Book Image

Apache Spark 2 for Beginners

By : Rajanarayanan Thottuvaikkatumana
Book Image

Apache Spark 2 for Beginners

By: Rajanarayanan Thottuvaikkatumana

Overview of this book

<p>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.</p> <p>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.</p> <p>By the end of this book, you will have all the knowledge you need to develop efficient large-scale applications using Apache Spark.</p>
Table of Contents (15 chapters)
Apache Spark 2 for Beginners
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface

Summary


This chapter concludes the book with one single application's use cases, implemented using the Spark concepts learned in the earlier chapters of the book. From a data processing application architecture perspective, this chapter covered the Lambda Architecture as a technology-agnostic architectural framework for data processing applications, which has huge applicability in the big data application development space.

From a data processing application development perspective, RDD-based Spark programming, Dataset-based Spark programming, Spark SQL-based DataFrames to process structured data, the Spark Streaming-based listener program that constantly listens to the incoming messages and processes them, and the Spark GraphX-based application to process follower relationships have been covered. The use cases covered so far have immense scope for readers to add their own functionalities and enhance the application use cases discussed in this chapter.