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Pentaho Data Integration

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Overview

This page serves as a library for each of the Pentaho Data Integration (PDI) Best Practices, Guidelines, and Techniques documents. It contains helpful information for the many uses, components and standards that have been developed to help you accomplish optimal use and performance.

Contents

  • Design Standards and Guidelines
    • PDI Project Setup and Lifecycle Management - new!
    • Design Guidelines for PDI
    • Naming Standards for PDI
    • Standards for Lookups, Joins, and Subroutines in PDI
  • How-To Guides
    • Realtime Data Processing with PDI
    • Fixed Width Data in PDI
    • Guidelines for Metadata Injection in PDI
    • Restartability in PDI
  • Working with the PDI Repository
    • Dividing Large Repositories in PDI
    • Logging and Monitoring in PDI
    • Performance Tuning in PDI
    • R on PDI
    • Pentaho Analyzer with Impala as a Data Source
    • Pentaho and QuickStart VM

The Components Reference in Pentaho Documentation has a complete list of supported software and hardware.

Design Standards and Guidelines

 projsetup_sm.png PDI Project Setup and Lifecycle Management
For versions 6.x, 7.x, 8.x / published November 2018

This page discusses and highlights all components of PDI project setup and lifecycle management. In it, you will find information on content and configuration, configuration management, logging and monitoring, Git, and how to use the DI framework.

Audience: Pentaho developers or anyone who is interested in setting up and improving PDI projects.

PDI_lib5.jpg Design Guidelines for PDI
For versions 6.x, 7.x, 8.0 / published December 2017

PDI Design Guidelines will show you how to create transformations and jobs for maximum speed, reuse, portability, maintainability, debugging, and knowledge transfer.

Audience: Pentaho ETL developers and architects, or anyone who is interested in learning PDI development patterns.

PDI_lib3.jpg Naming Standards for PDI
For versions 7.x, 8.x/ published June 2018

PDI contains step naming standards and help with choosing the appropriate steps in certain situations.

Audience: PDI users or anyone with a background in ETL development who is interested in learning PDI development patterns.

PDI_lib4.jpg Standards for Lookups, Joins, and Subroutines in PDI
For versions 7.x, 8.0 / published November 2017

Lookups, joins, and subroutines for PDI are covered in this document through best practices.

Audience: PDI users or anyone with a background in ETL development who is interested in learning PDI development patterns.

 

How-To Guides

RealtimePDI.png Realtime Data Processing with PDI 
For version 8.0 / published March 2018

This is part of a webinar covering best practices on designing and building your PDI transformations and jobs for maximum speed, reuse, portability, and debugging.

Audience: Solution architects and designers, or anyone with a background in real time data ingestion, or messaging systems like Java Message Servers.

 
PDI_lib1.jpg Fixed Width Data in PDI
For versions 6.x, 7.x, and 8.0 / published December 2017

PDI offers the Fixed File Input step for reading fixed-width text files. On the output side, there is no step dedicated to this specific purpose, but fixed-width text can still be written using the existing Text file output step. This document walks you through the changes you will need to make to the default column metadata to successfully accomplish this task.

Audience: Data analysts and ETL developers who need to write fixed-width data.

PDI_lib14.jpg Guidelines for Metadata Injection in PDI
For versions 6.x, 7.x, 8.0 / published December 2017

Here, you will find best practices for using template-driven designs and for navigating and operating the different levels of metadata injection. We have provided an example of how to build the data-driven rule extract/transform/load (ETL) transformation and make it flexible so that it can be added to, changed, or removed without adding development cycles.

Audience: Customers in need of tips for using template-driven designs, and for building the template-driven ETL transformation.

PDI_lib2.jpg Restartability in PDI
For versions 6.x, 7.x, 8.0 / published December 2017

Restartability architecture in PDI jobs and transformations plays a key role in restarting a failed ETL process where it left off. This is true whether you need to avoid duplicate entries in the target database, or you are simply seeking overall ETL efficiency and do not want to rerun processes that completed successfully in the previous run.

Audience: Pentaho ETL developers and architects, or anyone who is interested in learning PDI development patterns.

 

Working with the PDI Repository

PDI_lib16.jpg Dividing Large Repositories in PDI
For versions 6.x, 7.x, 8.0 / published August 2017

Performance and management problems are addressed here by detailing an automated method to improve performance with segmenting a single repository into several smaller repositories using PDI.

Audience: Customers looking to create a single PDI repository for maintaining many environments.

PDI_lib15.jpg Logging and Monitoring in PDI
For versions 6.x, 7.x, 8.0 / published February 2018

The main objective of this document is to provide information about the different options for best practices for PDI logging. Some of the things discussed here include reasons for using PDI logging, levels of logging, transformation and job logging, and debugging transformations and jobs.

Audience: Customers or developers who may be interested in using PDI logging.

PDI_lib18.jpg Performance Tuning in PDI
For versions 5.4, 6.x, 7.x / published August 2017

This guide provides an overview of factors that can affect the performance of PDI jobs and transformations, and it provides a methodical approach to identifying and addressing bottlenecks.

Audience: Customers who seek assistance with finding and fixing bottlenecks in their PDI performance.

r_on_pdi.png R on PDI
For version 6.x, 7.x, 8.0 / published December 2017

This document covers some best practices on integrating R with PDI, including how to install and use R with PDI and why you would want to use this setup.

Audience: Data analysts, data scientists, and PDI users who need to use the variety of statistical and machine learning tools available in the R environment.

analyzer_impala_sm.png Pentaho Analyzer with Impala as a Data Source
For version 6.x, 7.x, 8.0 / published February 2018

This is a collection of best practices on using Pentaho Analyzer with Impala data sources, including how to prepare and partition data and set configurations. You will also learn about schema recommendations and settings for Analyzer.

Audience: Pentaho developers, system administrators, and architects.

pentaho_and_cloudera_quickstart_sm.png Pentaho and QuickStart VM
For version 7.x, 8.x / published May 2018

This document covers some best practices on integrating Pentaho software with Cloudera QuickStart VM, including how to configure the QuickStart VM so that Pentaho can connect to it.

Audience: Pentaho developers and system architects looking to experiment with PDI and Hadoop.

 

 

 

 

 

 

 

 

 

 

 

 

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