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 – treating errors that may appear


  1. Open the transformation from the tutorial and save it under a different name.

  2. From the Transform category, drag the Add constants step to the canvas.

  3. Create a hop from the Write to log step to the Add constants step.

  4. Add an Integer constant named diff with value 999, and a String constant named age_of_film with value unknown.

  5. After the Add constants step, add a Select values step and use it to remove the fields err_code and err_desc.

  6. Create a hop from the Select values step to the Sort rows step. Your transformation should look like this:

    Note

    Note that you are merging two streams. Those streams must have the same metadata. If you get a trap detector warning, please verify that you executed these instructions exactly as explained.

  7. Select the Dummy step and do a preview. You will see this:

What just happened?

You modified the transformation so that you didn't end up discarding the erroneous rows. In the error stream (the stream after the red dotted...