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Example 1 with ReadOperation

use of org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation in project beam by apache.

the class IntrinsicMapTaskExecutorFactoryTest method testCreateMapTaskExecutor.

@Test
public void testCreateMapTaskExecutor() throws Exception {
    List<ParallelInstruction> instructions = Arrays.asList(createReadInstruction("Read"), createParDoInstruction(0, 0, "DoFn1"), createParDoInstruction(0, 0, "DoFnWithContext"), createFlattenInstruction(1, 0, 2, 0, "Flatten"), createWriteInstruction(3, 0, "Write"));
    MapTask mapTask = new MapTask();
    mapTask.setStageName(STAGE);
    mapTask.setSystemName("systemName");
    mapTask.setInstructions(instructions);
    mapTask.setFactory(Transport.getJsonFactory());
    try (DataflowMapTaskExecutor executor = mapTaskExecutorFactory.create(null, /* beamFnControlClientHandler */
    null, /* GrpcFnServer<GrpcDataService> */
    null, /* ApiServiceDescriptor */
    null, /* GrpcFnServer<GrpcStateService> */
    mapTaskToNetwork.apply(mapTask), options, STAGE, readerRegistry, sinkRegistry, BatchModeExecutionContext.forTesting(options, counterSet, "testStage"), counterSet, idGenerator)) {
        // Safe covariant cast not expressible without rawtypes.
        @SuppressWarnings({ // TODO(https://issues.apache.org/jira/browse/BEAM-10556)
        "rawtypes", "unchecked" }) List<Object> operations = (List) executor.operations;
        assertThat(operations, hasItems(instanceOf(ReadOperation.class), instanceOf(ParDoOperation.class), instanceOf(ParDoOperation.class), instanceOf(FlattenOperation.class), instanceOf(WriteOperation.class)));
        // Verify that the inputs are attached.
        ReadOperation readOperation = Iterables.getOnlyElement(Iterables.filter(operations, ReadOperation.class));
        assertEquals(2, readOperation.receivers[0].getReceiverCount());
        FlattenOperation flattenOperation = Iterables.getOnlyElement(Iterables.filter(operations, FlattenOperation.class));
        for (ParDoOperation operation : Iterables.filter(operations, ParDoOperation.class)) {
            assertSame(flattenOperation, operation.receivers[0].getOnlyReceiver());
        }
        WriteOperation writeOperation = Iterables.getOnlyElement(Iterables.filter(operations, WriteOperation.class));
        assertSame(writeOperation, flattenOperation.receivers[0].getOnlyReceiver());
    }
    @SuppressWarnings("unchecked") Counter<Long, ?> otherMsecCounter = (Counter<Long, ?>) counterSet.getExistingCounter("test-other-msecs");
    // "other" state only got created upon MapTaskExecutor.execute().
    assertNull(otherMsecCounter);
    counterSet.extractUpdates(false, updateExtractor);
    verifyOutputCounters(updateExtractor, "read_output_name", "DoFn1_output", "DoFnWithContext_output", "flatten_output_name");
    verify(updateExtractor).longSum(eq(named("Read-ByteCount")), anyBoolean(), anyLong());
    verify(updateExtractor).longSum(eq(named("Write-ByteCount")), anyBoolean(), anyLong());
    verifyNoMoreInteractions(updateExtractor);
}
Also used : ReadOperation(org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation) ParDoOperation(org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation) ParallelInstruction(com.google.api.services.dataflow.model.ParallelInstruction) FlattenOperation(org.apache.beam.runners.dataflow.worker.util.common.worker.FlattenOperation) Counter(org.apache.beam.runners.dataflow.worker.counters.Counter) WriteOperation(org.apache.beam.runners.dataflow.worker.util.common.worker.WriteOperation) MapTask(com.google.api.services.dataflow.model.MapTask) Matchers.anyLong(org.mockito.Matchers.anyLong) CloudObject(org.apache.beam.runners.dataflow.util.CloudObject) List(java.util.List) ImmutableList(org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableList) ArrayList(java.util.ArrayList) Test(org.junit.Test)

Example 2 with ReadOperation

use of org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation in project beam by apache.

the class IntrinsicMapTaskExecutorTest method testValidOperations.

