Book Image

Mastering Apache Spark 2.x - Second Edition

Book Image

Mastering Apache Spark 2.x - Second Edition

Overview of this book

Apache Spark is an in-memory, cluster-based Big Data processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and more. This book will take your knowledge of Apache Spark to the next level by teaching you how to expand Spark’s functionality and build your data flows and machine/deep learning programs on top of the platform. The book starts with a quick overview of the Apache Spark ecosystem, and introduces you to the new features and capabilities in Apache Spark 2.x. You will then work with the different modules in Apache Spark such as interactive querying with Spark SQL, using DataFrames and DataSets effectively, streaming analytics with Spark Streaming, and performing machine learning and deep learning on Spark using MLlib and external tools such as H20 and Deeplearning4j. The book also contains chapters on efficient graph processing, memory management and using Apache Spark on the cloud. By the end of this book, you will have all the necessary information to master Apache Spark, and use it efficiently for Big Data processing and analytics.
Table of Contents (21 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
10
Deep Learning on Apache Spark with DeepLearning4j and H2O

Overview


The following diagram shows potential data sources for Apache Streaming, such as Kafka, Flume, and HDFS:

These feed into the Spark Streaming module and are processed as Discrete Streams. The diagram also shows that other Spark module functionality, such as machine learning, can be used to process stream-based data.

The fully processed data can then be an output for HDFS, databases, or dashboards. This diagram is based on the one at the Spark streaming website, but we wanted to extend it to express the Spark module functionality:

When discussing Spark Discrete Streams, the previous figure, taken from the Spark website at http://spark.apache.org/, is the diagram that we would like to use.

The green boxes in the previous figure show the continuous data stream sent to Spark being broken down into a Discrete Stream (DStream).

Note

A DStream is nothing other than an ordered set of RDDs. Therefore, Apache Spark Streaming is not real streaming, but micro-batching. The size of the RDDs backing...