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 Dear Kettle enthusiasts, this is just a short blog post to point out that there are some new development resources available: Pentaho has added several sample plugins for PDI to the public CI-Server. If you ever wondered how to create your own plugins for PDI, check out the samples! . . . → Read More: Exploring the sample plugins for PDI  In this post I would like to announce the release of the Edi2Xml PDI plugin. It will convert a string field with edifact data to an XML text, with one tag per segment, containing the fields and values as child tags. This makes the edifact data more accessible, as the XML can be queried using the . . . → Read More: Releasing Edi2Xml plugin for PDI  This article introduces clustering concepts supported by Kettle a.k.a. PDI. If you need to replicate data to several physical databases, or would like to learn about scale-out options for record processing, this article may be for you. As usual, the downloads section has the demo transformations for this article. . . . → Read More: Clustering in Kettle  This article introduces partitioning concepts supported by Kettle a.k.a. PDI. If you need to partition records over several tables, or would like to learn about increasing the parallelism of your transformations, this article may be for you. . . . → Read More: Partitioning in Kettle  Regular expressions are a very useful tool for a variety of string related tasks. In Kettle they are frequently used for extraction and manipulation tasks, as well as for specifying groups of file names. This post gives an introduction to regular expressions in general as well as some applications within Kettle a.k.a. PDI. Since the built-in . . . → Read More: An Introduction to Regular Expressions  Anybody who finds themselves working on a client’s environment will usually face the fact that access to databases is restricted to what’s absolutely required to get the job done. The source files and target systems will be available, but creating helper tables or databases may be completely out of the question, or it may involve overcoming . . . → Read More: Using an on-demand in-memory SQL database in PDI  ETL processes sometimes need to generate data, even if there’s no input. This may be a bit puzzling at times, since an usual ETL row stream produces nothing if there’s no input. In some scenarios an ETL process is supposed to generate some sort of aggregation, which implies it should report a value of 0 even . . . → Read More: Processing the void – detecting and handling empty row streams in PDI  Tracking the progress of a transformation in PDI Spoon usually involves closely observing the numbers displayed in the step metrics tab. The step metrics tab dispays information about each step’s processed rows and input/output buffers, which makes it an important tool for understanding step performance at a glance as well as understanding the progress of a . . . → Read More: Tracking Transformation Progress becomes easier in PDI  The Excel Writer plugin offers support for Excel template files that can be filled in a variety of ways using Kettle a.k.a. PDI. In this post I would like to show how to fill an Excel report template file that has pre-styled cells, formulas and charts on different sheets. The entire report is filled within a . . . → Read More: Using the Excel Writer Step  Every now and then a field pops up that has comma-separated values in it. It is often used when it seems less convenient to properly model a 1:n relationship. In most cases the field contains a set of IDs or some subset of a fixed set of values. Working with these fields can be tricky. This post shows how to access individual values of comma separated fields in Kettle a.k.a. PDI without resorting to custom parsing with JavaScript or Java code. It also shows how to effectively create those fields, should you ever need to. Continue reading Dealing with comma separated fields in Kettle |
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