@Test
public void testValidOperations() throws Exception {
    TestOutputReceiver receiver = new TestOutputReceiver(counterSet, NameContextsForTests.nameContextForTest());
    List<Operation> operations = Arrays.<Operation>asList(new TestReadOperation(receiver, createContext("ReadOperation")));
    ExecutionStateTracker stateTracker = ExecutionStateTracker.newForTest();
    try (IntrinsicMapTaskExecutor executor = IntrinsicMapTaskExecutor.withSharedCounterSet(operations, counterSet, stateTracker)) {
        Assert.assertEquals(operations.get(0), executor.getReadOperation());
    }
}
Also used : ExecutionStateTracker(org.apache.beam.runners.core.metrics.ExecutionStateTracker) DataflowExecutionStateTracker(org.apache.beam.runners.dataflow.worker.DataflowExecutionContext.DataflowExecutionStateTracker) ParDoOperation(org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation) ReadOperation(org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation) Operation(org.apache.beam.runners.dataflow.worker.util.common.worker.Operation) TestOutputReceiver(org.apache.beam.runners.dataflow.worker.util.common.worker.TestOutputReceiver) Test(org.junit.Test)

Example 3 with ReadOperation

use of org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation in project beam by apache.

the class BeamFnMapTaskExecutor method createProgressTracker.

private ProgressTracker createProgressTracker() {
    ReadOperation readOperation;
    RemoteGrpcPortWriteOperation grpcWriteOperation;
    RegisterAndProcessBundleOperation bundleProcessOperation;
    try {
        readOperation = getReadOperation();
    } catch (Exception exn) {
        readOperation = null;
        LOG.info("Unable to get read operation.", exn);
        return new NullProgressTracker();
    }
    // RegisterAndProcessBundleOperation we know they have the right topology.
    try {
        grpcWriteOperation = Iterables.getOnlyElement(Iterables.filter(operations, RemoteGrpcPortWriteOperation.class));
        bundleProcessOperation = Iterables.getOnlyElement(Iterables.filter(operations, RegisterAndProcessBundleOperation.class));
    } catch (IllegalArgumentException | NoSuchElementException exn) {
        // TODO: Handle more than one sdk worker processing a single bundle.
        grpcWriteOperation = null;
        bundleProcessOperation = null;
        LOG.debug("Does not have exactly one grpcWRite and bundleProcess operation.", exn);
    }
    if (grpcWriteOperation != null && bundleProcessOperation != null) {
        return new SingularProcessBundleProgressTracker(readOperation, grpcWriteOperation, bundleProcessOperation);
    } else {
        return new ReadOperationProgressTracker(readOperation);
    }
}
Also used : ReadOperation(org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation) RemoteGrpcPortWriteOperation(org.apache.beam.runners.dataflow.worker.fn.data.RemoteGrpcPortWriteOperation) CancellationException(java.util.concurrent.CancellationException) NoSuchElementException(java.util.NoSuchElementException) ExecutionException(java.util.concurrent.ExecutionException) NoSuchElementException(java.util.NoSuchElementException)

Example 4 with ReadOperation

use of org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation in project beam by apache.

the class StreamingDataflowWorker method process.

