Book Image

Hadoop Real-World Solutions Cookbook - Second Edition

By : Tanmay Deshpande
Book Image

Hadoop Real-World Solutions Cookbook - Second Edition

By: Tanmay Deshpande

Overview of this book

Big data is the current requirement. Most organizations produce huge amount of data every day. With the arrival of Hadoop-like tools, it has become easier for everyone to solve big data problems with great efficiency and at minimal cost. Grasping Machine Learning techniques will help you greatly in building predictive models and using this data to make the right decisions for your organization. Hadoop Real World Solutions Cookbook gives readers insights into learning and mastering big data via recipes. The book not only clarifies most big data tools in the market but also provides best practices for using them. The book provides recipes that are based on the latest versions of Apache Hadoop 2.X, YARN, Hive, Pig, Sqoop, Flume, Apache Spark, Mahout and many more such ecosystem tools. This real-world-solution cookbook is packed with handy recipes you can apply to your own everyday issues. Each chapter provides in-depth recipes that can be referenced easily. This book provides detailed practices on the latest technologies such as YARN and Apache Spark. Readers will be able to consider themselves as big data experts on completion of this book. This guide is an invaluable tutorial if you are planning to implement a big data warehouse for your business.
Table of Contents (18 chapters)
Hadoop Real-World Solutions Cookbook Second Edition
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Preface
Index

Writing a user-defined function in Hive


In the previous chapter, we talked about how to write user-defined functions in Pig; in this recipe, we are going to do the same for Hive. Hive supports the adding of temporary functions, which can be used to process data. We will be writing UDF in Java and will also create functions that can be used in data processing.

Getting ready

To perform this recipe, you should have a running Hadoop cluster as well as the latest version of Hive installed on it. Here, I am using Hive 1.2.1. We will also need the Eclipse IDE for development.

How to do it

There are various system functions that are supported by Hive, but sometimes, you will need to do something different that cannot be handled by system provided functions. To do this, we will need to write a custom function.

Take a situation where we have census data and a person's income, and we want to categorize them into three parts based on the person's income. The following is some sample data where we have the...