What do you guys think of this: my facts are all the same type, so I didn't have anything like a consumer object to break things down with. But what I did was:
 
rule "group 1"
when
  $a : Trans( $groupValue : prodCat, $date : date )
  not Trans( this != $a, prodCat == $groupValue, date < $date )
  $b : LinkedList( size >= 1 ) from collect ( Trans( this != $a, prodCat == $groupValue, date > $date ) )
then
  //do something
end
 
This is quite quick. The rule grabs all the Trans objects that have the same prodCat, in a single firing, without the need to iteractively retract things or fire multiple times for the same group value. As the first condition only matches a single fact (the one with the oldest date), there is only ever a single permutation that can fulfill the conditions.
 
This is only aggregating on a single attribute, but the principal should work with more.
 

 
On 18 October 2010 16:12, Wolfgang Laun <wolfgang.laun@gmail.com> wrote:
Doing s.th. like
  $t1 : Trans( $id : id, $pc : pc, $tt : tt )
  $t2 : Trans( this != $t1, id == $id, pc == $pc, tt < ($tt + 3600) )
is bound to produce poor performanc.

Divide and conquer!

You might start with a Consumer record
  Consumer( $id : id )
  $t1 : Trans( id == $id: , $pc : pc, $tt : tt )
  $t2 : Trans( this != $t1, id == $id, pc == $pc, tt < ($tt + 3600) )

You might run an (external) sort on the Transaction records and
process it in batches of identical id+pc.

If transaction times don't go around the clock, you might sort by
date, and process day by day.

You may have to create a Domain Specific Language for the
non-programmers, putting a firm rein on how they combine the basic
facts. Processing large batches is bound to require skills they just
dont have.

-W


On 18 October 2010 16:14, Greg Barton <greg_barton@yahoo.com> wrote:
> It would be nice if we had an example of some rules.  That way we can rule out obvious performance killers like cartesian products and multiple "from" clauses in one rule.
>
> GreG
>
> On Oct 18, 2010, at 5:19, Tim 4076 <tm4076@gmail.com> wrote:
>
> Hi,
> I'm trying to use drools to do grouping of data according to patterns defined in my rules, but I'm having issues creating something that works in a reasonable amount of time (seconds). I've tried all sorts of permutations without much luck and would like to hear how others would do the same thing.
>
> To give an example: I've got a big batch of transaction records and I want to aggregate all the records where the consumer id and product category are the same and the purchases were made within an hour of each other.
>
> The fact that its matching the same values between facts, rather than against constants seems to scupper it somewhat.
>
> I would go down the ETL route, but the idea is for non-techies to define their own aggregations using rules.
>
> -Cheers. Tim
>
>
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