private void process(final SdkWorkerHarness worker, final ComputationState computationState, final Instant inputDataWatermark, @Nullable final Instant outputDataWatermark, @Nullable final Instant synchronizedProcessingTime, final Work work) {
    final Windmill.WorkItem workItem = work.getWorkItem();
    final String computationId = computationState.getComputationId();
    final ByteString key = workItem.getKey();
    work.setState(State.PROCESSING);
    {
        StringBuilder workIdBuilder = new StringBuilder(33);
        workIdBuilder.append(Long.toHexString(workItem.getShardingKey()));
        workIdBuilder.append('-');
        workIdBuilder.append(Long.toHexString(workItem.getWorkToken()));
        DataflowWorkerLoggingMDC.setWorkId(workIdBuilder.toString());
    }
    DataflowWorkerLoggingMDC.setStageName(computationId);
    LOG.debug("Starting processing for {}:\n{}", computationId, work);
    Windmill.WorkItemCommitRequest.Builder outputBuilder = initializeOutputBuilder(key, workItem);
    // Before any processing starts, call any pending OnCommit callbacks.  Nothing that requires
    // cleanup should be done before this, since we might exit early here.
    callFinalizeCallbacks(workItem);
    if (workItem.getSourceState().getOnlyFinalize()) {
        outputBuilder.setSourceStateUpdates(Windmill.SourceState.newBuilder().setOnlyFinalize(true));
        work.setState(State.COMMIT_QUEUED);
        commitQueue.put(new Commit(outputBuilder.build(), computationState, work));
        return;
    }
    long processingStartTimeNanos = System.nanoTime();
    final MapTask mapTask = computationState.getMapTask();
    StageInfo stageInfo = stageInfoMap.computeIfAbsent(mapTask.getStageName(), s -> new StageInfo(s, mapTask.getSystemName(), this));
    ExecutionState executionState = null;
    try {
        executionState = computationState.getExecutionStateQueue(worker).poll();
        if (executionState == null) {
            MutableNetwork<Node, Edge> mapTaskNetwork = mapTaskToNetwork.apply(mapTask);
            if (LOG.isDebugEnabled()) {
                LOG.debug("Network as Graphviz .dot: {}", Networks.toDot(mapTaskNetwork));
            }
            ParallelInstructionNode readNode = (ParallelInstructionNode) Iterables.find(mapTaskNetwork.nodes(), node -> node instanceof ParallelInstructionNode && ((ParallelInstructionNode) node).getParallelInstruction().getRead() != null);
            InstructionOutputNode readOutputNode = (InstructionOutputNode) Iterables.getOnlyElement(mapTaskNetwork.successors(readNode));
            DataflowExecutionContext.DataflowExecutionStateTracker executionStateTracker = new DataflowExecutionContext.DataflowExecutionStateTracker(ExecutionStateSampler.instance(), stageInfo.executionStateRegistry.getState(NameContext.forStage(mapTask.getStageName()), "other", null, ScopedProfiler.INSTANCE.emptyScope()), stageInfo.deltaCounters, options, computationId);
            StreamingModeExecutionContext context = new StreamingModeExecutionContext(pendingDeltaCounters, computationId, readerCache, !computationState.getTransformUserNameToStateFamily().isEmpty() ? computationState.getTransformUserNameToStateFamily() : stateNameMap, stateCache.forComputation(computationId), stageInfo.metricsContainerRegistry, executionStateTracker, stageInfo.executionStateRegistry, maxSinkBytes);
            DataflowMapTaskExecutor mapTaskExecutor = mapTaskExecutorFactory.create(worker.getControlClientHandler(), worker.getGrpcDataFnServer(), sdkHarnessRegistry.beamFnDataApiServiceDescriptor(), worker.getGrpcStateFnServer(), mapTaskNetwork, options, mapTask.getStageName(), readerRegistry, sinkRegistry, context, pendingDeltaCounters, idGenerator);
            ReadOperation readOperation = mapTaskExecutor.getReadOperation();
            // Disable progress updates since its results are unused  for streaming
            // and involves starting a thread.
            readOperation.setProgressUpdatePeriodMs(ReadOperation.DONT_UPDATE_PERIODICALLY);
            Preconditions.checkState(mapTaskExecutor.supportsRestart(), "Streaming runner requires all operations support restart.");
            Coder<?> readCoder;
            readCoder = CloudObjects.coderFromCloudObject(CloudObject.fromSpec(readOutputNode.getInstructionOutput().getCodec()));
            Coder<?> keyCoder = extractKeyCoder(readCoder);
            // If using a custom source, count bytes read for autoscaling.
            if (CustomSources.class.getName().equals(readNode.getParallelInstruction().getRead().getSource().getSpec().get("@type"))) {
