boy397 opened a new pull request, #39136:
URL: https://github.com/apache/beam/pull/39136
- Registered GroupByKey in KafkaStreamsPipelineTranslator.
- Created GroupByKeyTranslator to repartition via internal topic and route
into the GroupByKeyProcessor.
- Added GroupByKeyProcessor using Kafka Streams state stores to buffer the
global window KV elements.
- Added GroupByKeyTranslatorTest to verify execution via TopologyTestDriver.
**Please** add a meaningful description for your change here
Description:
Implement PTransformTranslator.
Translate the beam:transform:group_by_key:v1 primitive.
Set up a repartitioning step using Kafka Streams by setting the record key
to the extracted Beam GroupByKey key.
Route the data through an internal repartition topic using
KStreamsPayloadSerde from #39051.
Attach a key-value state store (via Stores.keyValueStoreBuilder) to buffer
the elements.
Implement a Kafka Streams Processor.
Buffer incoming WindowedValue<KV<K, V>> elements per key into the state
store.
Listen for watermark advancements (using the runner's watermark management).
When the watermark reaches TIMESTAMP_MAX (the end of GlobalWindow), retrieve
all buffered values for each key and emit KV<K, Iterable<V>> downstream.
Clear the state store for emitted keys.
Register GroupByKeyTranslator for beam:transform:group_by_key:v1 (known
URNs) alongside other primitives like Redistribute.
Set up a TopologyTestDriver E2E test.
Pipeline structure: Impulse -> produce mock KVs -> GroupByKey -> assert
grouped output matches the expected iterables.
Verify that elements are only emitted when the watermark reaches the end of
the global window.
Wire in the first @ValidatesRunner test on the GroupByKey category for the
global window.
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