Yes, this should work.
On Tue, 10 May 2016 at 19:01 Srikanth <srikanth...@gmail.com> wrote:
> Yes, will work.
> I was trying another route of having a "finalize & purge trigger" that will
> i) onElement - Register for event time watermark but not alter nested
> trigger's TriggerResult
> ii) OnEventTime - Always purge after fire
>
> That will work with CountTrigger and other custom trigger too rt?
>
> public class FinalizePurgingTrigger <T, W extends Window> extends
> Trigger<T, W> {
>
> @Override
> public TriggerResult onElement(T element, long timestamp, W window,
> TriggerContext ctx) throws Exception {
> ctx.registerEventTimeTimer(window.getEnd)
> return nestedTrigger.onElement(element, timestamp, window, ctx);
> }
>
> @Override
> public TriggerResult onEventTime(long time, W window, TriggerContext ctx)
> throws Exception {
> TriggerResult triggerResult = nestedTrigger.onEventTime(time, window, ctx);
> switch (triggerResult) {
> case FIRE:
> return TriggerResult.FIRE_AND_PURGE;
> case FIRE_AND_PURGE:
> return TriggerResult.FIRE_AND_PURGE;
> default:
> return TriggerResult.CONTINUE;
> }
> }
> }
>
> Srikanth
>
> On Tue, May 10, 2016 at 11:36 AM, Fabian Hueske <fhue...@gmail.com> wrote:
>
>> Maybe the last example of this blog post is helpful [1].
>>
>> Best, Fabian
>>
>> [1]
>> https://www.mapr.com/blog/essential-guide-streaming-first-processing-apache-flink
>>
>> 2016-05-10 17:24 GMT+02:00 Srikanth <srikanth...@gmail.com>:
>>
>>> Hi,
>>>
>>> I read the following in Flink doc "We can explicitly specify a Trigger
>>> to overwrite the default Trigger provided by the WindowAssigner. Note that
>>> specifying a triggers does not add an additional trigger condition but
>>> replaces the current trigger."
>>> So, I tested out the below code with count trigger. As per my
>>> understanding this will override the default watermark based trigger.
>>>
>>> val testStream = env.fromCollection(List( ("2016-04-07 13:11:59",
>>> 157428, 4),
>>> ("2016-04-07 13:11:59", 157428, 4),
>>> ("2016-04-07 13:11:59", 111283, 23),
>>> ("2016-04-07 13:11:57", 108042, 23),
>>> ("2016-04-07 13:12:00", 161374, 9),
>>> ("2016-04-07 13:12:00", 161374, 9),
>>> ("2016-04-07 13:11:59", 136505, 4)
>>> )
>>> )
>>> .assignAscendingTimestamps(b => f.parse(b._1).getTime())
>>> .map(b => (b._3, b._2))
>>>
>>> testStream.print
>>>
>>> val countStream = testStream
>>> .keyBy(_._1)
>>> .timeWindow(Time.seconds(20))
>>> .trigger(CountTrigger.of(3))
>>> .fold((0, List[Int]())) { case((k,r),i) => (i._1, r ++ List(i._2)) }
>>>
>>> countStream.print
>>>
>>> Output I saw confirms the documented behavior. Processing is triggered
>>> only when we have 3 elements for a key.
>>> How do I force trigger the left over records when watermark is past the
>>> window? I.e, I want to use triggers to start early processing but finalize
>>> the window based on watermark.
>>>
>>> Output shows that records for keys 23 & 9 weren't processed.
>>> (4,157428)
>>> (4,157428)
>>> (23,111283)
>>> (23,108042)
>>> (9,161374)
>>> (9,161374)
>>> (4,136505)
>>>
>>> (4,List(157428, 157428, 136505))
>>>
>>> Thanks,
>>> Srikanth
>>>
>>
>>
>
