Book Image

Apache Hadoop 3 Quick Start Guide

By : Hrishikesh Vijay Karambelkar
Book Image

Apache Hadoop 3 Quick Start Guide

By: Hrishikesh Vijay Karambelkar

Overview of this book

Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS. The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems. The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster.
Table of Contents (10 chapters)

Developing MapReduce Applications

"Programs must be written for people to read, and only incidentally for machines to execute."
– Harold Abelson, Structure and Interpretation of Computer Programs, 1984

When Apache Hadoop was designed, it was intended for large-scale processing of humongous data, where traditional programming techniques could not be applied. This was at a time when MapReduce was considered a part of Apache Hadoop. Earlier, MapReduce was the only programming option available in Hadoop; however, with new Hadoop releases, it was enhanced with YARN. It's also called MRv2 and older MapReduce is usually referred to as MRv1. In the previous chapter, we saw how HDFS can be configured and used for various application usages. In this chapter, we will do a deep dive into MapReduce programming to learn the different facets of how you can effectively...