[rules-users] Performance scaling with fact insertion

[zstlaw]

laune wrote
> 
> You realize that the modify negating part of the condition must result in
> an immediate retraction of the logical insertion?

Yes.  I did realize that the logical insert would retrigger.  sorry, I had
started with logical inserts without that clause.  I only added the negation
portion when I wrote the manual insert test (i didn't include the manual
retract logic in my post either).  Finally I changed to modify only approach
for a huge speedup. (Modify was initially the trivial case I posted but
later I used wrapper objects and was able to mirror the complexity of the
other approaches without a comparable slowdown.  I used the trivial modify
example since the final approach required a drastically different datamodel
and made the post rather long)


laune wrote
> During the runs: were there any other rules besides the one you have
> shown,
> especially rules with patterns using AnomalyFact or DataPoint?

My original rule file had many more rules but the numbers collected were for
performance testing with only a single rule once I identified that even the
simplest case was not scaling properly.  So yes the rule file was only a
single rule (plus an additional retraction rule for the non-logical insert
test) the rule while useless on its own proved sufficient to show that
scaling to millions of datapoints was impossible using logical insertions or
even manual insert/retract.  Luckily I was able to restructure my data to
use a modify based processing model but was dismayed that logical insert
suggestion that was documented as preferable scaled so poorly.  It made me
suspect that I was misusing some part of the system.

But the case is simple to test.  If performance is linear than doubling the
number of objects should result in double the time.  Anything worse is not
scalable for an extremely busy systems.  (thousands of points per second) My
post was largely to determine if others had also reproduced simular scaling
issues.  If so then we should modify the documentation to be more
appropriate in it's suggestions.  

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