations."
"Good introduction to how HDFS works at a basic level."
Offers practical Java programming experience.
"Looking forward to the hands-on programming parts."
"The focus on writing client programs in Java seems very practical."
"Learning the HDFS API directly is a key reason I took this."
Doesn't cover the broader Hadoop ecosystem.
"Wish it covered YARN or other related Hadoop components."
"It's purely focused on HDFS, not the whole Big Data picture."
"Doesn't seem to go into admin or performance tuning."
Content seems based on older HDFS version.
"Seems heavily focused on HDFS 1.0, which feels a bit outdated now."
"Wish they covered newer HDFS versions or alternatives."
"The architecture module specifically mentions HDFS 1.0 in the description."

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
Expand to see all activities and additional details
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:
Hadoop Developer
A Hadoop developer builds and maintains applications that run on the Hadoop ecosystem. This includes writing MapReduce jobs, developing custom data processing pipelines, and working with various Hadoop components such as HDFS and YARN. This course on HDFS architecture and programming directly impacts one's ability to succeed as a Hadoop developer. The course focuses on HDFS programming, including setup, configuration, file operations, compression, and serialization. This will allow the Hadoop Developer to build scalable and high-availability solutions.
See salaries and explore the career path for Hadoop Developer
Data Engineer
The data engineer is responsible for designing, building, and maintaining data pipelines and infrastructure that support data storage, processing, and analysis. A data engineer works with large datasets and distributed systems. This course on HDFS architecture and programming helps build a foundation in the underlying technologies used in modern data engineering. The course provides hands-on experience with HDFS, covering setup, configuration, and programming, allowing students to create and manipulate files. Exposure to concepts such as compression, serialization, and specialized file structures makes you a more valuable candidate as Data Engineer.
See salaries and explore the career path for Data Engineer
Big Data Architect
A big data architect designs and oversees the implementation of big data solutions for organizations. They are responsible for selecting technologies, designing the overall architecture, and ensuring that the system meets the organization's needs for scalability, performance, and reliability. This course on HDFS architecture and programming helps one to understand the fundamental building blocks of big data systems. The course's comprehensive coverage of HDFS architecture, components, and advanced programming techniques provides a solid base for designing scalable and robust big data solutions. The course also includes working with sequence and map files.
See salaries and explore the career path for Big Data Architect
ETL Developer
An extract, transform, load (ETL) developer designs, develops, and maintains processes for extracting data from various sources, transforming it into a consistent format, and loading it into a data warehouse or other target system. This course on HDFS architecture and programming helps ETL Developer in managing and processing large volumes of data. The course's focus on setting up and configuring Hadoop, along with its coverage of file operations and compression, is relevant to ETL processes. Experience using sequence and map files might be helpful for ETL Developer.
See salaries and explore the career path for ETL Developer
Data Warehouse Architect
The data warehouse architect designs and implements data warehouse solutions for organizations. This includes designing the data model, selecting the appropriate technologies, and ensuring that the data warehouse meets the organization's needs. This course on HDFS architecture and programming can help Data Warehouse Architect in building scalable and robust data warehouse solutions. The course's comprehensive coverage of HDFS architecture, components, and programming techniques provides a foundation for designing systems. One should note the course also covers sequence and map files.
See salaries and explore the career path for Data Warehouse Architect
DevOps Engineer
The DevOps engineer automates and streamlines the software development and deployment process. This involves tasks such as continuous integration, continuous delivery, and infrastructure automation. The course on HDFS Architecture and Programming will be useful for DevOps Engineer working with big data environments. The course's focus on HDFS, including setup, configuration, and programming helps DevOps Engineer in automating deployment and management of data infrastructure.
See salaries and explore the career path for DevOps Engineer
Cloud Engineer
The cloud engineer is responsible for designing, building, and maintaining cloud infrastructure and services. This includes tasks such as cloud deployment, automation, monitoring, and security. This course on HDFS architecture and programming will be useful for Cloud Engineer working with big data in the cloud. The course's focus on HDFS helps Cloud Engineer in deploying and managing big data solutions in cloud environments. The course also covers sequence and map files.
