Book Image

Apache Oozie Essentials

By : Jagat Singh
Book Image

Apache Oozie Essentials

By: Jagat Singh

Overview of this book

As more and more organizations are discovering the use of big data analytics, interest in platforms that provide storage, computation, and analytic capabilities is booming exponentially. This calls for data management. Hadoop caters to this need. Oozie fulfils this necessity for a scheduler for a Hadoop job by acting as a cron to better analyze data. Apache Oozie Essentials starts off with the basics right from installing and configuring Oozie from source code on your Hadoop cluster to managing your complex clusters. You will learn how to create data ingestion and machine learning workflows. This book is sprinkled with the examples and exercises to help you take your big data learning to the next level. You will discover how to write workflows to run your MapReduce, Pig ,Hive, and Sqoop scripts and schedule them to run at a specific time or for a specific business requirement using a coordinator. This book has engaging real-life exercises and examples to get you in the thick of things. Lastly, you’ll get a grip of how to embed Spark jobs, which can be used to run your machine learning models on Hadoop. By the end of the book, you will have a good knowledge of Apache Oozie. You will be capable of using Oozie to handle large Hadoop workflows and even improve the availability of your Hadoop environment.
Table of Contents (16 chapters)
Apache Oozie Essentials
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Chapter 8. Running Spark Jobs

In this chapter, we will see how to run Spark jobs from Oozie. Spark has changed the whole ecosystem of Hadoop and the Big Data world. It can be used as ETL tool or machine learning tool, and it can be used where traditionally we use Pig, Hive, or Sqoop.

In this chapter, we will:

  • Create Oozie Workflow for Spark actions

From the concept point of view, we will:

  • Understand the concept of Bundles

We will start off with a simple Workflow in which we will rewrite the same Pig logic of finding maximum rainfall in a given month in Spark and then we will schedule that using Oozie Workflow and Coordinators. The idea is to show the beauty of Spark—how seamlessly it replaces various tools such as Pig or Hive, and how it has become the default execution engine of the Big Data platform. If you are a very keen follower of Hadoop news, recently Cloudera announced that they are declaring phase out of MapReduce and are going to keep all their eggs in the Spark bucket. The vast number...