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Table of Contents

Status

Current state: Under Discussion Adopted (1.0)

Discussion thread: [DISCUS] KIP-182: Reduce Streams DSL overloads and allow easier use of custom storage engineshere [Change the link from the KIP proposal email archive to your own email thread]

JIRA: KAFKA-5651 

Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).

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Code Block
languagejava
titleKGroupedStream
<W extends Window> WindowedKStream<KTimeWindowedKStream<K, V> windowedBy(Windows<W> timeWindows);

SessionWindowedKStream<K, V> windowedBy(SessionWindows sessionWindows);

KTable<K, Long> count(final Materialized<K, Long> materialized);

KTable<K, V> reduce(final Reducer<V> reducer, final Materialized<K, V, KeyValueStore<Bytes, byte[]>> materialized);

<VR> KTable<K, VR> aggregate(final Initializer<VR> initializer,
                             final Aggregator<? super K, ? super V, VR> aggregator,
                             final Materialized<K, VR, KeyValueStore<Bytes, byte[]>> materialized);

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Code Block
languagejava
titleWindowedKStream
public interface WindowedKStream<KTimeWindowedKStream<K, V> {

    KTable<Windowed<K>, Long> count();

    KTable<Windowed<K>, Long> count(final Materialized<K, Long, WindowStore<Bytes, byte[]>> materializedAs);

    <VR> KTable<Windowed<K>, VR> aggregate(final Initializer<VR> initializer,
                                           final Aggregator<? super K, ? super V, VR> aggregator);

    <VR> KTable<Windowed<K>, VR> aggregate(final Initializer<VR> initializer,
                                           final Aggregator<? super K, ? super V, VR> aggregator,
                                           final Materialized<K, VR, WindowStore<Bytes, byte[]>> materializedAs);


    KTable<Windowed<K>, V> reduce(final Reducer<V> reducer);

    KTable<Windowed<K>, V> reduce(final Reducer<V> reducer,
                                  final Materialized<K, V, WindowStore<Bytes, byte[]>> materializedAs);


} 

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