Book Image

Scala Data Analysis Cookbook

By : Arun Manivannan
Book Image

Scala Data Analysis Cookbook

By: Arun Manivannan

Overview of this book

This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you’ll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX.
Table of Contents (14 chapters)
Scala Data Analysis Cookbook
About the Author
About the Reviewers

Running the Spark Job on YARN (local)

Hadoop has a long history, and in most cases, organizations have already invested in the Hadoop infrastructure before they move their MR jobs to Spark. Unlike the Spark standalone cluster manager, which can run only Spark jobs, and Mesos, which can run a variety of applications, YARN runs Hadoop jobs as first-class. At the same time, it can run Spark jobs as well. This means that when a team decides to replace some of their MR jobs with Spark jobs, they can use the same cluster manager to run Spark jobs. In this recipe, we'll see how to deploy our Spark application on the YARN cluster manager.

How to do it...

Running a Spark job on YARN is very similar to running it against a Spark standalone cluster. It involves the following steps:

  1. Installing the Hadoop cluster.

  2. Starting HDFS and YARN.

  3. Pushing the Spark assembly and dataset to HDFS.

  4. Running the Spark Job in the yarn-client mode.

  5. Running the Spark Job in the yarn-cluster mode.

Installing the Hadoop cluster...