Book Image

Modern Big Data Processing with Hadoop

By : V Naresh Kumar, Manoj R Patil, Prashant Shindgikar
Book Image

Modern Big Data Processing with Hadoop

By: V Naresh Kumar, Manoj R Patil, Prashant Shindgikar

Overview of this book

The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems.
Table of Contents (12 chapters)

Hadoop MapReduce

Apache MapReduce is a framework that makes it easier for us to run MapReduce operations on very large, distributed datasets. One of the advantages of Hadoop is a distributed file system that is rack-aware and scalable. The Hadoop job scheduler is intelligent enough to make sure that the computation happens on the nodes where the data is located. This is also a very important aspect as it reduces the amount of network IO.

Let's see how the framework makes it easier to run massively parallel computations with the help of this diagram:

This diagram looks a bit more complicated than the previous diagram, but most of the things are done by the Hadoop MapReduce framework itself for us. We still write the code for mapping and reducing our input data.

Let's see in detail what happens when we process our data with the Hadoop MapReduce framework from the preceding...