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https://issues.apache.org/jira/browse/KAFKA-13261?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17424158#comment-17424158
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Tomas Forsman commented on KAFKA-13261:
---------------------------------------

[~vcrfxia] thank you so much for solving this issue, it has been very 
interesting to follow the progress and how the process works. Great job :)

I'm glad the integration test could be of use! If it cause no trouble, then it 
would be an honor to be added as contributor. 

> KTable to KTable foreign key join loose events when using several partitions
> ----------------------------------------------------------------------------
>
>                 Key: KAFKA-13261
>                 URL: https://issues.apache.org/jira/browse/KAFKA-13261
>             Project: Kafka
>          Issue Type: Bug
>          Components: streams
>    Affects Versions: 2.8.0, 2.7.1
>            Reporter: Tomas Forsman
>            Assignee: Victoria Xia
>            Priority: Major
>              Labels: kip
>             Fix For: 3.1.0
>
>         Attachments: KafkaTest.java
>
>
> KIP-775: 
> [https://cwiki.apache.org/confluence/display/KAFKA/KIP-775%3A+Custom+partitioners+in+foreign+key+joins]
>  
> Two incoming streams A and B. 
> Stream A uses a composite key [a, b]
> Stream B has key [b]
> Stream B has 4 partitions and steams A has 1 partition.
> What we try to do is repartition stream A to have 4 partitions too, then put 
> both A and B into KTable and do a foreign key join on from A to B
> When doing this, all messages does not end up in the output topic.
> Repartitioning both to only use 1 partition each solve the problem so it seem 
> like it has something to do with the foreign key join in combination with 
> several partitions. 
> One suspicion would be that it is not possible to define what partitioner to 
> use for the join.
> Any insight or help is greatly appreciated.
> *Example code of the problem*
> {code:java}
> static Topology createTopoology(){
>     var builder = new StreamsBuilder();
>     KTable<String, String> tableB = builder.table("B",  
> stringMaterialized("table.b"));
>     builder
>         .stream("A", Consumed.with(Serde.of(KeyA.class), 
> Serde.of(EventA.class)))
>         .repartition(repartitionTopicA())
>         .toTable(Named.as("table.a"), aMaterialized("table.a"))
>         .join(tableB, EventA::getKeyB, topicAandBeJoiner(), 
> Named.as("join.ab"), joinMaterialized("join.ab"))
>         .toStream()
>         .to("output", with(...));
>     return builder.build();
> }
> private static Materialized<KeyA, EventA> aMaterialized(String name) {
>   Materialized<KeyA, EventA, KeyValueStore<Bytes, byte[]>> table = 
> Materialized.as(name);
>   return 
> table.withKeySerde(Serde.of(KeyA.class)).withValueSerde(Serde.of(EventA.class));
> }
> private static Repartitioned<DriverPeriod, DriverCosts> repartitionTopicA() {
>     Repartitioned<DriverPeriod, DriverCosts> repartitioned = 
> Repartitioned.as("driverperiod");
>     return 
> repartitioned.withKeySerde(Serde.of(KeyA.class)).withValueSerde(Serde.of(EventA.class))
>         .withStreamPartitioner(topicAPartitioner())
>         .withNumberOfPartitions(4);
> }
> private static StreamPartitioner<DriverPeriod, DriverCosts> 
> topicAPartitioner() {
>     return (topic, key, value, numPartitions) -> 
> Math.abs(key.getKeyB().hashCode()) % numPartitions;
> }
> private static Materialized<KeyA, EventA, KeyValueStore<Bytes, byte[]>> 
> joinMaterialized(String name) {
>     Materialized<DriverPeriod, DriverCosts, KeyValueStore<Bytes, byte[]>> 
> table = Materialized.as(name);
>     return 
> table.withKeySerde(Serde.of(KeyA.class)).withValueSerde(Serde.of(EventA.class));
> }
> {code}



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