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Pentaho Data Integration 4 Cookbook

Pentaho Data Integration 4 Cookbook

4.8 (8)
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Pentaho Data Integration 4 Cookbook

Pentaho Data Integration 4 Cookbook

4.8 (8)

Overview of this book

Pentaho Data Integration (PDI, also called Kettle), one of the data integration tools leaders, is broadly used for all kind of data manipulation such as migrating data between applications or databases, exporting data from databases to flat files, data cleansing, and much more. Do you need quick solutions to the problems you face while using Kettle? Pentaho Data Integration 4 Cookbook explains Kettle features in detail through clear and practical recipes that you can quickly apply to your solutions. The recipes cover a broad range of topics including processing files, working with databases, understanding XML structures, integrating with Pentaho BI Suite, and more. Pentaho Data Integration 4 Cookbook shows you how to take advantage of all the aspects of Kettle through a set of practical recipes organized to find quick solutions to your needs. The initial chapters explain the details about working with databases, files, and XML structures. Then you will see different ways for searching data, executing and reusing jobs and transformations, and manipulating streams. Further, you will learn all the available options for integrating Kettle with other Pentaho tools. Pentaho Data Integration 4 Cookbook has plenty of recipes with easy step-by-step instructions to accomplish specific tasks. There are examples and code that are ready for adaptation to individual needs.
Table of Contents (17 chapters)
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Pentaho Data Integration 4 Cookbook
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Looking for values in a variety of sources


The first recipes in the chapter showed you how to look for additional information in a database. There are still many other sources of information. You may need to look in property files, in Excel files, in text files, and so on. Kettle allows you to look for data coming from all those sources with the Stream lookup step.

In this example, you have information about books coming from an Excel file and you need to complete this dataset by looking up the author's data and genre description, which are in external sources. In this case, the author's information is inside a text file and the genres are in a fixed predefined list.

Getting ready

For doing this recipe, you will need the following:

  • A CSV file (authors.txt) with the author's data. The file should have the following columns: lastname, firstname, nationality, and id_author. The following are sample lines of this file:

    "lastname","firstname","nationality","id_author"
    "Larsson","Stieg","Swedish",...

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