On Friday, August 29, 2003, at 12:55 AM, Geoff Canyon wrote:

On Thursday, August 28, 2003, at 10:52 PM, Mark Brownell wrote:

This Xtra was coded using C or C++ to add speed to string searches. It has a feature findAll() and creates an array in half the time as the transcript loop.

Just want to make sure I'm reading this right: you're saying that the native C routine is only twice as fast as the equivalent transcript routine?


regards,

Geoff Canyon

Yes. I might be able to speed the transcript parallel numerical array builder by converting it to a single loop process. The only reason I used the three loop system was that the textCruncher Xtra created the char location arrays in the first place. Director was very slow, in fact so slow that it wasn't practical. My tests using this PNLP technique show that it is just slightly faster than perl regEx in a head to head task in transcript. Like I said I think I can speed it up some. Here is another thing to consider. I tested the textCruncher Xtra on Mac 9.2 classic on my Mac 10; 900 MHz iBook. That means that the speed in classic mode was about 266 MHZ.


If I were to get what I'm really looking for it would be:

getPNLPelements(startTag, endTag, stringToSearch) used like this to get an array of elements from a structured document like XML:

put "<record" into tStartT
put "</record>" into tEndT
put getPNLPelements(tStartT, tEndT, stringToSearch) into myArray

used like this:
put myArray[1]
-- transactionNumber="1234567" firstname="Bob" lastname="Smith">item# abc123


where:
<record transactionNumber="1234567" firstname="Bob" lastname="Smith">item# abc123</record>
were used as the first instance.


If I had a fast native transcript capability that extracted the element information between a start tag and an end tag and placed all found instances in an array and did this faster than a transcript loop then I would really have what I wanted. I would settle for offsetAll() while waiting for any speed enhancement in the future. I once referred to this process as a pull parser.

Best regards,

Mark Brownell

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