Book Image

Pentaho Data Integration 4 Cookbook

Book Image

Pentaho Data Integration 4 Cookbook

Overview of this book

Pentaho Data Integration (PDI, also called Kettle), one of the data integration tools leaders, is broadly used for all kind of data manipulation such as migrating data between applications or databases, exporting data from databases to flat files, data cleansing, and much more. Do you need quick solutions to the problems you face while using Kettle? Pentaho Data Integration 4 Cookbook explains Kettle features in detail through clear and practical recipes that you can quickly apply to your solutions. The recipes cover a broad range of topics including processing files, working with databases, understanding XML structures, integrating with Pentaho BI Suite, and more. Pentaho Data Integration 4 Cookbook shows you how to take advantage of all the aspects of Kettle through a set of practical recipes organized to find quick solutions to your needs. The initial chapters explain the details about working with databases, files, and XML structures. Then you will see different ways for searching data, executing and reusing jobs and transformations, and manipulating streams. Further, you will learn all the available options for integrating Kettle with other Pentaho tools. Pentaho Data Integration 4 Cookbook has plenty of recipes with easy step-by-step instructions to accomplish specific tasks. There are examples and code that are ready for adaptation to individual needs.

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Pentaho Data Integration 4 Cookbook
Jun, 2011 | 352 pages
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Table of Contents (17 chapters)
Pentaho Data Integration 4 Cookbook
Pentaho Data Integration 4 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
Working with Databases
Working with Databases
Introduction
Connecting to a database
Getting data from a database
Getting data from a database by providing parameters
Getting data from a database by running a query built at runtime
Inserting or updating rows in a table
Inserting new rows where a simple primary key has to be generated
Inserting new rows where the primary key has to be generated based on stored values
Deleting data from a table
Creating or altering a database table from PDI (design time)
Creating or altering a database table from PDI (runtime)
Inserting, deleting, or updating a table depending on a field
Changing the database connection at runtime
Loading a parent-child table
2
Reading and Writing Files
Reading and Writing Files
Introduction
Reading a simple file
Reading several files at the same time
Reading unstructured files
Reading files having one field by row
Reading files with some fields occupying two or more rows
Writing a simple file
Writing an unstructured file
Providing the name of a file (for reading or writing) dynamically
Using the name of a file (or part of it) as a field
Reading an Excel file
Getting the value of specific cells in an Excel file
Writing an Excel file with several sheets
Writing an Excel file with a dynamic number of sheets
3
Manipulating XML Structures
Manipulating XML Structures
Introduction
Reading simple XML files
Specifying fields by using XPath notation
Validating well-formed XML files
Validating an XML file against DTD definitions
Validating an XML file against an XSD schema
Generating a simple XML document
Generating complex XML structures
Generating an HTML page using XML and XSL transformations
4
File Management
File Management
Introduction
Copying or moving one or more files
Deleting one or more files
Getting files from a remote server
Putting files on a remote server
Copying or moving a custom list of files
Deleting a custom list of files
Comparing files and folders
Working with ZIP files
5
Looking for Data
Looking for Data
Introduction
Looking for values in a database table
Looking for values in a database (with complex conditions or multiple tables involved)
Looking for values in a database with extreme flexibility
Looking for values in a variety of sources
Looking for values by proximity
Looking for values consuming a web service
Looking for values over an intranet or Internet
6
Understanding Data Flows
Understanding Data Flows
Introduction
Splitting a stream into two or more streams based on a condition
Merging rows of two streams with the same or different structures
Comparing two streams and generating differences
Generating all possible pairs formed from two datasets
Joining two or more streams based on given conditions
Interspersing new rows between existent rows
Executing steps even when your stream is empty
Processing rows differently based on the row number
7
Executing and Reusing Jobs and Transformations
Executing and Reusing Jobs and Transformations
Introduction
Executing a job or a transformation by setting static arguments and parameters
Executing a job or a transformation from a job by setting arguments and parameters dynamically
Executing a job or a transformation whose name is determined at runtime
Executing part of a job once for every row in a dataset
Executing part of a job several times until a condition is true
Creating a process flow
Moving part of a transformation to a subtransformation
8
Integrating Kettle and the Pentaho Suite
Integrating Kettle and the Pentaho Suite
Introduction
Creating a Pentaho report with data coming from PDI
Configuring the Pentaho BI Server for running PDI jobs and transformations
Executing a PDI transformation as part of a Pentaho process
Executing a PDI job from the Pentaho User Console
Generating files from the PUC with PDI and the CDA plugin
Populating a CDF dashboard with data coming from a PDI transformation
9
Getting the Most Out of Kettle
Getting the Most Out of Kettle
Introduction
Sending e-mails with attached files
Generating a custom log file
Programming custom functionality
Generating sample data for testing purposes
Working with Json files
Getting information about transformations and jobs (file-based)
Getting information about transformations and jobs (repository-based)
Data Structures
Data Structures
Book's data structure
Museum's data structure
Outdoor data structure
Steel Wheels structure
Index
Index

Introduction

Databases are broadly used by organizations to store and administer transactional data such as customer service history, bank transactions, purchases and sales, and so on. They also constitute the storage method for data warehouses, the repositories used in Business Intelligence solutions.

In this chapter, you will learn to deal with databases in Kettle. The first recipe tells you how to connect to a database, which is a prerequisite for all the other recipes. The rest of the chapter teaches you how to perform different operations and can be read in any order according to your needs.

Note

The focus of this chapter is on relational databases (RDBMS). Thus the term database is used as a synonym for relational databases through the recipes.

Sample databases

Through the chapter you will use a couple of sample databases. Those databases can be created and loaded by running the scripts available at the book's website. The scripts are ready to run under MySQL.

Note

If you work with a different DBMS you may have to modify the scripts slightly.

For more information about the structure of the sample databases and the meaning of the tables and fields, please refer to Appendix, Data Structures. Feel free to adapt the recipes to different databases. You could try some well known databases; for example Foodmart (available as part of the Mondrian distribution at http://sourceforge.net/projects/mondrian/) or the MySQL sample databases (available at http://dev.mysql.com/doc/index-other.html).

Pentaho BI platform databases

As part of the sample databases used in this chapter you will use the Pentaho BI platform Demo databases. The Pentaho BI Platform Demo is a pre-configured installation that lets you explore the capabilities of the Pentaho platform. It relies on the following databases:

Database name

Description

hibernate

Administrative information including user authentication and authorization data.

quartz

Repository for Quartz, the scheduler used by Pentaho.

sampledata

Data for Steel Wheels, a fictional company that sells all kind of scale replicas of vehicles.

By default, all those databases are stored in Hypersonic (HSQLDB). The script for creating the databases in HSQLDB can be found at http://sourceforge.net/projects/pentaho/files. Under Business Intelligence Server | 1.7.1-stable look for pentaho_sample_data-1.7.1.zip.

It can also be found at svn://ci.pentaho.com/view/Platform/job/bi-platform-sample-data/.

These databases can be stored in other DBMS as well. Scripts for creating and loading these databases in other popular DBMS as for example MySQL or Oracle can be found in Prashant Raju's blog, at http://www.prashantraju.com/projects/pentaho/.

Beside the scripts, you will find instructions for creating and loading the databases.

Tip

Prashant Raju, an expert Pentaho developer, provides several excellent tutorials related to the Pentaho platform. If you are interested in knowing more about Pentaho, it's worth taking a look at his blog.

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