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

Using the Cluster Launch Scripts to Start a Standalone Cluster


We have seen how easy it was to launch a cluster with minimal effort. But, the cluster that we had set up was a relatively smallish cluster with only 5 worker nodes. Imagine, setting up a 5000 nodes cluster following the above steps. This will neither be easy nor maintainable especially in terms of adding/removing nodes from this cluster. Spark therefore provides options by which you can make sure you don't have to manually perform such configuration.

Before running any scripts you have to make sure that the workers are accessible from the master via SSH. You will need to provide either of the following:

  1. Password-less ssh between the master and the workers.
  2. Set SPARK_SSH_FOREGROUND option - Serially provide password for each worker.

In addition to the SSH configuration, you will need to create a configuration file in the conf directory called slaves, where you will enter the names of nodes which should be used as workers...