je-ik commented on code in PR #38764: URL: https://github.com/apache/beam/pull/38764#discussion_r3366925412
########## runners/kafka-streams/src/main/java/org/apache/beam/runners/kafka/streams/translation/ExecutableStageTranslator.java: ########## @@ -0,0 +1,93 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.beam.runners.kafka.streams.translation; + +import java.io.IOException; +import org.apache.beam.model.pipeline.v1.RunnerApi; +import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.Iterables; +import org.apache.kafka.streams.Topology; + +/** + * Translates the {@code beam:runner:executable_stage:v1} URN. + * + * <p>Adds an {@link ExecutableStageProcessor} node to the topology, wired to the processor that + * produces the stage's input PCollection (resolved through {@link + * KafkaStreamsTranslationContext#getProcessorNameForPCollection}). The processor runs the fused + * user code in the SDK harness; its single output PCollection is registered so downstream + * translators can attach to this node. + * + * <p>Multi-output stages (additional outputs / side inputs / state / timers) are out of scope for + * this first version and are rejected so the limitation fails fast rather than silently dropping + * outputs. + */ +class ExecutableStageTranslator implements PTransformTranslator { + + @Override + public void translate( + String transformId, RunnerApi.Pipeline pipeline, KafkaStreamsTranslationContext context) { + RunnerApi.PTransform transform = pipeline.getComponents().getTransformsOrThrow(transformId); + + RunnerApi.ExecutableStagePayload stagePayload; + try { + stagePayload = RunnerApi.ExecutableStagePayload.parseFrom(transform.getSpec().getPayload()); + } catch (IOException e) { + throw new IllegalArgumentException( + "Failed to parse ExecutableStagePayload for transform " + transformId, e); + } + + // Fail fast on stage features that are not yet supported, so users get a clear message rather + // than a silent miss further down the harness/topology path. + if (stagePayload.getSideInputsCount() > 0) { + throw new UnsupportedOperationException( + "ExecutableStage " + + transformId + + " has side inputs; side inputs are not yet supported by the Kafka Streams runner."); + } + if (stagePayload.getUserStatesCount() > 0 || stagePayload.getTimersCount() > 0) { + throw new UnsupportedOperationException( + "ExecutableStage " + + transformId + + " uses user state or timers; stateful ParDo is not yet supported by the Kafka" + + " Streams runner."); + } + if (transform.getOutputsMap().size() > 1) { + throw new UnsupportedOperationException( Review Comment: Do we plan to support this in later stages? ########## runners/kafka-streams/src/main/java/org/apache/beam/runners/kafka/streams/translation/ExecutableStageProcessor.java: ########## @@ -0,0 +1,211 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.beam.runners.kafka.streams.translation; + +import java.util.Queue; +import java.util.concurrent.ConcurrentLinkedQueue; +import org.apache.beam.model.pipeline.v1.RunnerApi; +import org.apache.beam.runners.fnexecution.control.BundleProgressHandler; +import org.apache.beam.runners.fnexecution.control.ExecutableStageContext; +import org.apache.beam.runners.fnexecution.control.OutputReceiverFactory; +import org.apache.beam.runners.fnexecution.control.RemoteBundle; +import org.apache.beam.runners.fnexecution.control.StageBundleFactory; +import org.apache.beam.runners.fnexecution.provisioning.JobInfo; +import org.apache.beam.runners.fnexecution.state.StateRequestHandler; +import org.apache.beam.sdk.fn.data.FnDataReceiver; +import org.apache.beam.sdk.util.construction.graph.ExecutableStage; +import org.apache.beam.sdk.values.WindowedValue; +import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.Iterables; +import org.apache.kafka.streams.processor.api.Processor; +import org.apache.kafka.streams.processor.api.ProcessorContext; +import org.apache.kafka.streams.processor.api.Record; +import org.checkerframework.checker.nullness.qual.Nullable; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +/** + * Kafka Streams {@link Processor} that executes a fused {@link ExecutableStage} (stateless user + * code such as ParDo) in the Beam SDK harness over the Fn API. + * + * <p>For each {@link KStreamsPayload#isData() data} payload it unwraps the {@link WindowedValue} + * and feeds it to the harness through the stage's main input {@link FnDataReceiver}. Harness + * outputs are collected on the harness threads into {@link #pendingOutputs} and then flushed + * downstream on the Kafka Streams processing thread when the bundle closes — Kafka Streams' {@link + * ProcessorContext#forward} must only be called from the processing thread, so outputs are never + * forwarded directly from a harness callback. + * + * <p>A {@link KStreamsPayload#isWatermark() watermark} payload marks a bundle boundary: the open + * bundle (if any) is closed (flushing