The Building Blocks of Hadoop - HDFS, MapReduce, and YARN

Processing billions of records requires a deep understanding of distributed computing. In this course, you'll get introduced to Hadoop, an open-source distributed computing framework that can help you do just that.
Course info
Rating
(348)
Level
Beginner
Updated
Nov 4, 2016
Duration
2h 18m
Table of contents
Description
Course info
Rating
(348)
Level
Beginner
Updated
Nov 4, 2016
Duration
2h 18m
Description

You know how to write Java code and you know what processing you want to perform on your huge dataset. But, can you use the Hadoop distributed framework effectively to get your work done? This course, The Building Blocks of Hadoop ­ HDFS, MapReduce, and YARN, gives you a fundamental understanding of the building blocks of Hadoop: HDFS for storage, MapReduce for processing, and YARN for cluster management, to help you bridge the gap between programming and big data analysis. First, you'll get a complete architecture overview for Hadoop. Next, you'll learn how to set up a pseudo-distributed Hadoop environment and submit and monitor tasks on that environment. And finally, you'll understand the configuration choices you can make for stability, reliability optimized task scheduling on your distributed system. By the end of this course you'll have gained a strong understanding of the building blocks needed in order for you to use Hadoop effectively.

About the author
About the author

A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.

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