                NameContext nameContext = NameContext.create(mapTask.getStageName(), readNode.getParallelInstruction().getOriginalName(), readNode.getParallelInstruction().getSystemName(), readNode.getParallelInstruction().getName());
                readOperation.receivers[0].addOutputCounter(new OutputObjectAndByteCounter(new IntrinsicMapTaskExecutorFactory.ElementByteSizeObservableCoder<>(readCoder), mapTaskExecutor.getOutputCounters(), nameContext).setSamplingPeriod(100).countBytes("dataflow_input_size-" + mapTask.getSystemName()));
            }
            executionState = new ExecutionState(mapTaskExecutor, context, keyCoder, executionStateTracker);
        }
        WindmillStateReader stateReader = new WindmillStateReader(metricTrackingWindmillServer, computationId, key, workItem.getShardingKey(), workItem.getWorkToken());
        StateFetcher localStateFetcher = stateFetcher.byteTrackingView();
        // If the read output KVs, then we can decode Windmill's byte key into a userland
        // key object and provide it to the execution context for use with per-key state.
        // Otherwise, we pass null.
        // 
        // The coder type that will be present is:
        // WindowedValueCoder(TimerOrElementCoder(KvCoder))
        @Nullable Coder<?> keyCoder = executionState.getKeyCoder();
        @Nullable Object executionKey = keyCoder == null ? null : keyCoder.decode(key.newInput(), Coder.Context.OUTER);
        if (workItem.hasHotKeyInfo()) {
            Windmill.HotKeyInfo hotKeyInfo = workItem.getHotKeyInfo();
            Duration hotKeyAge = Duration.millis(hotKeyInfo.getHotKeyAgeUsec() / 1000);
            // The MapTask instruction is ordered by dependencies, such that the first element is
            // always going to be the shuffle task.
            String stepName = computationState.getMapTask().getInstructions().get(0).getName();
            if (options.isHotKeyLoggingEnabled() && keyCoder != null) {
                hotKeyLogger.logHotKeyDetection(stepName, hotKeyAge, executionKey);
            } else {
                hotKeyLogger.logHotKeyDetection(stepName, hotKeyAge);
            }
        }
        executionState.getContext().start(executionKey, workItem, inputDataWatermark, outputDataWatermark, synchronizedProcessingTime, stateReader, localStateFetcher, outputBuilder);
        // Blocks while executing work.
        executionState.getWorkExecutor().execute();
        Iterables.addAll(this.pendingMonitoringInfos, executionState.getWorkExecutor().extractMetricUpdates());
        commitCallbacks.putAll(executionState.getContext().flushState());
        // Release the execution state for another thread to use.
        computationState.getExecutionStateQueue(worker).offer(executionState);
        executionState = null;
        // Add the output to the commit queue.
        work.setState(State.COMMIT_QUEUED);
        WorkItemCommitRequest commitRequest = outputBuilder.build();
        int byteLimit = maxWorkItemCommitBytes;
        int commitSize = commitRequest.getSerializedSize();
        int estimatedCommitSize = commitSize < 0 ? Integer.MAX_VALUE : commitSize;
        // Detect overflow of integer serialized size or if the byte limit was exceeded.
        windmillMaxObservedWorkItemCommitBytes.addValue(estimatedCommitSize);
        if (commitSize < 0 || commitSize > byteLimit) {
            KeyCommitTooLargeException e = KeyCommitTooLargeException.causedBy(computationId, byteLimit, commitRequest);
            reportFailure(computationId, workItem, e);
            LOG.error(e.toString());
            // Drop the current request in favor of a new, minimal one requesting truncation.
            // Messages, timers, counters, and other commit content will not be used by the service
            // so we're purposefully dropping them here
            commitRequest = buildWorkItemTruncationRequest(key, workItem, estimatedCommitSize);
        }
        commitQueue.put(new Commit(commitRequest, computationState, work));
        // Compute shuffle and state byte statistics these will be flushed asynchronously.
        long stateBytesWritten = outputBuilder.clearOutputMessages().build().getSerializedSize();
        long shuffleBytesRead = 0;
        for (Windmill.InputMessageBundle bundle : workItem.getMessageBundlesList()) {
            for (Windmill.Message message : bundle.getMessagesList()) {
                shuffleBytesRead += message.getSerializedSize();
            }
        }
        long stateBytesRead = stateReader.getBytesRead() + localStateFetcher.getBytesRead();
        windmillShuffleBytesRead.addValue(shuffleBytesRead);
        windmillStateBytesRead.addValue(stateBytesRead);
