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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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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

Processing XML data in Hive using XML SerDe


XML has been one of the most important data structures and has been used for quite a long time for data transfers and storage. Parsing XML data and then processing it is always a tricky task as parsing XML is one of the most costliest operations. Hive does not have any built-in support for XML data processing, but many organizations and individuals have made open source contributions to XML SerDe.

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. Apart from Hive, we also need XML SerDe.

There are various XML SerDe that have been made available by open source developers. Out of these, XML SerDe at https://github.com/dvasilen/Hive-XML-SerDe is well developed and quite useful. So, we can download the jar from http://search.maven.org/remotecontent?filepath=com/ibm/spss/hive/serde2/xml/hivexmlserde/1.0.5.3/hivexmlserde-1.0.5.3.jar.

How to do...

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