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.
Scala Data Analysis Cookbook
By :
Scala Data Analysis Cookbook
By:
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
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Getting Started with Breeze
Getting Started with Apache Spark DataFrames
Loading and Preparing Data – DataFrame
Data Visualization
Learning from Data
Scaling Up
Going Further
Index
Customer Reviews