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.
HDFS Architecture and Programming
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HDFS Architecture and Programming
This course is part of Big Data Processing Using Hadoop Specialization
Instructor: Karthik Shyamsunder
Included with 
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Understand HDFS architecture, components, and how it ensures scalability and availability for big data processing.
Learn to configure Hadoop for Java programming and perform file CRUD operations using HDFS APIs.
Master advanced HDFS programming concepts like compression, serialization, and working with specialized file structures like Sequence and Map files.
Skills you'll gain
Details to know
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Recently updated!
January 2025
Assessments
9 assignments
Taught in English
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This course is part of the Big Data Processing Using Hadoop Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
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.
What's included
2 readings
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.
What's included
6 videos4 readings3 assignments
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.
What's included
6 videos5 readings3 assignments
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.
What's included
6 videos5 readings3 assignments
Instructor
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