Hi Yassine,
Could you just remove the window and the apply, and just put a print() after
the:
> .assignTimestampsAndWatermarks(new AscendingTimestampExtractor<Request>() {
> @Override
> public long extractAscendingTimestamp(Request req) {
> return req.ts;
> }
> })
This at least will tell us if reading from Kafka works as expected.
Kostas
> On Jul 25, 2016, at 3:39 PM, Yassin Marzouki <[email protected]> wrote:
>
> Hi everyone,
>
> I am reading messages from a Kafka topic with 2 partitions and using event
> time. This is my code:
>
> .assignTimestampsAndWatermarks(new AscendingTimestampExtractor<Request>() {
> @Override
> public long extractAscendingTimestamp(Request req) {
> return req.ts;
> }
> })
> .windowAll(TumblingEventTimeWindows.of(Time.days(1)))
> .apply((TimeWindow window, Iterable<Request> iterable, Collector<String>
> collector) -> {
> collector.collect("Window: " + window.toString());
> for (Request req : iterable) {
> collector.collect(req.toString());
> }
> })
> .print()
>
> I could get an output only when setting the kafka source parallelism to 1. I
> guess that is because messages from multiple partitions arrive out-of-order
> to the timestamp exctractor according to this thread
> <http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Kafka-partition-alignment-for-event-time-td4782.html#a4804>,
> correct?
> So I replaced the AscendingTimestampExtractor with a
> BoundedOutOfOrdernessGenerator as in the documentation example
> <https://ci.apache.org/projects/flink/flink-docs-master/apis/streaming/event_timestamps_watermarks.html#tab_java_3>
> (with a higher delay) in order to handle out-of-order events, but I still
> can't get any output. Why is that?
>
> Best,
> Yassine
>
