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)

Prerequisites for Hadoop setup

In this section, we will look at the necessary prerequites for setting up Apache Hadoop in cluster or pseudo mode. Often, teams are forced to go through a major reinstallation of Hadoop and the data migration of their clusters due to improper planning for their cluster requirements. Hadoop can be installed on Windows as well as Linux; however, most productions that Hadoop installations run on are Unix or Linux-based platforms.

Preparing hardware for Hadoop

One important aspect of Hadoop setup is defining the hardware requirements and sizing before the start of a project. Although Apache Hadoop can run on commodity hardware, most of the implementations utilize server-class hardware for their Hadoop...