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Home > Data > Data Visualization > Pentaho Data Integration Beginner's Guide - Second Edition
Pentaho Data Integration Beginner's Guide - Second Edition
Pentaho Data Integration Beginner's Guide - Second Edition

Pentaho Data Integration Beginner's Guide - Second Edition: Get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guide with this book and ebook , Second Edition

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Pentaho Data Integration Beginner's Guide - Second Edition

Chapter 2. Getting Started with Transformations

In the previous chapter, you used the graphical designer Spoon to create your first transformation: Hello world. Now you're ready to begin transforming data, and at the same time get familiar with the Spoon environment.

In this chapter, you will:

  • Learn the simplest ways of transforming data
  • Get familiar with the process of designing, debugging, and testing a transformation
  • Explore the available features for running transformations from Spoon
  • Learn basic PDI terminology related with data
  • Get an introduction to handling runtime errors

Designing and previewing transformations

In the first chapter, you created a Hello world transformation, previewed the data, and also ran the transformation. As you saw, the preview functionality allows you to see a sample of the data produced for selected steps and the Run option effectively runs the whole transformation. In this section, you will experiment the Preview option in detail. You will also deal with errors that may appear as you develop and test a transformation.

Time for action – creating a simple transformation and getting familiar with the design process

In this exercise, you will create a simple transformation that takes a list of projects with the start and end dates, and calculates the time that it took to complete each project.

  1. Start Spoon.
  2. From the main menu, navigate to File | New | Transformation.
  3. Expand the Input branch of the Steps tree. Remember that the Steps tree is located in the Design tab to the left of the work area.
  4. Drag-and-drop the Data Grid icon on the canvas.
  5. Double-click on the Data Grid icon and enter projects in the Step name field.
  6. Fill in the grid as shown in the following screenshot:
    Time for action – creating a simple transformation and getting familiar with the design process
  7. Click on the Data tab, and fill the grid as shown in the following screenshot:
    Time for action – creating a simple transformation and getting familiar with the design process
  8. Click on Preview and in the small window that appears, click on OK.
  9. Oops! It seems that something went wrong. The following ERROR window appears:
    Time for action – creating a simple transformation and getting familiar with the design process
  10. Great! Now you know what the error was: Kettle tried to convert the string N/A to a date. You can easily fix it: delete...

Running transformations in an interactive fashion

In the previous section, you created a transformation and learned some basics about working with Spoon during the design process. Now you will continue learning about interacting with Spoon. This time you will create a new transformation and then run it.

Time for action – generating a range of dates and inspecting the data as it is being created

In this section, you will generate a rowset with one row by date in a date range.

Tip

As you progress, feel free to preview the data that is being generated even if you're not told to do so. This will help you understand what is going on. Testing each step as you move forward makes it easier to debug and craft a functional transformation.

  1. Create a new transformation.
  2. From the Input group of steps, drag to the canvas a Generate Rows step.
  3. Double-click on the step and fill in the grid as shown in the following screenshot:
    Time for action – generating a range of dates and inspecting the data as it is being created
  4. Note that you have to change the default value for the Limit textbox. Close the window.
  5. From the Transform category of steps, add a Calculator step, and create a hop that goes from the Generate Rows step to this one.
  6. Double-click on the Calculator step and add a field named diff_dates as the difference between end_date and start_date. That is, configure it exactly the same way...

Handling errors

So far, each time you got an error you had the opportunity to discover what kind of error it was and fix it. This is quite different form real scenarios, mainly for two reasons:

  • Real data has errors—a fact that cannot be avoided. If you fail to heed it, the transformations that run with test or sample data will probably crash when running with real data.
  • In most cases, your final work is run by an automated process and not by a user from Spoon. Therefore, if a transformation crashes, there will be nobody who notices and reacts to that situation.

In the next section, you will learn the simplest way to trap errors that may occur, avoiding unexpected crashes. This is the first step in the creation of transformations ready to be run in a production environment.

Time for action – avoiding errors while converting the estimated time from string to integer

In this section, you will create a variation of the first transformation in this chapter. In this case, you will allow invalid data as source, but will take care of it:

  1. Create a transformation.
  2. Add a Data Grid step and fill in the Meta tab just like you did in the first section: add a string named project_name and two dates with the format yyyy-MM-dd, named start_date and end_date. Also add a fourth field of type String, named estimated.
  3. Now also fill in the Data tab with the same values you had in that first section. For the estimated field, type the following values: 30, 180, 180, 700, 700, ---.

    Tip

    You can avoid typing all of this in again! Instead of adding and configuring the step from scratch, open the transformation you created in the first section, select the Data Grid step, copy it by pressing Ctrl + C, and paste it into the new transformation by pressing Ctrl + V. Then enter the new...

