Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud
Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink
Exploit big data using Hadoop 3 with real-world examples

Book Description

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.

What you will learn

Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce
Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples
Integrate Hadoop with R and Python for more efficient big data processing
Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics
Set up a Hadoop cluster on AWS cloud
Perform big data analytics on AWS using Elastic Map Reduce

Who This Book Is For

Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3's powerful features, or you're new to big data analytics. A basic understanding of the Java programming language is required.

Introduction to Hadoop
Overview of Big Data Analytics
Big Data Processing with MapReduce
Scientific Computing and Big Data Analysis with Python and Hadoop
Statistical Big Data Computing with R and Hadoop
Batch analytics with Apache Spark
Real time analytics with Apache Spark
Batch analytics with Apache Flink
Stream Processing with Apache Flink
Visualizing Big Data
Introduction to Cloud Computing
Using Amazon Web Services

About the Author

Sridhar Alla is a big data expert helping companies solve complex problems in distributed computing, large scale data science and analytics practice. He presents regularly at several prestigious conferences and provides training and consulting to companies. He holds a bachelor's in computer science from JNTU, India. He loves writing code in Python, Scala, and Java. He also has extensive hands-on knowledge of several Hadoop-based technologies, TensorFlow, NoSQL, IoT, and deep learning.

"About this title" may belong to another edition of this title.

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