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Pentaho Data Integration Cookbook - Second Edition - Second Edition

You're reading from  Pentaho Data Integration Cookbook - Second Edition - Second Edition

Product type Book
Published in Dec 2013
Publisher Packt
ISBN-13 9781783280674
Pages 462 pages
Edition 2nd Edition
Languages

Table of Contents (21) Chapters

Pentaho Data Integration Cookbook Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Working with Databases Reading and Writing Files Working with Big Data and Cloud Sources Manipulating XML Structures File Management Looking for Data Understanding and Optimizing Data Flows Executing and Re-using Jobs and Transformations Integrating Kettle and the Pentaho Suite Getting the Most Out of Kettle Utilizing Visualization Tools in Kettle Data Analytics Data Structures 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...

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