Codebits is an annual 3-day conference about software and, well, code. It's organized by SAPO and this year's edition is to be held on November 10 thru 12 at the Pavilhão Atlântico, Sala Tejo in Lisbon, Portugal.

I've never attended SAPO Codebits before, but I heard good things about it from Datacharmer Giuseppe Maxia. The interesting thing about the way this conference is organized is that all proposals are available to the public, which can also vote for the proposals. This year's proposals are looking very interesting already, with high quality proposals from …

Dear Kettle users,

Most of you usually use a data integration engine to process data in a batch-oriented way.  Pentaho Data Integration (Kettle) is typically deployed to run monthly, nightly, hourly workloads.  Sometimes folks run micro-batches of work every minute or so.  However, it’s lesser known that our beloved transformation engine can also be used to stream data indefinitely (never ending) from a source to a target.  This sort of data integration is sometimes referred to as being “streaming“, “real-time“, “near real-time“, “continuous” and so on.  Typical examples of situations where you have a never-ending supply of data that needs to be processed the instance it becomes available are JMS (Java Message Service), RDBMS log sniffing, on-line fraud analyses, web or application …

Dear Kettle friends,

on occasion we need to support environments where not only a lot of data needs to be processed but also in frequent batches.  For example, a new data file with hundreds of thousands of rows arrives in a folder every few seconds.

In this setting we want to use clustering to use “commodity” computing resources in parallel.  In this blog post I’ll detail how the general architecture would look like and how to tune memory usage in this environment.

Clustering was first created around the end of 2006.  Back then it looked like this.

The master

This is the most important part of our cluster.  It takes care of administrating network configuration and topology.  It also keeps track of the state of dynamically added slave servers.

The master …

Dear Kettlers,

A couple of years ago I wrote a post about key/value tables and how they can ruin the day of any honest person that wants to create BI solutions.  The obvious advice I gave back then was to not use those tables in the first place if you’re serious about a BI solution.  And if you have to, do some denormalization.

However, there are occasions where you need to query a source system and get some report going on them.  Let’s take a look at an example :

mysql> select * from person;
+----+-------+----------+
| id | name  | lastname |
+----+-------+----------+
|  1 | Lex   | Luthor   |
|  2 | Clark | Kent     |
|  3 | Lois  | Lane     |
+----+-------+----------+
3 rows in set (0.00 sec)

mysql> select * from person_attribute;
+----+-----------+---------------+------------+
| id | person_id | attr_key      | attr_value | …

Dear Kettle friends,

Some time ago while I visited the nice folks from Human Inference in Arnhem, I ran into Kasper Sørensen, the lead developer of DataCleaner.

DataCleaner is an open source data quality tool released (like Kettle) under the LGPL license.  It is essentially to blame for the lack of a profiling tool inside of Kettle.  That is because having DataCleaner available to our users was enough to push the priority of having our own data profiling tool far enough down.

Kasper worked on DataCleaner pretty much in his spare time in the past.  Now that Human Inference took over the project I was expecting more frequent updates and that’s what we …

Hi Folks,

Now that we’re blogging again I thought I might as well continue to do so.

Today we’re reading data from MongoDB with Pentaho Data Integration.  We haven’t had a lot of requests for MongoDB support so there is no step to read from it yet.  However, it is surprisingly simple to do with the “User Defined Java Class” step.

For the following sample to work you need to be on a recent 4.2.0-M1 build.  Get it from here.

Then download mongo-2.4.jar and put it in the libext/ folder of your PDI/Kettle distribution.

Then you can read from a collection with the following “User Defined Java Class” code:

import java.math.*;
import java.util.*;
import …

Dear Kettle friends,

Last year, right after the summer in version 4.1 of Pentaho Data Integration, we introduced the notion of dynamically inserted ETL metadata (Youtube video here).  Since then we received a lot of positive feedback on this functionality which encouraged me to extend it to a few more steps. Already with support for “CSV Input” and “Select Values” we could do a lot of dynamic things.  However, we can clearly do a lot better by extending our initiative to a few more steps: “Microsoft Excel Input” (which can also read ODS by the way), “Row Normalizer” and “Row De-normalizer”.

Below I’ll describe an actual (obfuscated) example that you will probably recognize as it is equally hideous as simple in it’s horrible complexity.

Take a look at this file:

Let’s assume that this spreadsheet …

It has been a while since I posted on my blog - in fact, I believe this is the first time ever that more than one month passed between posts since I started blogging. There are a couple of reasons for the lag:

• 
  
• Matt Casters, Jos van Dongen and me have spent a lot of time finalizing our forthcoming book, Pentaho Kettle Solutions (Wiley, ISBN: 978-0-470-63517-9). The book is currently being produced, and should be available according to schedule in early September 2010. If you're interested, you might like to read …

Dear Kettle fans,

A few weeks ago, when I was stuck in the US after the MySQL User Conference, a new book was published by Packt Publishing.

That all by itself is something that is not too remarkable.  However, this time it’s a book about my brainchild Kettle. That makes this book very special to me. The full title is Pentaho 3.2 Data Integration : Beginner’s Guide (Amazon, Packt).  The title all by itself explains the purpose of this book: give the reader a quick-start when it comes to Pentaho Data Integration (Kettle).

The author María Carina Roldán ( …

As requested by a few fans out there, here are the slides of my presentation:

Pentaho Data Integration 4.0 and MySQL.pdf

I had a great time at the conference, met a lot of nice folks, friends, customers, partners and colleagues. After the conference I was unable to get back home like so many of you because of the Paul Simon singing Eyjafjallajökul volcano in Iceland.

So I ended up flying over to Orlando for a week of brutal PDI 4.0 RC1 hacking with the rest of the l33t super Pentaho development team.  However, after 2+ weeks from home, even a severe storm …