gemini-code-assist[bot] commented on PR #37705: URL: https://github.com/apache/beam/pull/37705#issuecomment-3955637317
## Summary of Changes Hello @junaiddshaukat, I'm Gemini Code Assist[^1]! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request significantly enhances the performance of Kafka IO readers by addressing and removing two sources of unnecessary CPU overhead. By replacing an expensive timer mechanism with a more efficient alternative and eliminating redundant custom RPC latency metrics, the Kafka consumer's `poll()` loop now executes with reduced latency, especially when processing pre-fetched records. This change streamlines the data ingestion process from Kafka, leading to more efficient resource utilization. ### Highlights * **Performance Optimization in Kafka IO**: Removed the computationally expensive Guava `Stopwatch` from the critical `consumer.poll()` loop in Kafka IO readers (`ReadFromKafkaDoFn` and `KafkaUnboundedReader`). * **Replaced Stopwatch with System.currentTimeMillis()**: Switched from `Stopwatch` (which relies on `System.nanoTime()`) to a more lightweight `System.currentTimeMillis()` for tracking `remainingTimeout`, significantly reducing CPU overhead during rapid Kafka record prefetching. * **Removed Redundant RPC Latency Metrics**: Eliminated custom Beam RPC latency metric tracking and associated histograms (`KafkaMetrics`, `KafkaSinkMetrics`) as Kafka natively provides this data via JMX (`fetch-latency-avg`), making the custom implementation redundant and a source of performance overhead. * **Cleaned Up Metric Code and Tests**: Removed dead code related to RPC latency metrics from `KafkaMetrics.java` and `KafkaSinkMetrics.java`, and updated corresponding test files (`KafkaMetricsTest.java`, `KafkaSinkMetricsTest.java`) to reflect these changes. 🧠**New Feature in Public Preview:** You can now enable **Memory** to help **Gemini Code Assist** learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. **Click [here](https://codeassist.google/code-review/login) to enable Memory in your admin console.** <details> <summary><b>Changelog</b></summary> * **sdks/java/io/kafka/src/main/java/org/apache/beam/sdk/io/kafka/KafkaMetrics.java** * Removed `updateSuccessfulRpcMetrics` method signature from the interface. * Removed `updateSuccessfulRpcMetrics` implementation from `NoOpKafkaMetrics`. * Removed `LATENCY_HISTOGRAMS` map and `perTopicRpcLatencies` abstract method. * Adjusted `create` method in `KafkaMetricsImpl` to no longer initialize `perTopicRpcLatencies`. * Removed the `updateSuccessfulRpcMetrics` method implementation from `KafkaMetricsImpl`. * Removed the `recordRpcLatencyMetrics` method. * Removed the call to `recordRpcLatencyMetrics` from `flushBufferedMetrics`. * **sdks/java/io/kafka/src/main/java/org/apache/beam/sdk/io/kafka/KafkaSinkMetrics.java** * Removed imports for `DelegatingHistogram`, `Histogram`, and `HistogramData`. * Removed `RPC_LATENCY` constant. * Removed `RpcMethod` enum. * Removed `RPC_METHOD` metric label. * Removed the `createRPCLatencyHistogram` method. * **sdks/java/io/kafka/src/main/java/org/apache/beam/sdk/io/kafka/KafkaUnboundedReader.java** * Removed import for `Stopwatch`. * Removed the `stopwatch` instance variable. * Removed `stopwatch.start()`, `stopwatch.stop()`, and `kafkaResults.updateSuccessfulRpcMetrics` calls from the `consumerPollLoop` method. * **sdks/java/io/kafka/src/main/java/org/apache/beam/sdk/io/kafka/ReadFromKafkaDoFn.java** * Removed import for `Stopwatch`. * Removed `pollTimer` (Stopwatch) initialization. * Replaced `pollTimer.reset().start()` with `System.currentTimeMillis()` for `startMillis`. * Replaced `pollTimer.elapsed()` with `Duration.ofMillis(System.currentTimeMillis() - startMillis)` for `elapsed` calculation. * Removed `kafkaMetrics.updateSuccessfulRpcMetrics` call. * **sdks/java/io/kafka/src/test/java/org/apache/beam/sdk/io/kafka/KafkaMetricsTest.java** * Removed import for `containsInAnyOrder`. * Removed import for `Duration`. * Removed `results.updateSuccessfulRpcMetrics` call from `testNoOpKafkaMetrics`. * Renamed `testKafkaRPCLatencyMetrics` to `testKafkaBacklogMetrics`. * Removed all assertions related to RPC latency histograms from `testKafkaBacklogMetrics`. * Removed the `testKafkaRPCLatencyMetricsAreNotRecorded` test method. * **sdks/java/io/kafka/src/test/java/org/apache/beam/sdk/io/kafka/KafkaSinkMetricsTest.java** * Removed import for `Histogram`. * Removed the `testCreatingHistogram` method. </details> <details> <summary><b>Activity</b></summary> * The code compiled successfully. * The full Kafka IO test suite was run and passed. * The timeout logic in the poll loop was verified to function correctly using `java.time.Duration` and `System.currentTimeMillis()`. </details> <details> <summary><b>Using Gemini Code Assist</b></summary> <br> The full guide for Gemini Code Assist can be found on our [documentation page](https://developers.google.com/gemini-code-assist/docs/review-github-code), here are some quick tips. <b>Invoking Gemini</b> You can request assistance from Gemini at any point by creating a comment using either `/gemini <command>` or `@gemini-code-assist <command>`. 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