You can try to convert the final resultant stream to table.
Check this page for more info:
https://docs.confluent.io/current/streams/faq.html#how-can-i-convert-a-kstream-to-a-ktable-without-an-aggregation-step
This way table would always contain the latest (single) record for a given
key.
Sachin
On Tue, Jan 14, 2020 at 10:11 PM Viktor Markvardt <
viktor.markva...@gmail.com> wrote:
> Hi,
>
> My name is Viktor. I'm currently working with Kafka streams and have
> several questions about Kafka and I can not find answers in the official
> docs.
>
> 1. Why suppress functionality does not work with Hopping windows? How to
> make it work?
>
> Example of the code:
>
> KStream finalStream = source
> .groupByKey()
>
>
> .windowedBy(TimeWindows.of(Duration.ofSeconds(30)).advanceBy(Duration.ofSeconds(10)))
> .reduce((aggValue, newValue) -> newValue,
> Materialized.with(Serdes.String(), Serdes.String()))
>
>
> .suppress(Suppressed.untilWindowCloses(Suppressed.BufferConfig.unbounded()))
> .toStream();
>
> finalStream.print(Printed.toSysOut());
> finalStream.to(outputTopic);
>
> After I run the code above - output stream is empty. There were no
> errors/exceptions.
> NOTE: With Tumbling Window the code working as expected.
> Maybe I simply use it incorrectly?
>
> 2. Why with Hopping windows (without suppress) there are duplicates in the
> output stream?
> E.g., I send one record in the input kstream with Hopping window
> (duration=30s, advanceBy=2s) but get two same records (duplicate) in the
> output kstream.
> Is that an expected behavior? If so, how can I filter/switch off these
> duplicates?
>
> 3. Mainly I'm trying to solve this problem:
> I have kstream with events inside and events can be repeated (duplicates).
> In the output kstream I would like to receive only unique events for the
> last 24 hours (window duration) with 1 hour window overlay (window
> advanceBy).
> Could you recommend me any examples of code or docs please?
> I have already read official docs and examples but it was not enough to get
> full understanding of how I can achieve this.
>
> Best regards,
> Viktor Markvardt
>
