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

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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

edited Nov 22 at 8:20

Ahmed Ashour

3,510102442

asked Nov 22 at 7:48

Prince

KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));
– Prince
Nov 22 at 7:49

add a comment |

up vote
0
down vote

favorite

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

edited Nov 22 at 8:20

Ahmed Ashour

3,510102442

asked Nov 22 at 7:48

Prince

KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));
– Prince
Nov 22 at 7:49

add a comment |

up vote
0
down vote

favorite

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

edited Nov 22 at 8:20

Ahmed Ashour

3,510102442

asked Nov 22 at 7:48

Prince

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

edited Nov 22 at 8:20

Ahmed Ashour

3,510102442

asked Nov 22 at 7:48

Prince

edited Nov 22 at 8:20

Ahmed Ashour

3,510102442

asked Nov 22 at 7:48

Prince

edited Nov 22 at 8:20

Ahmed Ashour

3,510102442

edited Nov 22 at 8:20

Ahmed Ashour

3,510102442

edited Nov 22 at 8:20

Ahmed Ashour

3,510102442

asked Nov 22 at 7:48

Prince

asked Nov 22 at 7:48

Prince

asked Nov 22 at 7:48

Prince

KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));
– Prince
Nov 22 at 7:49

add a comment |

KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));
– Prince
Nov 22 at 7:49

KStream<String, dummy> demoZone = builder.stream(fromTopic, Consumed.with(Serializer.getSerde(String.class), Serializer.getSerde(dummy.class)));
– Prince
Nov 22 at 7:49

add a comment |

1 Answer
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1
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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

answered Nov 22 at 8:29

Nishu Tayal

11.2k73381

thanks it's working .....
– Prince
Nov 22 at 9:17

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

up vote
1
down vote

accepted

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

answered Nov 22 at 8:29

Nishu Tayal

11.2k73381

thanks it's working .....
– Prince
Nov 22 at 9:17

add a comment |

up vote
1
down vote

accepted

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

answered Nov 22 at 8:29

Nishu Tayal

11.2k73381

thanks it's working .....
– Prince
Nov 22 at 9:17

add a comment |

up vote
1
down vote

accepted

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

answered Nov 22 at 8:29

Nishu Tayal

11.2k73381

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

answered Nov 22 at 8:29

Nishu Tayal

11.2k73381

answered Nov 22 at 8:29

Nishu Tayal

11.2k73381

answered Nov 22 at 8:29

Nishu Tayal

11.2k73381

answered Nov 22 at 8:29

Nishu Tayal

11.2k73381

thanks it's working .....
– Prince
Nov 22 at 9:17

add a comment |

thanks it's working .....
– Prince
Nov 22 at 9:17

thanks it's working .....
– Prince
Nov 22 at 9:17

add a comment |

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