Book Image

Pentaho Data Integration Cookbook - Second Edition

Book Image

Pentaho Data Integration Cookbook - Second Edition

Overview of this book

Pentaho Data Integration is the premier open source ETL tool, providing easy, fast, and effective ways to move and transform data. While PDI is relatively easy to pick up, it can take time to learn the best practices so you can design your transformations to process data faster and more efficiently. If you are looking for clear and practical recipes that will advance your skills in Kettle, then this is the book for you. Pentaho Data Integration Cookbook Second Edition guides you through the features of explains the Kettle features in detail and provides easy to follow recipes on file management and databases that can throw a curve ball to even the most experienced developers. Pentaho Data Integration Cookbook Second Edition provides updates to the material covered in the first edition as well as new recipes that show you how to use some of the key features of PDI that have been released since the publication of the first edition. You will learn how to work with various data sources – from relational and NoSQL databases, flat files, XML files, and more. The book will also cover best practices that you can take advantage of immediately within your own solutions, like building reusable code, data quality, and plugins that can add even more functionality. Pentaho Data Integration Cookbook Second Edition will provide you with the recipes that cover the common pitfalls that even seasoned developers can find themselves facing. You will also learn how to use various data sources in Kettle as well as advanced features.
Table of Contents (21 chapters)
Pentaho Data Integration Cookbook Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
References
Index

Introduction


While flat files and databases are the most common type of source that developers using Kettle interact with, there are many other types of data sources that are capable of being used. Data warehouses are now starting to leverage the capabilities of tools such as Hadoop, NoSQL databases, and cloud services such as Amazon Web Services and SalesForce.

In this chapter, you will learn to interact with these Big Data sources in Kettle. The recipes in this chapter are grouped into various data sources, with each grouping covering how to connect, read data from, and load data into the given data source.

The focus of this chapter is on data sources that are usually larger than can be set up for working through exercises. For each data source, the recipe Connecting to a database in Chapter 1, Working with Databases, will cover how to connect to the given data source, as well as recommendations for setting up a test environment in which to work in.