outputs), and the watermark is then forwarded downstream so + * that subsequent stages observe it after all data of the bundle. + * + * <p>This is the Kafka Streams analogue of Flink's {@code ExecutableStageDoFnOperator} and Spark's + * {@code SparkExecutableStageFunction}. State, timers, and side inputs are out of scope for this + * first version: the stage is executed with {@link StateRequestHandler#unsupported()} and no timer + * receivers. + */ +class ExecutableStageProcessor + implements Processor<byte[], KStreamsPayload<byte[]>, byte[], KStreamsPayload<byte[]>> { + + private static final Logger LOG = LoggerFactory.getLogger(ExecutableStageProcessor.class); + + private final RunnerApi.ExecutableStagePayload stagePayload; + private final JobInfo jobInfo; + + // pendingOutputs is enqueued by SDK harness threads (inside the OutputReceiverFactory callback) + // and drained by the Kafka Streams processing thread on bundle close; needs to be thread-safe. + private final Queue<WindowedValue<byte[]>> pendingOutputs = new ConcurrentLinkedQueue<>(); + + private @Nullable ProcessorContext<byte[], KStreamsPayload<byte[]>> context; + private @Nullable ExecutableStageContext stageContext; + private @Nullable StageBundleFactory stageBundleFactory; + private @Nullable RemoteBundle currentBundle; + + ExecutableStageProcessor(RunnerApi.ExecutableStagePayload stagePayload, JobInfo jobInfo) { + this.stagePayload = stagePayload; + this.jobInfo = jobInfo; + } + + @Override + public void init(ProcessorContext<byte[], KStreamsPayload<byte[]>> context) { + this.context = context; + ExecutableStage executableStage = ExecutableStage.fromPayload(stagePayload); + this.stageContext = KafkaStreamsExecutableStageContextFactory.getInstance().get(jobInfo); + this.stageBundleFactory = stageContext.getStageBundleFactory(executableStage); + } + + @Override + public void process(Record<byte[], KStreamsPayload<byte[]>> record) { + KStreamsPayload<byte[]> payload = record.value(); + if (payload.isWatermark()) { + // NOTE: flushing the bundle on every received watermark is provisional. Once the + // WatermarkManager lands, a stage will receive watermarks from multiple parent instances and + // the output watermark becomes min() across them — the bundle should flush / the output + // watermark advance only when that minimum actually moves forward, not on every received + // watermark. Tracked in #38743. + closeBundleAndFlush(record); + forwardWatermark(record, payload.getWatermarkMillis()); + return; + } + try { + ensureBundleOpen(); + mainInputReceiver().accept(payload.getData()); + } catch (Exception e) { + throw new RuntimeException("Failed to process element through SDK harness", e); + } + } + + private void ensureBundleOpen() throws Exception { + if (currentBundle != null) { + return; + } + StageBundleFactory factory = checkInitialized(stageBundleFactory); + OutputReceiverFactory outputReceiverFactory = + new OutputReceiverFactory() { + @Override + public <OutputT> FnDataReceiver<OutputT> create(String pCollectionId) { + // Outputs are queued here on harness threads and drained on the processing thread + // after the bundle closes. + return receivedElement -> { + if (receivedElement != null) { + pendingOutputs.add((WindowedValue<byte[]>) receivedElement); + } + }; + } + }; + currentBundle = + factory.getBundle( + outputReceiverFactory, + StateRequestHandler.unsupported(), + BundleProgressHandler.ignored()); + } + + private FnDataReceiver<WindowedValue<?>> mainInputReceiver() { + RemoteBundle bundle = checkInitialized(currentBundle); + @SuppressWarnings("unchecked") + FnDataReceiver<WindowedValue<?>> receiver = + (FnDataReceiver<WindowedValue<?>>) + (FnDataReceiver<?>) Iterables.getOnlyElement(bundle.getInputReceivers().values()); + return receiver; + } + + private void closeBundleAndFlush(Record<byte[], KStreamsPayload<byte[]>> record) { + RemoteBundle bundle = currentBundle; + if (bundle == null) { + return; + } + try { + // close() blocks until the harness finishes the bundle and all outputs have been delivered + // to the output receiver (and hence enqueued in pendingOutputs). + bundle.close(); + } catch (Exception e) { + throw new RuntimeException("Failed to close SDK harness bundle", e); + } finally { + currentBundle = null; + } + ProcessorContext<byte[], KStreamsPayload<byte[]>> ctx = checkInitialized(context); + WindowedValue<byte[]> output; + while ((output = pendingOutputs.poll()) != null) { Review Comment: We might use `forEach` here. ########## runners/kafka-streams/src/test/java/org/apache/beam/runners/kafka/streams/translation/SharedTestCollector.java: ########## @@ -0,0 +1,82 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.beam.runners.kafka.streams.translation; + +import java.io.Serializable; +import java.util.ArrayList; +import java.util.Collections; +import java.util.List; +import java.util.Map; +import java.util.UUID; +import