how to apply window with KStreams {use case with java}












0















KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));


I want to apply window on demoZone of 1 minutes and find average of that 1 min data






apache-kafka apache-kafka-streams







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  • KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));

    – Prince
    Nov 22 '18 at 7:49
















0















KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));


I want to apply window on demoZone of 1 minutes and find average of that 1 min data






apache-kafka apache-kafka-streams







share|improve this question

























  • KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));

    – Prince
    Nov 22 '18 at 7:49














0












0








0








KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));


I want to apply window on demoZone of 1 minutes and find average of that 1 min data






apache-kafka apache-kafka-streams







share|improve this question
















KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));


I want to apply window on demoZone of 1 minutes and find average of that 1 min data






apache-kafka apache-kafka-streams




apache-kafka apache-kafka-streams






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 22 '18 at 8:20









Ahmed Ashour

3,572102642




3,572102642










asked Nov 22 '18 at 7:48









Prince Prince

33




33













  • KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));

    – Prince
    Nov 22 '18 at 7:49



















  • KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));

    – Prince
    Nov 22 '18 at 7:49

















KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));

– Prince
Nov 22 '18 at 7:49





KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));

– Prince
Nov 22 '18 at 7:49












1 Answer
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oldest

votes


















1














You can use TimeWindow as given below : 



KTable<Windowed<String>, Long> averageCount = demoZone

        .groupByKey(Serialized.with(Serdes.String(), dummySerde()))

        .windowedBy(TimeWindows.of(TimeUnit.MINUTES.toMillis(5).advanceBy(TimeUnit.MINUTES.toMillis(1))))

        .reduce(// Your aggregate logic here);


You can find more details about Windowing here :
https://docs.confluent.io/current/streams/developer-guide/dsl-api.html#windowing






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  • thanks it's working .....

    – Prince
    Nov 22 '18 at 9:17











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1 Answer
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1 Answer
1






active

oldest

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active

oldest

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1














You can use TimeWindow as given below : 



KTable<Windowed<String>, Long> averageCount = demoZone

        .groupByKey(Serialized.with(Serdes.String(), dummySerde()))

        .windowedBy(TimeWindows.of(TimeUnit.MINUTES.toMillis(5).advanceBy(TimeUnit.MINUTES.toMillis(1))))

        .reduce(// Your aggregate logic here);


You can find more details about Windowing here :
https://docs.confluent.io/current/streams/developer-guide/dsl-api.html#windowing






share|improve this answer
























  • thanks it's working .....

    – Prince
    Nov 22 '18 at 9:17
















1














You can use TimeWindow as given below : 



KTable<Windowed<String>, Long> averageCount = demoZone

        .groupByKey(Serialized.with(Serdes.String(), dummySerde()))

        .windowedBy(TimeWindows.of(TimeUnit.MINUTES.toMillis(5).advanceBy(TimeUnit.MINUTES.toMillis(1))))

        .reduce(// Your aggregate logic here);


You can find more details about Windowing here :
https://docs.confluent.io/current/streams/developer-guide/dsl-api.html#windowing






share|improve this answer
























  • thanks it's working .....

    – Prince
    Nov 22 '18 at 9:17














1












1








1







You can use TimeWindow as given below : 



KTable<Windowed<String>, Long> averageCount = demoZone

        .groupByKey(Serialized.with(Serdes.String(), dummySerde()))

        .windowedBy(TimeWindows.of(TimeUnit.MINUTES.toMillis(5).advanceBy(TimeUnit.MINUTES.toMillis(1))))

        .reduce(// Your aggregate logic here);


You can find more details about Windowing here :
https://docs.confluent.io/current/streams/developer-guide/dsl-api.html#windowing






share|improve this answer













You can use TimeWindow as given below : 



KTable<Windowed<String>, Long> averageCount = demoZone

        .groupByKey(Serialized.with(Serdes.String(), dummySerde()))

        .windowedBy(TimeWindows.of(TimeUnit.MINUTES.toMillis(5).advanceBy(TimeUnit.MINUTES.toMillis(1))))

        .reduce(// Your aggregate logic here);


You can find more details about Windowing here :
https://docs.confluent.io/current/streams/developer-guide/dsl-api.html#windowing







share|improve this answer












share|improve this answer



share|improve this answer










answered Nov 22 '18 at 8:29









Nishu TayalNishu Tayal

12.6k73482




12.6k73482













  • thanks it's working .....

    – Prince
    Nov 22 '18 at 9:17



















  • thanks it's working .....

    – Prince
    Nov 22 '18 at 9:17

















thanks it's working .....

– Prince
Nov 22 '18 at 9:17





thanks it's working .....

– Prince
Nov 22 '18 at 9:17




















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