        windmillStateBytesWritten.addValue(stateBytesWritten);
        LOG.debug("Processing done for work token: {}", workItem.getWorkToken());
    } catch (Throwable t) {
        if (executionState != null) {
            try {
                executionState.getContext().invalidateCache();
                executionState.getWorkExecutor().close();
            } catch (Exception e) {
                LOG.warn("Failed to close map task executor: ", e);
            } finally {
                // Release references to potentially large objects early.
                executionState = null;
            }
        }
        t = t instanceof UserCodeException ? t.getCause() : t;
        boolean retryLocally = false;
        if (KeyTokenInvalidException.isKeyTokenInvalidException(t)) {
            LOG.debug("Execution of work for computation '{}' on key '{}' failed due to token expiration. " + "Work will not be retried locally.", computationId, key.toStringUtf8());
        } else {
            LastExceptionDataProvider.reportException(t);
            LOG.debug("Failed work: {}", work);
            Duration elapsedTimeSinceStart = new Duration(Instant.now(), work.getStartTime());
            if (!reportFailure(computationId, workItem, t)) {
                LOG.error("Execution of work for computation '{}' on key '{}' failed with uncaught exception, " + "and Windmill indicated not to retry locally.", computationId, key.toStringUtf8(), t);
            } else if (isOutOfMemoryError(t)) {
                File heapDump = memoryMonitor.tryToDumpHeap();
                LOG.error("Execution of work for computation '{}' for key '{}' failed with out-of-memory. " + "Work will not be retried locally. Heap dump {}.", computationId, key.toStringUtf8(), heapDump == null ? "not written" : ("written to '" + heapDump + "'"), t);
            } else if (elapsedTimeSinceStart.isLongerThan(MAX_LOCAL_PROCESSING_RETRY_DURATION)) {
                LOG.error("Execution of work for computation '{}' for key '{}' failed with uncaught exception, " + "and it will not be retried locally because the elapsed time since start {} " + "exceeds {}.", computationId, key.toStringUtf8(), elapsedTimeSinceStart, MAX_LOCAL_PROCESSING_RETRY_DURATION, t);
            } else {
                LOG.error("Execution of work for computation '{}' on key '{}' failed with uncaught exception. " + "Work will be retried locally.", computationId, key.toStringUtf8(), t);
                retryLocally = true;
            }
        }
        if (retryLocally) {
            // Try again after some delay and at the end of the queue to avoid a tight loop.
            sleep(retryLocallyDelayMs);
            workUnitExecutor.forceExecute(work, work.getWorkItem().getSerializedSize());
        } else {
            // Consider the item invalid. It will eventually be retried by Windmill if it still needs to
            // be processed.
            computationState.completeWork(ShardedKey.create(key, workItem.getShardingKey()), workItem.getWorkToken());
        }
    } finally {
        // Update total processing time counters. Updating in finally clause ensures that
        // work items causing exceptions are also accounted in time spent.
        long processingTimeMsecs = TimeUnit.NANOSECONDS.toMillis(System.nanoTime() - processingStartTimeNanos);
        stageInfo.totalProcessingMsecs.addValue(processingTimeMsecs);
        // either here or in DFE.
        if (work.getWorkItem().hasTimers()) {
            stageInfo.timerProcessingMsecs.addValue(processingTimeMsecs);
        }
        DataflowWorkerLoggingMDC.setWorkId(null);
        DataflowWorkerLoggingMDC.setStageName(null);
    }
}
Also used : MetricName(org.apache.beam.sdk.metrics.MetricName) MapTask(com.google.api.services.dataflow.model.MapTask) UserCodeException(org.apache.beam.sdk.util.UserCodeException) WindowedValueCoder(org.apache.beam.sdk.util.WindowedValue.WindowedValueCoder) MetricsLogger(org.apache.beam.runners.core.metrics.MetricsLogger) CommitWorkStream(org.apache.beam.runners.dataflow.worker.windmill.WindmillServerStub.CommitWorkStream) CloudObjects(org.apache.beam.runners.dataflow.util.CloudObjects) ImmutableMap(org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap) Map(java.util.Map) CreateRegisterFnOperationFunction(org.apache.beam.runners.dataflow.worker.graph.CreateRegisterFnOperationFunction) ScopedProfiler(org.apache.beam.runners.dataflow.worker.profiler.ScopedProfiler) StreamPool(org.apache.beam.runners.dataflow.worker.windmill.WindmillServerStub.StreamPool) 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Example 5 with ReadOperation

