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)

Large-Scale Data Processing Frameworks

As the volume and complexity of data sources are increasing, deriving value out of data is also becoming increasingly difficult. Ever since Hadoop was made, it has built a massively scalable filesystem, HDFS. It has adopted the MapReduce concepts from functional programming to approach the large-scale data processing challenges. As technology is constantly evolving to overcome the challenges posed by data mining, enterprises are also finding ways to embrace these changes to stay ahead.

In this chapter, we will focus on these data processing solutions:

  • MapReduce
  • Apache Spark
  • Spark SQL
  • Spark Streaming