java.util.concurrent.ConcurrentHashMap; + +/** + * Test-only side-effect sink that survives Beam serialization without losing collected elements. + * + * <p>An ExecutableStage that contains a user {@link org.apache.beam.sdk.transforms.DoFn} runs the + * DoFn in the SDK harness even when its output PCollection has no downstream consumer — the work is + * still performed for its side effects. The natural unit test for that is to have the DoFn record + * into a side-effect container and assert the container's contents from the test thread. + * + * <p>A plain static {@code AtomicReference} / {@code List} works only as long as the runner does + * not serialize the {@code DoFn} (and therefore the container instance it holds). The EMBEDDED + * environment may already, and could in the future, serialize the user code, in which case a cloned + * container would silently drop its writes. + * + * <p>This class works around that by keying the actual storage on a {@link UUID} held by an + * otherwise-empty instance. The instance itself is cheaply {@link Serializable}; clones still carry + * the same {@code UUID} and therefore see the same backing list in the static {@link #REGISTRY}. + * + * @param <T> element type + */ +final class SharedTestCollector<T> implements Serializable { + + private static final long serialVersionUID = 1L; + + /** Per-UUID storage, populated lazily on the first {@code record} for each instance. */ + private static final Map<UUID, List<Object>> REGISTRY = new ConcurrentHashMap<>(); + + private final UUID id = UUID.randomUUID(); + + /** Returns a fresh, empty collector instance with its own UUID. */ + static <T> SharedTestCollector<T> create() { + return new SharedTestCollector<>(); + } + + /** Records a single element. Safe to call from any thread. */ + void record(T element) { + REGISTRY.computeIfAbsent(id, k -> Collections.synchronizedList(new ArrayList<>())).add(element); + } + + /** Returns an immutable snapshot of all recorded elements, in order. */ + @SuppressWarnings("unchecked") + List<T> recorded() { + List<Object> raw = REGISTRY.get(id); + if (raw == null) { + return Collections.emptyList(); + } + synchronized (raw) { + return Collections.unmodifiableList(new ArrayList<>((List<T>) (List<?>) raw)); + } + } + + /** Clears the backing storage for this collector. Useful for {@code @Before} resets. */ + void reset() { Review Comment: Would it be more practical to have `close()` and remove the UUID at the end of the test? ########## runners/kafka-streams/src/main/java/org/apache/beam/runners/kafka/streams/translation/ExecutableStageProcessor.java: ########## @@ -0,0 +1,211 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.beam.runners.kafka.streams.translation; + +import java.util.Queue; +import java.util.concurrent.ConcurrentLinkedQueue; +import org.apache.beam.model.pipeline.v1.RunnerApi; +import org.apache.beam.runners.fnexecution.control.BundleProgressHandler; +import org.apache.beam.runners.fnexecution.control.ExecutableStageContext; +import org.apache.beam.runners.fnexecution.control.OutputReceiverFactory; +import org.apache.beam.runners.fnexecution.control.RemoteBundle; +import org.apache.beam.runners.fnexecution.control.StageBundleFactory; +import org.apache.beam.runners.fnexecution.provisioning.JobInfo; +import org.apache.beam.runners.fnexecution.state.StateRequestHandler; +import org.apache.beam.sdk.fn.data.FnDataReceiver; +import org.apache.beam.sdk.util.construction.graph.ExecutableStage; +import org.apache.beam.sdk.values.WindowedValue; +import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.Iterables; +import org.apache.kafka.streams.processor.api.Processor; +import org.apache.kafka.streams.processor.api.ProcessorContext; +import org.apache.kafka.streams.processor.api.Record; +import org.checkerframework.checker.nullness.qual.Nullable; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +/** + * Kafka Streams {@link Processor} that executes a fused {@link ExecutableStage} (stateless user + * code such as ParDo) in the Beam SDK harness over the Fn API. + * + * <p>For each {@link KStreamsPayload#isData() data} payload it unwraps the {@link WindowedValue} + * and feeds it to the harness through the stage's main input {@link FnDataReceiver}. Harness + * outputs are collected on the harness threads into {@link #pendingOutputs} and then flushed + * downstream on the Kafka Streams processing thread when the bundle closes — Kafka Streams' {@link + * ProcessorContext#forward} must only be called from the processing thread, so outputs are never + * forwarded directly from a harness callback. + * + * <p>A {@link KStreamsPayload#isWatermark() watermark} payload marks a bundle boundary: the open + * bundle (if any) is closed (flushing outputs), and the watermark is then forwarded downstream so + * that subsequent stages observe it after all data of the bundle. + * + * <p>This is the Kafka Streams analogue of Flink's {@code