Time for action – configuring the error handling to see the description of the errors

In this section, you will adapt the previous transformation so that you can capture more detail about the errors that occur:

  1. Open the transformation from the previous section, and save it with a different name. You can do it from the main menu by navigating to File | Save as…, or from the main toolbar.
  2. Right-click on the Select values step and select Define Error handling.... The following dialog window appears:
    Time for action – configuring the error handling to see the description of the errors
  3. In the Error descriptions fieldname textbox, type error_desc and click on OK.
  4. Double-click on the Write to log step and, after the last row, type or select error_desc.
  5. Save the transformation.
  6. Do a preview on the Write to log step. You will see a new field named error_desc with the description of the error.
  7. Run the transformation. In the Execution Window, you will see the following code:
    Write to log.0 - ------------> Linenr 1------------------------
Write to log.0 - There was an error...

Designing and previewing transformations

In the first chapter, you created a Hello world transformation, previewed the data, and also ran the transformation. As you saw, the preview functionality allows you to see a sample of the data produced for selected steps and the Run option effectively runs the whole transformation. In this section, you will experiment the Preview option in detail. You will also deal with errors that may appear as you develop and test a transformation.

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Page 1 of 9

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Key benefits

  • Manipulate your data by exploring, transforming, validating, and integrating it
  • Learn to migrate data between applications
  • Explore several features of Pentaho Data Integration 5.0
  • Connect to any database engine, explore the databases, and perform all kind of operations on databases

Description

Capturing, manipulating, cleansing, transferring, and loading data effectively are the prime requirements in every IT organization. Achieving these tasks require people devoted to developing extensive software programs, or investing in ETL or data integration tools that can simplify this work. Pentaho Data Integration is a full-featured open source ETL solution that allows you to meet these requirements. Pentaho Data Integration has an intuitive, graphical, drag-and-drop design environment and its ETL capabilities are powerful. However, getting started with Pentaho Data Integration can be difficult or confusing. "Pentaho Data Integration Beginner's Guide - Second Edition" provides the guidance needed to overcome that difficulty, covering all the possible key features of Pentaho Data Integration. "Pentaho Data Integration Beginner's Guide - Second Edition" starts with the installation of Pentaho Data Integration software and then moves on to cover all the key Pentaho Data Integration concepts. Each chapter introduces new features, allowing you to gradually get involved with the tool. First, you will learn to do all kinds of data manipulation and work with plain files. Then, the book gives you a primer on databases and teaches you how to work with databases inside Pentaho Data Integration. Moreover, you will be introduced to data warehouse concepts and you will learn how to load data in a data warehouse. After that, you will learn to implement simple and complex processes. Finally, you will have the opportunity of applying and reinforcing all the learned concepts through the implementation of a simple datamart. With "Pentaho Data Integration Beginner's Guide - Second Edition", you will learn everything you need to know in order to meet your data manipulation requirements.

Who is this book for?

This book is a must-have for software developers, database administrators, IT students, and everyone involved or interested in developing ETL solutions, or, more generally, doing any kind of data manipulation. Those who have never used Pentaho Data Integration will benefit most from the book, but those who have, they will also find it useful. This book is also a good starting point for database administrators, data warehouse designers, architects, or anyone who is responsible for data warehouse projects and needs to load data into them.

What you will learn

  • Install and get started with Pentaho Data Integration
  • Get started with MySQL
  • Learn the ins and outs of Spoon, the graphical designer tool
  • Transform data in several ways such as performing simple and complex calculations, cleaning, counting, de-duplicating, filtering, and ordering
  • Learn to get data from all kind of data sources as plain files, Excel spreadsheets, databases, XML files and more, then preview it, and send it back to the same or different destinations
  • Discover how to read and parse unstructured files
  • Embed Java and JavaScript code in your Pentaho Data Integration transformations to enrich the treatment of data
  • Use Pentaho Data Integration to perform CRUD (create, read, update, and delete) operations on databases
  • Learn the basic concepts of data warehousing
  • Populate a data warehouse with Pentaho Data Integration including loading slowly changing dimensions, junk dimensions, time dimensions and more
  • Implement business processes by scheduling tasks, checking conditions, organizing files and folders, running daily processes, treating errors, and so on in a way that meets your requirements

Product Details

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Publication date : Oct 24, 2013
Length: 502 pages
Edition : 2nd
Language : English
ISBN-13 : 9781782165057
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Category :
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Concepts :
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Publication date : Oct 24, 2013
Length: 502 pages
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Language : English
ISBN-13 : 9781782165057
Vendor :
Pentaho
Category :
Data
Languages :
Java
Concepts :
Data Visualization
Tools :
Pentaho

