Book Image

Pentaho Data Integration Cookbook - Second Edition - Second Edition

Book Image

Pentaho Data Integration Cookbook - Second Edition - 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

Loading data into MongoDB


MongoDB is a type of NoSQL database, called a document store. Data is stored in JSON-like arrays in a format called BSON (binary JSON), which allows for quick and scalable queries. Java Script Object Notation (JSON), are name/value pairs that can be nested to store complex data. Another way of thinking of a MongoDB document is that they are akin to a multidimensional array. Like many NoSQL databases, the schema structure is dynamic. This means that the descriptors of a dataset can be added, removed, or not even required for records to be stored into a given document.

Getting ready

We will continue to use the Lahman's Baseball Database mentioned earlier in the chapter to load MongoDB and later use it to query for specific data. Before we can do anything else though, we need to make sure that we have an instance of MongoDB to play with, either locally on a virtual machine or elsewhere. To download a copy of MongoDB, check out the website at http://www.monodb/org/downloads...