概要

在 Flink 中，StreamGraph 是数据流的逻辑表示，它描述了如何在 Flink 作业中执行数据流转换。StreamGraph 是 Flink 运行时生成执行计划的基础。

使用DataStream API开发的应用程序，首先被转换为 Transformation，再被映射为StreamGraph，在客户端进行StreamGraph、JobGraph的转换，提交JobGraph到Flink集群后，Flink集群负责将JobGraph转换为ExecutionGraph，之后进入调度执行阶段。

SteramGraph 核心对象

• StreamNode
  StreamNode 是 StremGraph 中的节点 ，从 Transformation 转换而来，可以简单理解为一个 StreamNode 表示一个算子，从逻辑上来说，SteramNode 在 StreamGraph 中存在实体和虚拟的 StreamNode。StremNode 可以有多个输入，也可以有多个输出。
  实体的 StreamNode 会最终变成物理算子。虚拟的 StreamNode 会附着在 StreamEdge 上。
• StreamEdge
  StreamEdge 是 StreamGraph 中的边，用来连接两个 StreamNode,一个 StreamNode 可以有多个出边、入边，StreamEdge 中包含了旁路输出、分区器、字段筛选输出等信息。

SteramGraph 生成过程

StreamGraph 在 FlinkClient 中生成，由 FlinkClient 在提交的时候触发 Flink 应用的 main 方法，用户编写的业务逻辑组装成 Transformation 流水线，在最后调用 StreamExecutionEnvironment.execute() 的时候开始触发 StreamGraph 构建。
StreamGraph在Flink的作业提交前生成，生成StreamGraph的入口在StreamExecutionEnvironment中

    @Internalpublic StreamGraph getStreamGraph() {return this.getStreamGraph(this.getJobName());}@Internalpublic StreamGraph getStreamGraph(String jobName) {return this.getStreamGraph(jobName, true);}@Internalpublic StreamGraph getStreamGraph(String jobName, boolean clearTransformations) {StreamGraph streamGraph = this.getStreamGraphGenerator().setJobName(jobName).generate();if (clearTransformations) {this.transformations.clear();}return streamGraph;}private StreamGraphGenerator getStreamGraphGenerator() {if (this.transformations.size() <= 0) {throw new IllegalStateException("No operators defined in streaming topology. Cannot execute.");} else {RuntimeExecutionMode executionMode = (RuntimeExecutionMode)this.configuration.get(ExecutionOptions.RUNTIME_MODE);return (new StreamGraphGenerator(this.transformations, this.config, this.checkpointCfg, this.getConfiguration())).setRuntimeExecutionMode(executionMode).setStateBackend(this.defaultStateBackend).setChaining(this.isChainingEnabled).setUserArtifacts(this.cacheFile).setTimeCharacteristic(this.timeCharacteristic).setDefaultBufferTimeout(this.bufferTimeout);}}

StreamGraph实际上是在StreamGraphGenerator中生成的，从SinkTransformation(输出向前追溯到SourceTransformation)。在遍历过程中一边遍历一遍构建StreamGraph，如代码清单所示