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Table of Contents

20 Chapters
1. Getting Started with Pentaho Data Integration Chevron down icon Chevron up icon
1. Getting Started with Pentaho Data Integration
Pentaho Data Integration and Pentaho BI Suite
Exploring the Pentaho Demo
Installing PDI
Time for action – installing PDI
Launching the PDI graphical designer – Spoon
Time for action – starting and customizing Spoon
Time for action – creating a hello world transformation
Installing MySQL
Time for action – installing MySQL on Windows
Time for action – installing MySQL on Ubuntu
Summary
2. Getting Started with Transformations Chevron down icon Chevron up icon
2. Getting Started with Transformations
Designing and previewing transformations
Time for action – creating a simple transformation and getting familiar with the design process
Running transformations in an interactive fashion
Time for action – generating a range of dates and inspecting the data as it is being created
Handling errors
Time for action – avoiding errors while converting the estimated time from string to integer
Time for action – configuring the error handling to see the description of the errors
Summary
3. Manipulating Real-world Data Chevron down icon Chevron up icon
3. Manipulating Real-world Data
Reading data from files
Time for action – reading results of football matches from files
Time for action – reading all your files at a time using a single text file input step
Time for action – reading all your files at a time using a single text file input step and regular expressions
Sending data to files
Time for action – sending the results of matches to a plain file
Getting system information
Time for action – reading and writing matches files with flexibility
Time for action – running the matches transformation from a terminal window
XML files
Time for action – getting data from an XML file with information about countries
Summary
4. Filtering, Searching, and Performing Other Useful Operations with Data Chevron down icon Chevron up icon
4. Filtering, Searching, and Performing Other Useful Operations with Data
Sorting data
Time for action – sorting information about matches with the Sort rows step
Calculations on groups of rows
Time for action – calculating football match statistics by grouping data
Filtering
Time for action – counting frequent words by filtering
Time for action – refining the counting task by filtering even more
Looking up data
Time for action – finding out which language people speak
5. Controlling the Flow of Data Chevron down icon Chevron up icon
5. Controlling the Flow of Data
Splitting streams
Time for action – browsing new features of PDI by copying a dataset
Time for action – assigning tasks by distributing
Splitting the stream based on conditions
Time for action – assigning tasks by filtering priorities with the Filter rows step
Time for action – assigning tasks by filtering priorities with the Switch/Case step
Merging streams
Time for action – gathering progress and merging it all together
Time for action – giving priority to Bouchard by using the Append Stream
Treating invalid data by splitting and merging streams
Time for action – treating errors in the estimated time to avoid discarding rows
Summary
6. Transforming Your Data by Coding Chevron down icon Chevron up icon
6. Transforming Your Data by Coding
Doing simple tasks with the JavaScript step
Time for action – counting frequent words by coding in JavaScript
Reading and parsing unstructured files with JavaScript
Time for action – changing a list of house descriptions with JavaScript
Doing simple tasks with the Java Class step
Time for action – counting frequent words by coding in Java
Transforming the dataset with Java
Time for action – splitting the field to rows using Java
Avoiding coding by using purpose built steps
Summary
7. Transforming the Rowset Chevron down icon Chevron up icon
7. Transforming the Rowset
Converting rows to columns
Time for action – enhancing the films file by converting rows to columns
Aggregating data with a Row Denormaliser step
Time for action – aggregating football matches data with the Row Denormaliser step
Normalizing data
Time for action – enhancing the matches file by normalizing the dataset
Generating a custom time dimension dataset by using Kettle variables
Time for action – creating the time dimension dataset
Time for action – parameterizing the start and end date of the time dimension dataset
Summary
8. Working with Databases Chevron down icon Chevron up icon
8. Working with Databases
Introducing the Steel Wheels sample database
Time for action – creating a connection to the Steel Wheels database
Time for action – exploring the sample database
Querying a database
Time for action – getting data about shipped orders
Time for action – getting orders in a range of dates using parameters
Time for action – getting orders in a range of dates by using Kettle variables
Sending data to a database
Time for action – loading a table with a list of manufacturers
Time for action – inserting new products or updating existing ones
Time for action – testing the update of existing products
Eliminating data from a database
Time for action – deleting data about discontinued items
Summary
9. Performing Advanced Operations with Databases Chevron down icon Chevron up icon
9. Performing Advanced Operations with Databases
Preparing the environment
Time for action – populating the Jigsaw database
Looking up data in a database
Time for action – using a Database lookup step to create a list of products to buy
Time for action – using a Database join step to create a list of suggested products to buy
Introducing dimensional modeling
Loading dimensions with data
Time for action – loading a region dimension with a Combination lookup/update step
Time for action – testing the transformation that loads the region dimension
Time for action – keeping a history of changes in products by using the Dimension lookup/update step
Time for action – testing the transformation that keeps history of product changes
Summary
