Apache Spark 2 for Beginners

Key Features This book offers an easy introduction to the Spark framework

published on the latest version of Apache Spark 2 Perform efficient data

processing, machine learning and graph processing using various Spark

components A practical guide aimed at beginners to get them up and running

with Spark Book Description

Spark is one of the most widely-used large-scale data processing engines and

runs extremely fast. It is a framework that has tools that are equally useful

for application developers as well as data scientists.

This book starts with the fundamentals of Spark 2 and covers the core data

processing framework and API, installation, and application development setup.

Then the Spark programming model is introduced through real-world examples

followed by Spark SQL programming with DataFrames. An introduction to SparkR

is covered next. Later, we cover the charting and plotting features of Python

in conjunction with Spark data processing. After that, we take a look at

Spark's stream processing, machine learning, and graph processing libraries.

The last chapter combines all the skills you learned from the preceding

chapters to develop a real-world Spark application.

By the end of this book, you will have all the knowledge you need to develop

efficient large-scale applications using Apache Spark.

What you will learn Get to know the fundamentals of Spark 2 and the Spark

programming model using Scala and Python Know how to use Spark SQL and

DataFrames using Scala and Python Get an introduction to Spark programming

using R Perform Spark data processing, charting, and plotting using Python Get

acquainted with Spark stream processing using Scala and Python Be introduced

to machine learning using Spark MLlib Get started with graph processing using

the Spark GraphX Bring together all that you've learned and develop a complete

Spark application About the Author

**Rajanarayanan Thottuvaikkatumana** , Raj, is a seasoned technologist with

more than 23 years of software development experience at various multinational

companies. He has lived and worked in India, Singapore, and the USA, and is

presently based out of the UK. His experience includes architecting,

designing, and developing software applications. He has worked on various

technologies including major databases, application development platforms, web

technologies, and big data technologies. Since 2000, he has been working

mainly in Java related technologies, and does heavy-duty server-side

programming in Java and Scala. He has worked on very highly concurrent, highly

distributed, and high transaction volume systems. Currently he is building a

next generation Hadoop YARN-based data processing platform and an application

suite built with Spark using Scala.

Raj holds one master's degree in Mathematics, one master's degree in Computer

Information Systems and has many certifications in ITIL and cloud computing to

his credit. Raj is the author of Cassandra Design Patterns - Second Edition,

published by Packt.

When not working on the assignments his day job demands, Raj is an avid

listener to classical music and watches a lot of tennis.

Table of Contents Spark Fundamentals Spark Programming Model Spark SQL Spark

Programming with R Spark Data Analysis with Python Spark Stream Processing

Spark Machine Learning Spark Graph Processing De