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Hadoop Real-World Solutions Cookbook - Second Edition

You're reading from  Hadoop Real-World Solutions Cookbook - Second Edition

Product type Book
Published in Mar 2016
Publisher
ISBN-13 9781784395506
Pages 290 pages
Edition 2nd Edition
Languages
Author (1):
Tanmay Deshpande Tanmay Deshpande
Profile icon Tanmay Deshpande

Table of Contents (18) Chapters

Hadoop Real-World Solutions Cookbook Second Edition
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Preface
Getting Started with Hadoop 2.X Exploring HDFS Mastering Map Reduce Programs Data Analysis Using Hive, Pig, and Hbase Advanced Data Analysis Using Hive Data Import/Export Using Sqoop and Flume Automation of Hadoop Tasks Using Oozie Machine Learning and Predictive Analytics Using Mahout and R Integration with Apache Spark Hadoop Use Cases Index

Performing table joins in Hive


In the previous chapter, we talked about how to perform joins in Pig. In this recipe, we are going to take a look at how to perform joins in Hive. Hive supports various types of joins such as inner, outer, and so on.

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.

How to do it...

To perform joins, we will need two types of datasets, which have something in common to join. Consider a situation where we have two employee tables and departments, and every employee table has a structure (ID, name, salary, and department ID) and every department table has an ID and a name. We will quickly create tables and load data into them:

 CREATE TABLE emp(
 id INT,
 name STRING,
 salary DOUBLE,
 deptId INT)
 ROW FORMAT DELIMITED
 FIELDS TERMINATED BY '|'
 STORED AS TEXTFILE;
 
 LOAD DATA LOCAL INPATH 'emp.txt' INTO TABLE emp;
    hive> select * from emp;
    OK
...
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