10. Creating Basic Task Flows Chevron down icon Chevron up icon
10. Creating Basic Task Flows
Introducing PDI jobs
Time for action – creating a folder with a Kettle job
Designing and running jobs
Time for action – creating a simple job and getting familiar with the design process
Running transformations from jobs
Time for action – generating a range of dates and inspecting how things are running
Receiving arguments and parameters in a job
Time for action – generating a hello world file by using arguments and parameters
Running jobs from a terminal window
Time for action – executing the hello world job from a terminal window
Using named parameters and command-line arguments in transformations
Time for action – calling the hello world transformation with fixed arguments and parameters
Deciding between the use of a command-line argument and a named parameter
Summary
11. Creating Advanced Transformations and Jobs Chevron down icon Chevron up icon
11. Creating Advanced Transformations and Jobs
Re-using part of your transformations
Time for action – calculating statistics with the use of a subtransformations
Time for action – generating top average scores by copying and getting rows
Iterating jobs and transformations
Time for action – generating custom files by executing a transformation for every input row
Enhancing your processes with the use of variables
Time for action – generating custom messages by setting a variable with the name of the examination file
Summary
12. Developing and Implementing a Simple Datamart Chevron down icon Chevron up icon
12. Developing and Implementing a Simple Datamart
Exploring the sales datamart
Loading the dimensions
Time for action – loading the dimensions for the sales datamart
Extending the sales datamart model
Loading a fact table with aggregated data
Time for action – loading the sales fact table by looking up dimensions
Getting facts and dimensions together
Time for action – loading the fact table using a range of dates obtained from the command line
Time for action – loading the SALES star
Automating the administrative tasks
Time for action – automating the loading of the sales datamart
Summary
A. Working with Repositories Chevron down icon Chevron up icon
A. Working with Repositories
Creating a database repository
Time for action – creating a PDI repository
Working with the repository storage system
Time for action – logging into a database repository
Examining and modifying the contents of a repository with the Repository Explorer
Migrating from file-based system to repository-based system and vice versa
Summary
B. Pan and Kitchen – Launching Transformations and Jobs from the Command Line Chevron down icon Chevron up icon
B. Pan and Kitchen – Launching Transformations and Jobs from the Command Line
Running transformations and jobs stored in files
Running transformations and jobs from a repository
Kettle variables and the Kettle home directory
Checking the exit code
Providing options when running Pan and Kitchen
Summary
C. Quick Reference – Steps and Job Entries Chevron down icon Chevron up icon
C. Quick Reference – Steps and Job Entries
Transformation steps
Job entries
Summary
D. Spoon Shortcuts Chevron down icon Chevron up icon
D. Spoon Shortcuts
General shortcuts
Designing transformations and jobs
Grids
Repositories
Database wizards
Summary
E. Introducing PDI 5 Features Chevron down icon Chevron up icon
E. Introducing PDI 5 Features
Welcome page
Usability
Solutions to commonly occurring situations
Backend
Summary
F. Best Practices Chevron down icon Chevron up icon
F. Best Practices
Summary
G. Pop Quiz Answers Chevron down icon Chevron up icon
Chapter 1, Getting Started with Pentaho Data Integration
Chapter 2, Getting Started with Transformations
Chapter 3, Manipulating Real-world Data
Chapter 4, Filtering, Searching, and Performing Other Useful Operations with Data
Chapter 5, Controlling the Flow of Data
Chapter 6, Transforming Your Data by Coding
Chapter 8, Working with Databases
Chapter 9, Performing Advanced Operations with Databases
Chapter 10, Creating Basic Task Flows
Chapter 11, Creating Advanced Transformations and Jobs
Chapter 12, Developing and Implementing a Simple Datamart
Index Chevron down icon Chevron up icon
Index

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Profound Reviewer Jun 13, 2017
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This is really a wonderful resource. I understand both the basics of Pentaho and much more beyond that. The book is filled with example after example. All are helpful and useful. I can't imagine a better introduction to Pentaho. Highly recommended!
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Jaime A Solares Silva Jul 09, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excelente libro
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Antonio Tostes Jr. Sep 19, 2014
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Extremely helpful!
Amazon Verified review Amazon
Hugh Powers May 19, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good introduction book if you're looking to get into using Kettle. The author does a good job of presenting the subject using good examples, and doesn't get overly techie with the reader. Good book also for those who know SSIS but are looking for other ETL tools to explore.
Amazon Verified review Amazon

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About the author

Profile icon Carina Roldán
Carina Roldán
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María Carina Roldán was born in Argentina and has a bachelor's degree in computer science. She started working with Pentaho back in 2006. She spent all these years developing BI solutions, mainly as an ETL specialist, and working for different companies around the world. Currently, she lives in Buenos Aires and works as an independent consultant. Carina is the author of Learning Pentaho Data Integration 8 CE, published by Packt in December 2017. She has also authored other books on Pentaho, all of them published by Packt.
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