- 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
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
- Designing Spark Applications