Zhuoxi2000 opened a new pull request, #290:
URL: https://github.com/apache/flink-connector-kafka/pull/290

   ## What is the purpose of the change
   
   Fixes [FLINK-36434](https://issues.apache.org/jira/browse/FLINK-36434): the 
`KafkaPartitionSplitReader` is constructed on the source-reader thread — or, 
when `KafkaSourceFetcherManager#commitOffsets` re-creates a fetcher after an 
idle shutdown, on the checkpoint thread — and its constructor eagerly created 
the `KafkaConsumer` (and registered consumer metrics) there. The consumer is 
then used almost exclusively on the split fetcher thread, but `KafkaConsumer` 
is not thread-safe; as described in the ticket, this broken threading model 
blocks Kafka client upgrades (sporadic `CorrelationIdMismatchException`).
   
   This PR makes the consumer lazy inside the reader, so it is created on the 
first consumer-touching call — which by construction happens on the split 
fetcher thread (`fetch`, `handleSplitsChanges`, `pauseOrResumeSplits`, the 
offset-commit task, and `close()` in the fetcher's shutdown path all run 
there). Design points, as discussed on the ticket:
   
   - The constructor only computes `consumerProps` (client-id derivation 
unchanged) and stores them; no consumer, no metric registration.
   - A private `ensureConsumer()` runs at the entry of every consumer-touching 
method; consumer metric registration moves there as well.
   - `wakeUp()` remains the only cross-thread entry point (the one call 
`KafkaConsumer` documents as thread-safe). `wakeUp()` and creation synchronize 
on a small lock: if the consumer does not exist yet, the wakeup is recorded and 
applied right after creation, so the first blocking call still observes it — 
matching the semantics of a wakeup against an eagerly-created consumer. The 
worst case is one spurious `WakeupException` on the first consumer call, which 
the existing `retryOnWakeup` handling already tolerates.
   - `close()` before first use is a no-op.
   
   `KafkaPartitionSplitReaderWrapper` (DynamicKafkaSource) subclasses this 
reader and only wraps `fetch()` output, so the fix covers the 
`DynamicKafkaSource` path as well.
   
   Deferring `splitReaderFactory.get()` itself onto the fetcher thread in 
flink-connector-base would fix this class of issue for all connectors; with the 
lazy consumer this connector no longer depends on that, so I will file it as a 
separate ticket (as discussed on FLINK-36434, it is orthogonal).
   
   ## Brief change log
   
     - `KafkaPartitionSplitReader` no longer creates the `KafkaConsumer` (nor 
registers consumer metrics) in its constructor; both happen in a new 
`ensureConsumer()` on the first consumer-touching call, i.e. on the split 
fetcher thread
     - `wakeUp()` before the consumer exists records a pending wakeup that is 
applied immediately after creation; `close()` before first use is a no-op
     - A protected `@VisibleForTesting createConsumer(Properties)` seam allows 
tests to observe consumer creation
   
   ## Verifying this change
   
   Please make sure both new and modified tests in this PR follow [the 
conventions for tests defined in our code quality 
guide](https://flink.apache.org/how-to-contribute/code-style-and-quality-common/#7-testing).
   
   This change added tests and can be verified as follows:
   
     - Added `KafkaPartitionSplitReaderConsumerThreadTest` (pure unit tests, no 
Kafka cluster needed): the consumer is not created at construction time and is 
created on the thread that first uses the reader; a `wakeUp()` arriving before 
creation is applied on creation exactly once; a `wakeUp()` after creation 
delegates directly; `close()` without prior use never creates a consumer
     - Existing `KafkaPartitionSplitReaderTest` covers the eager-path behaviors 
against a real cluster and passes unchanged in CI (not run locally: no Docker 
environment on this machine); `mvn test` for the module (compilation, 
checkstyle, spotless, and the new tests) passes locally
   
   ## 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)`: (no — `KafkaPartitionSplitReader` is `@Internal`)
     - The serializers: (no)
     - The runtime per-record code paths (performance sensitive): (no — 
`fetch()` gains a single volatile read on its fast path; consumer creation is 
one-time)
     - Anything that affects deployment or recovery: JobManager (and its 
components), Checkpointing, Kubernetes/Yarn, ZooKeeper: (no)
     - The S3 file system connector: (no)
   
   ## Documentation
   
     - Does this pull request introduce a new feature? (no)
     - If yes, how is the feature documented? (not applicable)
   
   ---
   
   ##### Was generative AI tooling used to co-author this PR?
   
   - [X] Yes (please specify the tool below)
   
   Claude Code


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