Speed

[Jim Hurley]

I have a question about optimization.

I am helping a local candidate with their database. It is a large 
county election database which I have imported into a field within 
Rev.

This is a voter database in which we would like to identify a single 
addresses for all voters within a given households so that we do not 
have to send multiple letters to individual voters within the same 
household. This makes a big difference in mailing costs.

I found that my original program runs prohibitively slowly.

But I find when I break up the data into smaller blocks, things run 
much more rapidly. For example I use the following code:

   repeat with k = 0 to 8
     put line k*1000 to (k+1)*1000+1 of tField into temp
     put identifyUniqueAddresses(temp) into a[k]
   end repeat

so that the data in the variable tField is broken up into 9 chunks of 
1000 lines each. Later I reassemble the results from the array, a[k].

If instead I try to run the whole field at once using:

	identifyUniqueAddressess(tField)

I would have to wait all day for the data in tField to process.

(I have not found a was to use:

	repeat for each line tLine in tField

I have to be able to discover whether *successive* lines in the 
sorted data share the same address.)

Now I'm sure my handler, identifyUniqueAddresess, is not the most 
efficient code, but my question is this:  Why does the handler run so 
much more rapidly working on several smaller chunks which are later 
reassembled rather than all at once?

I suspect the problem may be successively pulling up lines of text 
from a very long list of lines. Would it help if I first put the 
lines into an array and then worked with the array?

Is there an optimizer out there? Gentlemen and gentle ladies, start 
your engines.



-- 
Jim Hurley
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