ExecutableStageDoFnOperator} and Spark's + * {@code SparkExecutableStageFunction}. State, timers, and side inputs are out of scope for this + * first version: the stage is executed with {@link StateRequestHandler#unsupported()} and no timer + * receivers. + */ +class ExecutableStageProcessor + implements Processor<byte[], KStreamsPayload<byte[]>, byte[], KStreamsPayload<byte[]>> { + + private static final Logger LOG = LoggerFactory.getLogger(ExecutableStageProcessor.class); + + private final RunnerApi.ExecutableStagePayload stagePayload; + private final JobInfo jobInfo; + + // pendingOutputs is enqueued by SDK harness threads (inside the OutputReceiverFactory callback) + // and drained by the Kafka Streams processing thread on bundle close; needs to be thread-safe. + private final Queue<WindowedValue<byte[]>> pendingOutputs = new ConcurrentLinkedQueue<>(); + + private @Nullable ProcessorContext<byte[], KStreamsPayload<byte[]>> context; + private @Nullable ExecutableStageContext stageContext; + private @Nullable StageBundleFactory stageBundleFactory; + private @Nullable RemoteBundle currentBundle; + + ExecutableStageProcessor(RunnerApi.ExecutableStagePayload stagePayload, JobInfo jobInfo) { + this.stagePayload = stagePayload; + this.jobInfo = jobInfo; + } + + @Override + public void init(ProcessorContext<byte[], KStreamsPayload<byte[]>> context) { + this.context = context; + ExecutableStage executableStage = ExecutableStage.fromPayload(stagePayload); + this.stageContext = KafkaStreamsExecutableStageContextFactory.getInstance().get(jobInfo); + this.stageBundleFactory = stageContext.getStageBundleFactory(executableStage); + } + + @Override + public void process(Record<byte[], KStreamsPayload<byte[]>> record) { + KStreamsPayload<byte[]> payload = record.value(); + if (payload.isWatermark()) { + // NOTE: flushing the bundle on every received watermark is provisional. Once the + // WatermarkManager lands, a stage will receive watermarks from multiple parent instances and + // the output watermark becomes min() across them — the bundle should flush / the output + // watermark advance only when that minimum actually moves forward, not on every received + // watermark. Tracked in #38743. + closeBundleAndFlush(record); + forwardWatermark(record, payload.getWatermarkMillis()); + return; + } + try { + ensureBundleOpen(); + mainInputReceiver().accept(payload.getData()); + } catch (Exception e) { + throw new RuntimeException("Failed to process element through SDK harness", e); + } + } + + private void ensureBundleOpen() throws Exception { + if (currentBundle != null) { + return; + } + StageBundleFactory factory = checkInitialized(stageBundleFactory); + OutputReceiverFactory outputReceiverFactory = + new OutputReceiverFactory() { + @Override + public <OutputT> FnDataReceiver<OutputT> create(String pCollectionId) { + // Outputs are queued here on harness threads and drained on the processing thread + // after the bundle closes. + return receivedElement -> { + if (receivedElement != null) { + pendingOutputs.add((WindowedValue<byte[]>) receivedElement); + } + }; + } + }; + currentBundle = + factory.getBundle( + outputReceiverFactory, + StateRequestHandler.unsupported(), + BundleProgressHandler.ignored()); + } + + private FnDataReceiver<WindowedValue<?>> mainInputReceiver() { + RemoteBundle bundle = checkInitialized(currentBundle); + @SuppressWarnings("unchecked") + FnDataReceiver<WindowedValue<?>> receiver = + (FnDataReceiver<WindowedValue<?>>) + (FnDataReceiver<?>) Iterables.getOnlyElement(bundle.getInputReceivers().values()); + return receiver; + } + + private void closeBundleAndFlush(Record<byte[], KStreamsPayload<byte[]>> record) { + RemoteBundle bundle = currentBundle; + if (bundle == null) { + return; + } + try { + // close() blocks until the harness finishes the bundle and all outputs have been delivered + // to the output receiver (and hence enqueued in pendingOutputs). + bundle.close(); + } catch (Exception e) { + throw new RuntimeException("Failed to close SDK harness bundle", e); + } finally { + currentBundle = null; + } + ProcessorContext<byte[], KStreamsPayload<byte[]>> ctx = checkInitialized(context); + WindowedValue<byte[]> output; + while ((output = pendingOutputs.poll()) != null) { + ctx.forward( + new Record<byte[], KStreamsPayload<byte[]>>( + record.key(), KStreamsPayload.data(output), record.timestamp())); + } + } + + private void forwardWatermark( + Record<byte[], KStreamsPayload<byte[]>> record, long watermarkMillis) { + ProcessorContext<byte[], KStreamsPayload<byte[]>> ctx = checkInitialized(context); + ctx.forward( Review Comment: This will get more complicated, we need to forward the watermark to all instances of downstream processors - i.e. the simplest approach would be to forward it to all downstream partitions. -- This is an automated message from the Apache Git Service. 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