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Pentaho Data Integration Cookbook - Second Edition - Second Edition

You're reading from  Pentaho Data Integration Cookbook - Second Edition - Second Edition

Product type Book
Published in Dec 2013
Publisher Packt
ISBN-13 9781783280674
Pages 462 pages
Edition 2nd Edition
Languages

Table of Contents (21) Chapters

Pentaho Data Integration Cookbook Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Working with Databases 2. Reading and Writing Files 3. Working with Big Data and Cloud Sources 4. Manipulating XML Structures 5. File Management 6. Looking for Data 7. Understanding and Optimizing Data Flows 8. Executing and Re-using Jobs and Transformations 9. Integrating Kettle and the Pentaho Suite 10. Getting the Most Out of Kettle 11. Utilizing Visualization Tools in Kettle 12. Data Analytics Data Structures References Index

Using the name of a file (or part of it) as a field


There are some occasions where you need to include the name of a file as a column in your dataset for further processing. With Kettle, you can do it in a very simple way.

In this example, you have several text files about camping products. Each file belongs to a different category and you know the category from the filename. For example, tents.txt contains tent products. You want to obtain a single dataset with all the products from these files including a field indicating the category of every product.

Getting ready

In order to run this exercise, you need a directory (campingProducts) with text files named kitchen.txt, lights.txt, sleeping_bags.txt, tents.txt, and tools.txt. Each file contains descriptions of the products and their price separated with a |. Consider the following example:

Swedish Firesteel - Army Model|$19.97
Mountain House #10 Can Freeze-Dried Food|$53.50
Coleman 70-Quart Xtreme Cooler (Blue)|$59.99
Kelsyus Floating Cooler...
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