Book Image

Pentaho Analytics for MongoDB Cookbook

By : Joel André Latino, Harris Ward
Book Image

Pentaho Analytics for MongoDB Cookbook

By: Joel André Latino, Harris Ward

Overview of this book

MongoDB is an open source, schemaless NoSQL database system. Pentaho as a famous open source Analysis tool provides high performance, high availability, and easy scalability for large sets of data. The variant features in Pentaho for MongoDB are designed to empower organizations to be more agile and scalable and also enables applications to have better flexibility, faster performance, and lower costs. Whether you are brand new to online learning or a seasoned expert, this book will provide you with the skills you need to create turnkey analytic solutions that deliver insight and drive value for your organization. The book will begin by taking you through Pentaho Data Integration and how it works with MongoDB. You will then be taken through the Kettle Thin JDBC Driver for enabling a Java application to interact with a database. This will be followed by exploration of a MongoDB collection using Pentaho Instant view and creating reports with MongoDB as a datasource using Pentaho Report Designer. The book will then teach you how to explore and visualize your data in Pentaho BI Server using Pentaho Analyzer. You will then learn how to create advanced dashboards with your data. The book concludes by highlighting contributions of the Pentaho Community.

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Pentaho Analytics for MongoDB Cookbook
Joel André Latino | Harris Ward
Dec, 2015 | 218 pages
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Table of Contents (15 chapters)
Pentaho Analytics for MongoDB Cookbook
Pentaho Analytics for MongoDB Cookbook
Credits
Credits
About the Authors
About the Authors
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
PDI and MongoDB
PDI and MongoDB
Introduction
Learning basic operations with Pentaho Data Integration
Migrating data from the RDBMS to MongoDB
Loading data from MongoDB to MySQL
Migrating data from files to MongoDB
Exporting MongoDB data using the aggregation framework
MongoDB Map/Reduce using the User Defined Java Class step and MongoDB Java Driver
Working with jobs and filtering MongoDB data using parameters and variables
2
The Thin Kettle JDBC Driver
The Thin Kettle JDBC Driver
Introduction
Using a transformation as a data service
Running the Carte server in a single instance
Running the Pentaho Data Integration server in a single instance
Define a connection using a SQL Client (SQuirreL SQL)
3
Pentaho Instaview
Pentaho Instaview
Introduction
Creating an analysis view
Modifying Instaview transformations
Modifying the Instaview model
Exploring, saving, deleting, and opening analysis reports
4
A MongoDB OLAP Schema
A MongoDB OLAP Schema
Introduction
Creating a date dimension
Creating an Orders cube
Creating the customer and product dimensions
Saving and publishing a Mondrian schema
Creating a Mondrian 4 physical schema
Creating a Mondrian 4 cube
Publishing a Mondrian 4 schema
5
Pentaho Reporting
Pentaho Reporting
Introduction
Copying the MongoDB JDBC library
Connecting to MongoDB using Reporting Wizard
Connecting to MongoDB via PDI
Adding a chart to a report
Adding parameters to a report
Adding a formula to a report
Grouping data in reports
Creating subreports
Creating a report with MongoDB via Java
Publishing a report to the Pentaho server
Running a report in the Pentaho server
6
The Pentaho BI Server
The Pentaho BI Server
Introduction
Importing Foodmart MongoDB sample data
Creating a new analysis view using Pentaho Analyzer
Creating a dashboard using Pentaho Dashboard Designer
7
Pentaho Dashboards
Pentaho Dashboards
Introduction
Copying the MongoDB JDBC library
Importing a sample repository
Using a transformation data source
Using a BeanShell data source
Using Pentaho Analyzer for MongoDB data source
Using a Thin Kettle data source
Defining dashboard layouts
Creating a Dashboard Table component
Creating a Dashboard line chart component
8
Pentaho Community Contributions
Pentaho Community Contributions
Introduction
The PDI MongoDB Delete Step
The PDI MongoDB GridFS Output Step
The PDI MongoDB Map/Reduce Output step
The PDI MongoDB Lookup step
Index
Index

The PDI MongoDB Map/Reduce Output step

Most aggregation operations in MongoDB are done by the Aggregation Framework, which provides better performance, but in some cases, it is necessary that it possesses flexibility that isn't present in it and is just possible with Map/Reduce commands.

Ivy Information Systems has contributed a plugin with two MongoDB steps—MongoDB Map/Reduce and MongoDB Lookup—under the AGPL license. These are available on GitHub at https://github.com/ivylabs/ivy-pdi-mongodb-steps.

Getting ready

To get ready for this recipe, you will need to start your ETL development environment Spoon, and make sure that you have the MongoDB server running with the data from the previous chapters.

How to do it…

Perform the following steps to create a quick sample for users with MongoDB Map/Reduce in PDI:

  1. Let's install the Ivy PDI MongoDB by performing the following steps:

    1. On the menu bar of Spoon, select Help and then Marketplace.

    2. A PDI Marketplace popup will show you the list of plugins available...

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