Book Image

Mastering Apache Spark

By : Mike Frampton
Book Image

Mastering Apache Spark

By: Mike Frampton

Overview of this book

<p>Apache Spark is an in-memory cluster based parallel processing system that provides a wide range of functionality like graph processing, machine learning, stream processing and SQL. It operates at unprecedented speeds, is easy to use and offers a rich set of data transformations.</p> <p>This book aims to take your limited knowledge of Spark to the next level by teaching you how to expand Spark functionality. The book commences with an overview of the Spark eco-system. You will learn how to use MLlib to create a fully working neural net for handwriting recognition. You will then discover how stream processing can be tuned for optimal performance and to ensure parallel processing. The book extends to show how to incorporate H20 for machine learning, Titan for graph based storage, Databricks for cloud-based Spark. Intermediate Scala based code examples are provided for Apache Spark module processing in a CentOS Linux and Databricks cloud environment.</p>
Table of Contents (17 chapters)
Mastering Apache Spark
Credits
Foreword
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Further reading


Before summing up this chapter, and the last for cloud-based Apache Spark usage in Databricks, I wanted to mention some resources for gaining extra information on both, Apache Spark, and Databricks. First, there is the Databricks forum available at: forums.databricks.com/ for questions, and answers related to the use of https://databricks.com/. Also, within your Databricks instance, under the Workspace menu option, there will be a Databricks guide that contains a lot of useful information. The Apache Spark website at http://spark.apache.org/ also contains a lot of useful information, as well as module-based API documentation. Finally, there is the Spark mailing list, , which provides a great deal of Spark usage information, and problem solving.