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

Spark Streaming

Spark Streaming wasn't the first streaming architecture. Over time, multiple technologies have been developed in order to address various real-time processing needs. One of the first popular stream processor technologies was Twitter Storm, and it was used in many businesses. Spark includes the streaming library, which has grown to become the most widely used technology today. This is mainly because Spark Streaming holds some significant advantages over all of the other technologies, the most important being its integration of Spark Streaming APIs within its core API. Not only that, but Spark Streaming is also integrated with Spark ML and Spark SQL, along with GraphX. Because of all of these integrations, Spark is a powerful and versatile streaming technology.

Note that has more information on Spark Streaming Flink, Heron (Twitter Storm's successor), and Samza and their various features; for example, their...