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 case study


Let's have a twist in the rainfall use case we solved in the previous chapter. Instead of getting CSV files for rainfall data, we need to import the rainfall data from MySQL database and then move on to processing.

As the first step of the analysis, we need to bring data inside Hadoop using Sqoop. To do this, we will use Sqoop import at end of each day to get data on Hadoop, and then we will run our Pig script for processing and saving results to Hive.

Just like previous chapters, we will start with the command-line option to trigger jobs, and we will learn about Sqoop action and scheduling it via Coordinator. Lastly, we will cover the concept of HCatalog Datasets. Let's get started.