I would implement them directly in Flink/Flink table API. I don’t think Drools plays well in this distributed scenario. It expects a centralized rule store and evaluation .
> Am 23.06.2020 um 21:03 schrieb Jaswin Shah <jaswin.s...@outlook.com>: > > > Hi I am thinking of using some rule engine like DROOLS with flink to solve a > problem described below: > > I have stream of events coming from kafka topic and I want to analyze those > events based on some rules and give the results in results streams when rules > are satisfied. > > Now, I am able to solve the same problem with flink entirely but I need to > write hard coded conditions in flink for the rules and in future I want to > keep my flink job generic that if any rules are changed I should not need the > redeployment of flink job. > > Use case: > Consider there are events coming like A,B,C D....and those events are > denoting those entity A is down, B is down,C is down ...etc. > > Now, there are many rules like: > 1.A is actually down if A is down and there are 3 Bs for A are down...here A > entity can have B in event json so. > > 2. B IS ACTUALLY DOWN IF B IS DOWN AND 2As for B are not down. > > THOSE EVENTS FROM SAME MINUTE > > See the not condition here, so, here When I received event of B down the, I > will wait for buffer time say 1 min and after 1 min if I dont receive 2A down > events, I declare B as down in result stream. > > Here basically we check on events at some minute so, keyboard minute.==》very > imp > > I need a help on how can use DROOls engine to get those rules out from > business logic and also maintenaning maximum partitioning as I am able to do > it with static rules. > > Any help will be really appreciated. > > Thanks, > Jaswin > > > > > > Get Outlook for Android