See salaries and explore the career path for Cloud Engineer
Database Administrator
A database administrator (DBA) manages and maintains databases, ensuring their availability, performance, and security. This may involve tasks such as database design, backup and recovery, performance tuning, and security administration. This course on HDFS architecture and programming provides a complementary skill set for database administrators. The skills to handle large-scale data storage and processing are invaluable. The course's hands-on approach to setting up and configuring Hadoop, along with its coverage of file operations and compression, can help Database Administrator to more effectively manage data.
See salaries and explore the career path for Database Administrator
System Administrator
The system administrator is responsible for managing and maintaining computer systems and servers. This may involve tasks such as system installation, configuration, monitoring, and troubleshooting. This course on HDFS architecture and programming may be useful for System Administrator working with Hadoop clusters. The course's hands-on approach to setting up and configuring Hadoop, along with coverage of HDFS architecture and components, is helpful for managing HDFS environments.
See salaries and explore the career path for System Administrator
Machine Learning Engineer
The machine learning engineer develops and deploys machine learning models. This includes building data pipelines, training models, and deploying them to production environments. This course on HDFS architecture and programming may be useful for Machine Learning Engineers, particularly those working with large datasets. The course's focus on HDFS programming, file operations, compression, and serialization helps build the skills needed to manage and process data efficiently for machine learning tasks.
See salaries and explore the career path for Machine Learning Engineer
Data Scientist
The data scientist analyzes large datasets to extract insights and inform business decisions. This includes data cleaning, preprocessing, statistical analysis, and machine learning. While a data scientist may not always directly interact with HDFS, understanding its architecture and programming is beneficial when working with big data. This course helps build a foundation in working with large-scale data storage and processing. The course's focus on practical experience with HDFS could be helpful.
See salaries and explore the career path for Data Scientist
Solutions Architect
The solutions architect designs and implements technology solutions to meet business needs. This involves understanding business requirements, designing the overall system architecture, and selecting the appropriate technologies. This course on HDFS architecture and programming may prepare one for architecting solutions that involve big data storage and processing. The course's comprehensive coverage of HDFS architecture, components, and programming techniques helps one design scalable and robust solutions. The course may be useful for the Solutions Architect.
See salaries and explore the career path for Solutions Architect
Software Engineer
The software engineer designs, develops, and tests software applications. This can range from web applications to mobile apps to enterprise systems. This course on HDFS architecture and programming provides valuable experience in working with distributed file systems and big data technologies. The course's hands-on approach to HDFS programming, including setting up Java environments and working with files, can help Software Engineer in developing scalable and high-performance applications. This course also covers sequence and map files.
See salaries and explore the career path for Software Engineer
Data Analyst
The data analyst collects, cleans, and analyzes data to identify trends, patterns, and insights. Data analysts use these insights to inform business decisions and improve performance. A course like HDFS Architecture and Programming may be helpful for the data analyst. By understanding the underlying infrastructure and programming aspects of HDFS, one gains a deeper insight into the data that they are working with. This course also covers sequence and map files.
See salaries and explore the career path for Data Analyst
Business Intelligence Analyst
The business intelligence analyst analyzes data to identify trends and insights that can help improve business performance. This may involve creating reports, dashboards, and visualizations to communicate findings to stakeholders. This course on HDFS architecture and programming may allow the Business Intelligence Analyst to better understand the data they are working with. This course also covers sequence and map files.
See salaries and explore the career path for Business Intelligence Analyst

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
Save
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
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Provides hands-on experience with HDFS, allowing learners to write client programs and apply advanced techniques for specialized data storage, which is essential for big data processing
Covers essential topics such as the HDFS programming model, file and directory CRUD operations, and compression techniques, which are fundamental for managing data within HDFS
Explores serialization, deserialization, and specialized file structures like Sequence and Map Files, which are useful for optimizing data storage and retrieval in big data applications
Teaches how to set up Java programming environments and configure Hadoop, which is a practical skill for developing HDFS-based applications
Focuses on HDFS 1.0 architecture, so learners should be aware that there are newer versions of HDFS with potentially different features and capabilities
Requires learners to set up and configure Hadoop for Java development, which may require specific software versions and configurations that are not explicitly detailed
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