[jira] [Updated] (FLINK-21317) Downstream keyed state not work after FlinkKafkaShuffle

["Yun Gao (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-21317?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Yun Gao updated FLINK-21317:
----------------------------
    Fix Version/s: 1.16.0

> Downstream keyed state not work after FlinkKafkaShuffle
> -------------------------------------------------------
>
>                 Key: FLINK-21317
>                 URL: https://issues.apache.org/jira/browse/FLINK-21317
>             Project: Flink
>          Issue Type: Bug
>          Components: Connectors / Kafka
>    Affects Versions: 1.13.0
>            Reporter: Kezhu Wang
>            Priority: Minor
>              Labels: auto-deprioritized-major
>             Fix For: 1.15.0, 1.16.0
>
>
> {{FlinkKafkaShuffle}} uses {{KeyGroupRangeAssignment.assignKeyToParallelOperator}} to assign partition records to kafka topic partition. The assignment works as follow:
>  # {{KeyGroupRangeAssignment.assignToKeyGroup(Object key, int maxParallelism)}} assigns key to key group.
>  # {{KeyGroupRangeAssignment.computeOperatorIndexForKeyGroup(int maxParallelism, int parallelism, int keyGroupId)}} assigns that key group to operator/subtask index.
> When kafka topic partitions are consumed, they are redistributed by {{KafkaTopicPartitionAssigner.assign(KafkaTopicPartition partition, int numParallelSubtasks)}}. I copied code of this redistribution here.
> {code:java}
> public class KafkaTopicPartitionAssigner {
>     public static int assign(KafkaTopicPartition partition, int numParallelSubtasks) {
>         int startIndex =
>                 ((partition.getTopic().hashCode() * 31) & 0x7FFFFFFF) % numParallelSubtasks;
>         // here, the assumption is that the id of Kafka partitions are always ascending
>         // starting from 0, and therefore can be used directly as the offset clockwise from the
>         // start index
>         return (startIndex + partition.getPartition()) % numParallelSubtasks;
>     }
> }
> {code}
> This partition redistribution breaks prerequisites for {{DataStreamUtils.reinterpretAsKeyedStream}}, that is key groups are messed up. The consequence is unusable keyed state. I list deepest stack trace captured here:
> {noformat}
> Caused by: java.lang.NullPointerException
> 	at org.apache.flink.runtime.state.heap.StateTable.transform(StateTable.java:205)
> 	at org.apache.flink.runtime.state.heap.HeapReducingState.add(HeapReducingState.java:100)
> {noformat}
> cc [~ym]  [~sewen] [~AHeise]  [~pnowojski]
> Below is my proposed changes:
> * Make assignment between partition and subtask customizable.
> * Provide a 0-based round-robin assignment. (This is making {{startIndex}} 0 in existing assignment algorithms.)
> I saw FLINK-8570, above changes could be helpful if we finally decide to deliver FLINK-8570.



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