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I currently have a set of transformers in a workspace that are completing the task at hand and are performing well.

 

 

I started looking into using a Custom Transformer as a mechanism to encapsulate the functionality however the performance is significantly longer (killed after 15min, original workspace completed in 3.5sec).

 

 

Based on the logs it looks like the Custom Transformer is being invoked for each individual feature rather than the whole set; I also suspect I'll get the wrong answer without invoking the transformers as a group. Does anyone have any ideas on how to invoke the Custom Transformer with a set of features rather than individual ones? Am I approaching this incorrectly?

 

 

Thanks

 

David

 

 

Hi David,

 

 

It's difficult to guess a reason that just replacing a part of the workflow with a custom transformer causes such a large difference.

 

A possibility I can imagine: if you published an Attribute Name type parameter in the custom transformer, the issue might be concerned with the usage of the parameter. See these threads:

 

Should Attributes in Parameters be pointers?

 

http://fmepedia.safe.com/AnswersQuestionDetail?id=906a0000000ckr0AAA

 

Retrieving Parameter Attribute Values

 

http://fmepedia.safe.com/AnswersQuestionDetail?id=906a0000000cmROAAY

 

 

Takashi
Hi,

 

 

a custom transformer is in principle like any other transformer: it will be called once for every feature that enters it.

 

 

If you want to call it only once for the whole dataset, you will have to rethink your strategy / logic a little bit, but it is difficult to give specific advice without having the details of your process.

 

 

David

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