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

Performing FILTER By queries in Pig


After going through the various file formats that we can use to store data in HDFS, it's time to take a look at how to execute various operations in Pig. Pig is a data flow language and works in the same way as Hive by transforming the instructions given in Pig Latin to Map Reduce programs.

Getting ready

To perform this recipe, you should have a running Hadoop cluster as well as the latest version of Pig installed on it. Here, I am going to use Pig 0.15. In case you don't have the installation already, you can refer to https://pig.apache.org/docs/r0.15.0/start.html#Pig+Setup.

How to do it...

In this recipe, you will learn how to use FILTER BY in the Pig script. To do so, let's assume that we have an employee dataset that is stored in the following format (ID, name, department, and salary):

1	Tanmay	ENGINEERING	5000
2	Sneha	PRODUCTION	8000
3	Sakalya	ENGINEERING	7000
4	Avinash	SALES	6000
5	Manisha	SALES	5700
6	Vinit	FINANCE	6200

Here the columns are delimited...