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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

Interspersing new rows between existent rows


In most Kettle datasets, all rows share a common meaning; they represent the same kind of entity, for example:

  • In a dataset with sold items, each row has data about one item

  • In a dataset with the mean temperature for a range of days in five different regions, each row has the mean temperature for a different day in one of those regions

  • In a dataset with a list of people ordered by age range (0-10, 11-20, 20-40, and so on), each row has data about one person

Sometimes, there is a need of interspersing new rows between your current rows. Taking the previous examples, imagine the following situations:

  • In the sold items dataset, every 10 items, you have to insert a row with the running quantity of items and running sold price from the first line until that line.

  • In the temperature's dataset, you have to order the data by region and the last row for each region has to have the average temperature for that region.

  • In the people's dataset, for each age range...

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