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Hadoop Real-World Solutions Cookbook- Second Edition

You're reading from   Hadoop Real-World Solutions Cookbook- Second Edition Over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout

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Product type Paperback
Published in Mar 2016
Publisher
ISBN-13 9781784395506
Length 290 pages
Edition 2nd Edition
Tools
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Author (1):
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Tanmay Deshpande Tanmay Deshpande
Author Profile Icon Tanmay Deshpande
Tanmay Deshpande
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started with Hadoop 2.X FREE CHAPTER 2. Exploring HDFS 3. Mastering Map Reduce Programs 4. Data Analysis Using Hive, Pig, and Hbase 5. Advanced Data Analysis Using Hive 6. Data Import/Export Using Sqoop and Flume 7. Automation of Hadoop Tasks Using Oozie 8. Machine Learning and Predictive Analytics Using Mahout and R 9. Integration with Apache Spark 10. Hadoop Use Cases Index

Storing and processing Hive data in the RC file format

I'm sure that most of the time, you would have created Hive tables and stored data in a text format; in this recipe, we are going to store data in RC files.

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 going to use Hive 1.2.1.

How to do it...

Hive 1.2.1 supports different types of files, which help process data in a fast manner. In this recipe, we are going to use RC files to store data in Hive. To store data in RC files, we first need to create a Hive table that stores this data in a textual format. We will use the same table that we created in the first recipe.

Creating a table to store RCFILE is very easy, as shown here:

create table employee_rc(
id int, name string)
row format delimited
fields terminated by '|'
stored as RCFILE;

To insert data into the table from our text table, we need to execute the following query, which...

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