XSLT

I had to transform some XML from one format to another recently for a cool thing that I am doing at the moment - more details soon with luck ;).

The XML in question was contained in a lot of files and I couldn't face editing them so I decided to embrace the power of XSLT and get the transformation done automatically using RapidMiner.

It turned out to be really quite easy and in the interests of giving something back I made a simple version of the process that shows it working.

Here is the process.

This is the input XML (a copy of the XML for a RapidMiner process as it happens)

 

Close examination shows it contains 5 operators.

The XSLT document input to the "Process XSLT" operator is shown below.

This finds all the operators with name attributes within the input XML and for each writes out the name and also finds and writes out the corresponding class attribute all within a new XML document.

The result of this is shown here.

It has correctly found the 5 operators in the original XML document and has written the name and class for each in a new XML document.

Very cool and powerful and it turned out to be quite easy. The hard bit is knowing how to create the XSLT transform.

Finding processes in the repository

I have a lot of processes and it's sometimes hard to remember the name of one containing something useful. A metadata view and search capability of the repository would be very useful.

While that is being invented, here's a process that scans through a repository and determines the name and location of the processes it finds. It also counts the number of operators used to give a sense of how big the process is. The process recursively scans files with extension ".rmp" from a starting folder. Various document operators including "extract information" and "cut documents" using Xpath are used to process the files and extract information from them. The "aggregate" operator is used to count operators.

One day I will make it into a report that can be viewed using RapidAnalytics.

Other data is also extracted and this could be used if desired.

The default location is the default Windows location of the samples processes; change this to the folder where your repository is.

Some gymnastics were required to get the loop files operator to work correctly. This seems to present zero sized directories when iterating so I was forced to use the "branch" operator to eliminate these. Pointing the loop files operator to the C:\ drive usually results in an error that I haven't got to the bottom of yet.

How to read a PMML file to determine the attributes shown on a decision tree

Here is a process to read a PMML file created by RapidMiner.

The PMML file in this case is a model created by running a decision tree algorithm on the iris data set. Here's a snapshot - the highlighted parts are to help explain later.

The process writes this to c:\temp\Iris.xml.pmml and then reads it back in (the subprocess operator allows this to be synchronised). The file is handled as a document by RapidMiner.

Next, the process uses the following XPath to split the document into chunks (the PMML is probably not required).

/xmlns:PMML//xmlns:SimplePredicate

The xmlns is a namespace and this is provided by the following name value pair in the "cut document" operator.

xmlns  http://www.dmg.org/PMML-3_1

This value is provided in the raw XML and it is important to get this correct. The "assume html" checkbox is unchecked.

The XPath itself simply finds all XML nodes somewhere beneath the PMML node that correspond to "SimplePredicate". By inspection of the PMML, this looked to be the correct way of determining the fields used on the decision tree.

The result of this XPath is to create multiple documents each containing a small section of the original document. Each section corresponds to the XML for a specific SimplePredicate entry.

Within the "cut document" operator, the inner operator extracts information using more XPath. This time, the XPath is looking for an attribute named "field" and the XPath to do this is as follows.

//@field

A namespace is not required here because it looks like the document fragments don't refer to one.

Next the process turns the documents into an example set and the number of rows in this corresponds to the number of times the SimplePredicate XPath query cut the file into smaller documents. The example set is returned and after some processing the final output is a list of the attributes used in the decision tree.

In the example, attributes a3 and a4 can be seen on the decision tree and these are also output as an example set.