Book Image

Pentaho 3.2 Data Integration: Beginner's Guide

Book Image

Pentaho 3.2 Data Integration: Beginner's Guide

Overview of this book

Pentaho Data Integration (a.k.a. Kettle) is a full-featured open source ETL (Extract, Transform, and Load) solution. Although PDI is a feature-rich tool, effectively capturing, manipulating, cleansing, transferring, and loading data can get complicated.This book is full of practical examples that will help you to take advantage of Pentaho Data Integration's graphical, drag-and-drop design environment. You will quickly get started with Pentaho Data Integration by following the step-by-step guidance in this book. The useful tips in this book will encourage you to exploit powerful features of Pentaho Data Integration and perform ETL operations with ease.Starting with the installation of the PDI software, this book will teach you all the key PDI concepts. Each chapter introduces new features, allowing you to gradually get involved with the tool. First, you will learn to work with plain files, and to do all kinds of data manipulation. Then, the book gives you a primer on databases and teaches you how to work with databases inside PDI. Not only that, you'll be given an introduction to data warehouse concepts and you will learn to load data in a data warehouse. After that, you will learn to implement simple and complex processes.Once you've learned all the basics, you will build a simple datamart that will serve to reinforce all the concepts learned through the book.
Table of Contents (27 chapters)
Pentaho 3.2 Data Integration Beginner's Guide
Credits
Foreword
The Kettle Project
About the Author
About the Reviewers
Preface
Index

Time for action – testing the transformation that keeps a historyof product changes


  1. In the previous tutorial you loaded a dimension with products by using a Dimension lookup/update step. You ran the transformation once, causing the insertion of one record for each product and a special record with values n/a for the descriptive fields. Let's apply some changes in the operational database, and run the transformation again to see how the Dimension lookup/update step keeps history.

  2. In MySQL Query Browser, open the script update_jumbo_products.sql and run it.

  3. Switch to Spoon.

  4. If the transformation created in the last tutorial is not open, open it again.

  5. Run the transformation. Explore the js_dw database again. Press Open SQL for [lk_puzzles] and type the following sentence:

    SELECT   *
    FROM     lk_puzzles
    WHERE    id_js_man = 'JUM' 
    ORDER BY id_js_prod
           , version
  6. You will see this:

What just happened?

After making some changes in the operational database, you ran the transformation for a second...