Book Image

Big Data Analytics with Hadoop 3

By : Sridhar Alla
Book Image

Big Data Analytics with Hadoop 3

By: Sridhar Alla

Overview of this book

Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly.
Table of Contents (18 chapters)
Title Page
Copyright and Credits
Packt Upsell
Scientific Computing and Big Data Analysis with Python and Hadoop

Chapter 2. Overview of Big Data Analytics

In this chapter, we will talk about big data analytics, starting with a general point of view and then taking a deep dive into some common technologies used to gain insights into data. This chapter introduces the reader to the process of examining large data sets to uncover patterns in data, generating reports, and gathering valuable insights. We will particularly focus on the seven Vs of big data. We will also learn about data analysis and big data; we will see the challenges that big data provides and how they are dealt with in distributed computing, and look at approaches using Hive and Tableau to showcase the most commonly used technologies.

In a nutshell, the following topics will be covered throughout this chapter:

  • Introduction to data analytics
  • Introduction to big data
  • Distributed computing using Apache Hadoop
  • MapReduce framework
  • Hive
  • Apache Spark