[rules-users] Performance of JBoss Rules

[Mark Proctor]

Dandrea,

I believe that MVEL has just got stable for JDK1.4 so we should be doing 
an M1 release which is much much much faster than 3.0.x - it should be 
backards compatible, any chance you could re-run those tests when M1 is out?

Thanks

Mark
Dandrea Francesco wrote:
> Hi all,
> I have to evaluate if JBoss Rules is a viable solution in this scenario:
> We have to monitor a large network using performance alarms. These 
> alarms arrive every 15 minutes. We don't know the real rate, but peaks 
> of many tens of thousands of alarms every 15 minutes must be managed 
> in a timely way.
> We want to use JBoss Rules to correlate these alarms, in order to show 
> less higher level  alarms to the users .
> We have basically 2 use cases:
> 1) I have to correlate the alarms on a single node of the network. 
> (for example in node A I have 2 alarms of different severity about the 
> connection with node B, so I aggregate everything in a third alarm 
> saying "I cannot connect to node B from node A"). In this scenario I 
> have many workingMemories (one for each node) and not so many facts 
> for each working memory. The performance of JBossRules is very very 
> good (almost linear with the number of nodes)
> 2) I have to correlate alarms among the nodes. (for example all nodes 
> connecting with a node A have an alarm "I cannot connect to node A 
> from node ...", I want to create an alarm "The node A is unreachable").
> In this scenario I'm very worried about the performance of JBoss 
> Rules, as I prepared a test case (in attachment) and I inferred that 
> the growth is highly non linear on the number of the facts. Is this 
> performance data wrong? Am I doing something stupid? Can someone comment?
>  
> Here are the numbers (The numbers are not so important, but rate they 
> grows is)
>  
> *Number of Facts* 	*Time to assert alla the new allarms (seconds)* 
> *Time to modify the alarms to close them (seconds)* 	*Total*
> 1000 	1.735 	0.969 	2.704
> 2000 	5.875 	3.000 	8.875
> 3000 	12.281 	6.406 	18.687
> 4000 	23.672 	11.672 	35.344
> 6000 	52.282 	23.250 	75.532
> 8000 	87.188 	42.532 	129.720
> 12000 	200.767 	94.642 	295.409
> 16000 	360.909 	176.579 	537.488
> 20000 	518.019 	263.158 	781.177
>
>  
> Or in a graph:
>  
>  
> Thanks a lot for your interest.
>  
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