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Pentaho Data Integration 4 Cookbook

You're reading from   Pentaho Data Integration 4 Cookbook Over 70 recipes to solve ETL problems using Pentaho Kettle

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Product type Paperback
Published in Jun 2011
Publisher Packt
ISBN-13 9781849515245
Length 352 pages
Edition 1st Edition
Tools
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Toc

Table of Contents (17) Chapters Close

Pentaho Data Integration 4 Cookbook
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Working with Databases FREE CHAPTER 2. Reading and Writing Files 3. Manipulating XML Structures 4. File Management 5. Looking for Data 6. Understanding Data Flows 7. Executing and Reusing Jobs and Transformations 8. Integrating Kettle and the Pentaho Suite 9. Getting the Most Out of Kettle Data Structures 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 |. For 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|$26.99
Lodge LCC3...
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