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

Chapter 4. Project Tungsten

This chapter introduces Project Tungsten. CPU and main memory performance became the new bottlenecks in big data processing after the massive increase in I/O performance due to the usage of solid state disks (SSDs) and 10 Gbps Ethernet. Therefore, Project Tungsten, the core of the Apache Spark execution engine, aims at improving performance at the CPU and main memory level. This chapter will cover the following topics:

  • Memory management beyond the Java Virtual Machine (JVM) Garbage Collector (GC)
  • Cache-friendly layout of data in memory
  • Code generation

We will have an in-depth look at all these three topics now.