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

Understanding the core concepts of Docker


So now it's time to further unfold the topic by introducing Docker. Docker basically makes use of LXC but adds support for building, shipping, and running operation system images. So there exists a layered image format, which makes it possible to pack the filesystem components necessary for running a specific application into a Docker images file.

Note

Although not necessary for this chapter because it is already provided by the following minikube package we are using, Docker can be easily installed on different operating systems. Since Docker uses functionality only present in the Linux kernel, it can be run natively only on Linux (and only there you will see the performance benefits over using virtual machines). But you still can use it on macOS and Windows, where a separate hypervisor is running Docker on Linux in the background. So on Ubuntu Linux, we'll just provide the command here since it is so simple: sudo apt install docker.io.Please have...