@Internal
public class StreamGraphGenerator {private final List<Transformation<?>> transformations;private StateBackend stateBackend;private static final Map<Class<? extends Transformation>, TransformationTranslator<?, ? extends Transformation>> translatorMap;protected static Integer iterationIdCounter;private StreamGraph streamGraph;private Map<Transformation<?>, Collection<Integer>> alreadyTransformed;public StreamGraphGenerator(List<Transformation<?>> transformations, ExecutionConfig executionConfig, CheckpointConfig checkpointConfig) {this(transformations, executionConfig, checkpointConfig, new Configuration());}public StreamGraphGenerator(List<Transformation<?>> transformations, ExecutionConfig executionConfig, CheckpointConfig checkpointConfig, ReadableConfig configuration) {this.chaining = true;this.timeCharacteristic = DEFAULT_TIME_CHARACTERISTIC;this.jobName = "Flink Streaming Job";this.savepointRestoreSettings = SavepointRestoreSettings.none();this.defaultBufferTimeout = -1L;this.runtimeExecutionMode = RuntimeExecutionMode.STREAMING;this.transformations = (List)Preconditions.checkNotNull(transformations);this.executionConfig = (ExecutionConfig)Preconditions.checkNotNull(executionConfig);this.checkpointConfig = new CheckpointConfig(checkpointConfig);this.configuration = (ReadableConfig)Preconditions.checkNotNull(configuration);}public StreamGraph generate() {this.streamGraph = new StreamGraph(this.executionConfig, this.checkpointConfig, this.savepointRestoreSettings);this.shouldExecuteInBatchMode = this.shouldExecuteInBatchMode(this.runtimeExecutionMode);this.configureStreamGraph(this.streamGraph);this.alreadyTransformed = new HashMap();Iterator var1 = this.transformations.iterator();while(var1.hasNext()) {Transformation<?> transformation = (Transformation)var1.next();this.transform(transformation);}StreamGraph builtStreamGraph = this.streamGraph;this.alreadyTransformed.clear();this.alreadyTransformed = null;this.streamGraph = null;return builtStreamGraph;}private Collection<Integer> transform(Transformation<?> transform) {if (this.alreadyTransformed.containsKey(transform)) {return (Collection)this.alreadyTransformed.get(transform);} else {LOG.debug("Transforming " + transform);if (transform.getMaxParallelism() <= 0) {int globalMaxParallelismFromConfig = this.executionConfig.getMaxParallelism();if (globalMaxParallelismFromConfig > 0) {transform.setMaxParallelism(globalMaxParallelismFromConfig);}}transform.getOutputType();TransformationTranslator<?, Transformation<?>> translator = (TransformationTranslator)translatorMap.get(transform.getClass());Collection transformedIds;if (translator != null) {transformedIds = this.translate(translator, transform);} else {transformedIds = this.legacyTransform(transform);}if (!this.alreadyTransformed.containsKey(transform)) {this.alreadyTransformed.put(transform, transformedIds);}return transformedIds;}}private Collection<Integer> legacyTransform(Transformation<?> transform) {Collection transformedIds;if (transform instanceof FeedbackTransformation) {transformedIds = this.transformFeedback((FeedbackTransformation)transform);} else {if (!(transform instanceof CoFeedbackTransformation)) {throw new IllegalStateException("Unknown transformation: " + transform);}transformedIds = this.transformCoFeedback((CoFeedbackTransformation)transform);}if (transform.getBufferTimeout() >= 0L) {this.streamGraph.setBufferTimeout(transform.getId(), transform.getBufferTimeout());} else {this.streamGraph.setBufferTimeout(transform.getId(), this.defaultBufferTimeout);}if (transform.getUid() != null) {this.streamGraph.setTransformationUID(transform.getId(), transform.getUid());}if (transform.getUserProvidedNodeHash() != null) {this.streamGraph.setTransformationUserHash(transform.getId(), transform.getUserProvidedNodeHash());}if (!this.streamGraph.getExecutionConfig().hasAutoGeneratedUIDsEnabled() && transform instanceof PhysicalTransformation && transform.getUserProvidedNodeHash() == null && transform.getUid() == null) {throw new IllegalStateException("Auto generated UIDs have been disabled but no UID or hash has been assigned to operator " + transform.getName());} else {if (transform.getMinResources() != null && transform.getPreferredResources() != null) {this.streamGraph.setResources(transform.getId(), transform.getMinResources(), transform.getPreferredResources());}this.streamGraph.setManagedMemoryUseCaseWeights(transform.getId(), transform.getManagedMemoryOperatorScopeUseCaseWeights(), transform.getManagedMemorySlotScopeUseCases());return transformedIds;}}private <T> Collection<Integer> transformFeedback(FeedbackTransformation<T> iterate) {if (this.shouldExecuteInBatchMode) {throw new UnsupportedOperationException("Iterations are not supported in BATCH execution mode. If you want to execute such a pipeline, please set the '" + ExecutionOptions.RUNTIME_MODE.key() + "'=" + RuntimeExecutionMode.STREAMING.name());} else if (iterate.getFeedbackEdges().size() <= 0) {throw new IllegalStateException("Iteration " + iterate + " does not have any feedback edges.");} else {List<Transformation<?