use of org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation in project beam by apache.

the class IntrinsicMapTaskExecutorFactoryTest method testCreateReadOperation.

@Test
public void testCreateReadOperation() throws Exception {
    ParallelInstructionNode instructionNode = ParallelInstructionNode.create(createReadInstruction("Read"), ExecutionLocation.UNKNOWN);
    when(network.successors(instructionNode)).thenReturn(ImmutableSet.<Node>of(IntrinsicMapTaskExecutorFactory.createOutputReceiversTransform(STAGE, counterSet).apply(InstructionOutputNode.create(instructionNode.getParallelInstruction().getOutputs().get(0), PCOLLECTION_ID))));
    when(network.outDegree(instructionNode)).thenReturn(1);
    Node operationNode = mapTaskExecutorFactory.createOperationTransformForParallelInstructionNodes(STAGE, network, PipelineOptionsFactory.create(), readerRegistry, sinkRegistry, BatchModeExecutionContext.forTesting(options, counterSet, "testStage")).apply(instructionNode);
    assertThat(operationNode, instanceOf(OperationNode.class));
    assertThat(((OperationNode) operationNode).getOperation(), instanceOf(ReadOperation.class));
    ReadOperation readOperation = (ReadOperation) ((OperationNode) operationNode).getOperation();
    assertEquals(1, readOperation.receivers.length);
    assertEquals(0, readOperation.receivers[0].getReceiverCount());
    assertEquals(Operation.InitializationState.UNSTARTED, readOperation.initializationState);
    assertThat(readOperation.reader, instanceOf(ReaderFactoryTest.TestReader.class));
    counterSet.extractUpdates(false, updateExtractor);
    verifyOutputCounters(updateExtractor, "read_output_name");
    verify(updateExtractor).longSum(eq(named("Read-ByteCount")), anyBoolean(), anyLong());
    verifyNoMoreInteractions(updateExtractor);
}
Also used : OperationNode(org.apache.beam.runners.dataflow.worker.graph.Nodes.OperationNode) ReadOperation(org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation) InstructionOutputNode(org.apache.beam.runners.dataflow.worker.graph.Nodes.InstructionOutputNode) OperationNode(org.apache.beam.runners.dataflow.worker.graph.Nodes.OperationNode) ParallelInstructionNode(org.apache.beam.runners.dataflow.worker.graph.Nodes.ParallelInstructionNode) Node(org.apache.beam.runners.dataflow.worker.graph.Nodes.Node) ParallelInstructionNode(org.apache.beam.runners.dataflow.worker.graph.Nodes.ParallelInstructionNode) Test(org.junit.Test)

Aggregations

ReadOperation (org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation)9 Test (org.junit.Test)7 ParDoOperation (org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation)5 ExecutionStateTracker (org.apache.beam.runners.core.metrics.ExecutionStateTracker)4 DataflowExecutionStateTracker (org.apache.beam.runners.dataflow.worker.DataflowExecutionContext.DataflowExecutionStateTracker)4 Operation (org.apache.beam.runners.dataflow.worker.util.common.worker.Operation)4 Counter (org.apache.beam.runners.dataflow.worker.counters.Counter)3 TestOutputReceiver (org.apache.beam.runners.dataflow.worker.util.common.worker.TestOutputReceiver)3 MapTask (com.google.api.services.dataflow.model.MapTask)2 ArrayList (java.util.ArrayList)2 List (java.util.List)2 NameContext (org.apache.beam.runners.dataflow.worker.counters.NameContext)2 InstructionOutputNode (org.apache.beam.runners.dataflow.worker.graph.Nodes.InstructionOutputNode)2 Node (org.apache.beam.runners.dataflow.worker.graph.Nodes.Node)2 ParallelInstructionNode (org.apache.beam.runners.dataflow.worker.graph.Nodes.ParallelInstructionNode)2 CounterStructuredName (com.google.api.services.dataflow.model.CounterStructuredName)1 CounterUpdate (com.google.api.services.dataflow.model.CounterUpdate)1 ParallelInstruction (com.google.api.services.dataflow.model.ParallelInstruction)1 Status (com.google.api.services.dataflow.model.Status)1 StreamingComputationConfig (com.google.api.services.dataflow.model.StreamingComputationConfig)1