Book Image

Learning Apache Spark 2

Book Image

Learning Apache Spark 2

Overview of this book

Apache Spark has seen an unprecedented growth in terms of its adoption over the last few years, mainly because of its speed, diversity and real-time data processing capabilities. It has quickly become the preferred choice of tool for many Big Data professionals looking to find quick insights from large chunks of data. This book introduces you to the Apache Spark framework, and familiarizes you with all the latest features and capabilities introduced in Spark 2. Starting with a detailed introduction to Spark’s architecture and the installation procedure, this book covers everything you need to know about the Spark framework in the most practical manner. You will learn how to perform the basic ETL activities using Spark, and work with different components of Spark such as Spark SQL, as well as the Dataset and DataFrame APIs for manipulating your data. Then, you will perform machine learning using Spark MLlib, as well as perform streaming analytics and graph processing using the Spark Streaming and GraphX modules respectively. The book also gives special emphasis on deploying your Spark models, and how they can be operated in a clustered mode. During the course of the book, you will come across implementations of different real-world use-cases and examples, giving you the hands-on knowledge you need to use Apache Spark in the best possible manner.
Table of Contents (18 chapters)
Learning Apache Spark 2
Credits
About the Author
About the Reviewers
www.packtpub.com
Customer Feedback
Preface

Running Spark in standalone mode


A standalone mode is basically when Spark uses its default mode provided with the application and does not use one of the externally provided cluster managers like YARN or Mesos. In this section, we'll look at the following key topics:

  • Installing Spark Standalone on a cluster
  • Starting the cluster
    • Manually
    • Launch-Scripts
  • Launching an application in the cluster
  • Monitoring
  • Configuring High-Availability
    • Configuring Stand-by masters with ZooKeeper
    • Recovery with the FileSystem

Installing Spark standalone on a cluster

In our example we are going to build a 6 node Spark cluster, and have a windows machine submit Spark jobs to the cluster. We'll not develop a new Spark program, but rather submit the examples provided with the Spark Framework for the purpose of this exercise. Our architecture looks something like the following image:

Figure 8.2: Spark Standalone Cluster Deployment

The installation of a standalone cluster is very simple, you need to place...