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Posted to issues@flink.apache.org by GitBox <gi...@apache.org> on 2020/04/14 06:24:19 UTC

[GitHub] [flink] curcur opened a new pull request #11725: [FLINK-15670] Provide a Kafka Source/Sink pair as KafkaShuffle

curcur opened a new pull request #11725: [FLINK-15670] Provide a Kafka Source/Sink pair as KafkaShuffle
URL: https://github.com/apache/flink/pull/11725

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## What is the purpose of the change

This pull request is to provide a Kafka Source/Sink pair to simulate a KafkaShuffle that can:
1. Read topics that are already partitioned by key and process them without partitioning them again (avoid shuffles); and
2. Use this to decompose the job into smaller jobs and independent pipelined regions that failover independently.

## Brief Change Log
- Extend Datastream API to allow user-defined SinkFunction to manipulate watermark
- Kafka Shuffle Producer change
- Write timestamp and watermark information together with a record in Kafka
- Use `KeyGroupRangeAssignment` to assign records to different Kafka partitions
- Kafka Shuffle Consumer change, Kafka Fechter Change
- Each consumer read partitions equal to the key group indices that it got assigned. For now, the number of partitions is enforced to equal to the number of consumer parallelism.
- KafkaShuffleFechter encapsulates the logic of record emitting and watermark emitting.

## Verifying this change
This change added tests:
1. End-2-end tests
2. partition assignment tests

Some other tests are missing:
1. Specific watermark tests
2. failover tests

## Does this pull request potentially affect one of the following parts:
- Dependencies (does it add or upgrade a dependency): (no)
- The public API, i.e., is any changed class annotated with `@Public(Evolving)`: (yes)
- The serializers: (don't know)
- The runtime per-record code paths (performance sensitive): (no)
- Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn/Mesos, ZooKeeper: (no)
- The S3 file system connector: (no)

## Documentation

- Does this pull request introduce a new feature? (yes)
- If yes, how is the feature documented? (JavaDocs)

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