Query with Siddhi CEP using two times windows and 2 streams (continued)

Question

I keep trying to make complex correlations with Siddhi, on this occasion I have two input streams, web client consult and notices sent to clients visits, I want to generate an alert if the first stream for each client is repeated more than once as long as the second stream not It has occurred under two windows and depends of the status of this events.

define stream consults (idClient string,dniClient string,codProduct string,codSubProduct string,chanel string,time string )

define stream comercialActions(idClient string, idAccionComercial string,codProduct string,codSubProduct string,chanel string,time string,status string)

from consults[codProduct=='Fondos']#window.time(50 seconds) select idClient,codProduct, codSubProduct, chanel, time, count(idClient) as visitCount group by idClient insert into consultsAvg for current-events

from consultsAvg[visitCount==1] select idClient, '' as idAccionComercial,codProduct, codSubProduct ,chanel, time, 'temp' as status insert into comercialActions for all-events

from comercialActions[status=='temp' or status == 'Lanzada' ]#window.time(5 seconds) select idClient as idClient, codProduct, codSubProduct, chanel, status, count(idClient) as num_status group by idClient insert into acciones_generadas for all-events

from comercialActions[status=='temp' or status=='Aceptada' or status =='Rechazada'or status=='Caduca']#window.time(3 seconds) select idClient as idClient, codProduct, codSubProduct, chanel, status,  count(idClient) as num_status group by idClient insert into acciones_realizadas for all-events

from consultsAvg[visitCount>=2]#window.time(50 seconds) as c join acciones_realizadas[num_status>=1]#window.time(5 seconds) as ag on c.idClient == ag.idClient and c.codProduct==ag.codProduct select c.idClient,c.codProduct,c.codSubProduct,c.chanel, c.time, count(c.idClient) as conteo insert into posible_ac for all-events

from posible_ac#window.time(5 seconds) as pac  join acciones_generadas[num_status>=1]#window.time(1 seconds) as ar on pac.idClient == ar.idClient select pac.idClient,pac.codProduct,pac.codSubProduct,pac.chanel,pac.time,conteo, count(ar.idClient) as conteo2  insert into enviar_Ac

from enviar_Ac[conteo==1 and conteo2==1] select idClient, codProduct,codSubProduct, chanel, time insert into generar_accion_comercial

What I try to do is use intermediate streams to count the number of website hits when this is greater than or equal to 2 , I see if it has already made a commercial action for that customer through various joins... I think I 've become very complicated and do not know if there would be a simpler solution ??? , considering it does not have the function Siddhi NOT Happened nor other join ( left join )

Rajeev Sampath · Answer 1 · 2015-07-14T01:16:10.923

You can accomplish this with a pattern. In this case i assume that we have to wait for 1 minute for an event from the second stream and if there's none, and more than 1 event from the first, we are going to emit an output.

from consults#window.time(1 minute)
select idClient, count(idClient) as idCount, <select more attributes here>
insert into expiredConsultsStream for expired-events;

from expiredConsultsStream[idCount > 1]
select *
insert into filteredConsultsStream;

from firstEvent = consults -> 
nonOccurringEvent = commercialActions[firstEvent.idClient == idClient] 
or
triggerEvent = filteredConsultsStream[firstEvent.idClient == idClient]
select firstEvent.idClient as id, triggerEvent.idCount as idCount, nonOccurringEvent.idClient as nid
having( not (nid instanceof string))
insert into alertStream;

These are draft queries, so may require some modifications to get them working. The filteredConsultsStream contains consult events with more than 1 occurrence within the last minute. In the last query we get the or of the conditions as: nonOccurringEvent = commercialActions[firstEvent.idClient == idClient] or triggerEvent = filteredConsultsStream[firstEvent.idClient == idClient]

So the query will be triggered by one of those above occurrences. But, then we need to find whether the condition is triggered by commercialActions. For that we use the 'having' clause and check whether the id is null (id is null implies that the event is null, the non-occurrence). Finally we emit the output.

You can find a better description for a somewhat similar query here (that is new 4.0.0 version btw and there are small syntax changes)

Query with Siddhi CEP using two times windows and 2 streams (continued)

1 Answers1