>> inputs = iterate.getInputs();Preconditions.checkState(inputs.size() == 1);Transformation<?> input = (Transformation)inputs.get(0);List<Integer> resultIds = new ArrayList();Collection<Integer> inputIds = this.transform(input);resultIds.addAll(inputIds);if (this.alreadyTransformed.containsKey(iterate)) {return (Collection)this.alreadyTransformed.get(iterate);} else {Tuple2<StreamNode, StreamNode> itSourceAndSink = this.streamGraph.createIterationSourceAndSink(iterate.getId(), getNewIterationNodeId(), getNewIterationNodeId(), iterate.getWaitTime(), iterate.getParallelism(), iterate.getMaxParallelism(), iterate.getMinResources(), iterate.getPreferredResources());StreamNode itSource = (StreamNode)itSourceAndSink.f0;StreamNode itSink = (StreamNode)itSourceAndSink.f1;this.streamGraph.setSerializers(itSource.getId(), (TypeSerializer)null, (TypeSerializer)null, iterate.getOutputType().createSerializer(this.executionConfig));this.streamGraph.setSerializers(itSink.getId(), iterate.getOutputType().createSerializer(this.executionConfig), (TypeSerializer)null, (TypeSerializer)null);resultIds.add(itSource.getId());this.alreadyTransformed.put(iterate, resultIds);List<Integer> allFeedbackIds = new ArrayList();Iterator var10 = iterate.getFeedbackEdges().iterator();while(var10.hasNext()) {Transformation<T> feedbackEdge = (Transformation)var10.next();Collection<Integer> feedbackIds = this.transform(feedbackEdge);allFeedbackIds.addAll(feedbackIds);Iterator var13 = feedbackIds.iterator();while(var13.hasNext()) {Integer feedbackId = (Integer)var13.next();this.streamGraph.addEdge(feedbackId, itSink.getId(), 0);}}String slotSharingGroup = this.determineSlotSharingGroup((String)null, allFeedbackIds);if (slotSharingGroup == null) {slotSharingGroup = "SlotSharingGroup-" + iterate.getId();}itSink.setSlotSharingGroup(slotSharingGroup);itSource.setSlotSharingGroup(slotSharingGroup);return resultIds;}}}private <F> Collection<Integer> transformCoFeedback(CoFeedbackTransformation<F> coIterate) {if (this.shouldExecuteInBatchMode) {throw new UnsupportedOperationException("Iterations are not supported in BATCH execution mode. If you want to execute such a pipeline, please set the '" + ExecutionOptions.RUNTIME_MODE.key() + "'=" + RuntimeExecutionMode.STREAMING.name());} else {Tuple2<StreamNode, StreamNode> itSourceAndSink = this.streamGraph.createIterationSourceAndSink(coIterate.getId(), getNewIterationNodeId(), getNewIterationNodeId(), coIterate.getWaitTime(), coIterate.getParallelism(), coIterate.getMaxParallelism(), coIterate.getMinResources(), coIterate.getPreferredResources());StreamNode itSource = (StreamNode)itSourceAndSink.f0;StreamNode itSink = (StreamNode)itSourceAndSink.f1;this.streamGraph.setSerializers(itSource.getId(), (TypeSerializer)null, (TypeSerializer)null, coIterate.getOutputType().createSerializer(this.executionConfig));this.streamGraph.setSerializers(itSink.getId(), coIterate.getOutputType().createSerializer(this.executionConfig), (TypeSerializer)null, (TypeSerializer)null);Collection<Integer> resultIds = Collections.singleton(itSource.getId());this.alreadyTransformed.put(coIterate, resultIds);List<Integer> allFeedbackIds = new ArrayList();Iterator var7 = coIterate.getFeedbackEdges().iterator();while(var7.hasNext()) {Transformation<F> feedbackEdge = (Transformation)var7.next();Collection<Integer> feedbackIds = this.transform(feedbackEdge);allFeedbackIds.addAll(feedbackIds);Iterator var10 = feedbackIds.iterator();while(var10.hasNext()) {Integer feedbackId = (Integer)var10.next();this.streamGraph.addEdge(feedbackId, itSink.getId(), 0);}}String slotSharingGroup = this.determineSlotSharingGroup((String)null, allFeedbackIds);itSink.setSlotSharingGroup(slotSharingGroup);itSource.setSlotSharingGroup(slotSharingGroup);return Collections.singleton(itSource.getId());}}private Collection<Integer> translate(TransformationTranslator<?, Transformation<?>> translator, Transformation<?> transform) {Preconditions.checkNotNull(translator);Preconditions.checkNotNull(transform);List<Collection<Integer>> allInputIds = this.getParentInputIds(transform.getInputs());if (this.alreadyTransformed.containsKey(transform)) {return (Collection)this.alreadyTransformed.get(transform);} else {String slotSharingGroup = this.determineSlotSharingGroup(transform.getSlotSharingGroup(), (Collection)allInputIds.stream().flatMap(Collection::stream).collect(Collectors.toList()));Context context = new StreamGraphGenerator.ContextImpl(this, this.streamGraph, slotSharingGroup, this.configuration);return this.shouldExecuteInBatchMode ? translator.translateForBatch(transform, context) : translator.translateForStreaming(transform, context);}}private List<Collection<Integer>> getParentInputIds(@Nullable Collection<Transformation<?>> parentTransformations) {List<Collection<Integer>> allInputIds = new ArrayList();if (parentTransformations == null) {return allInputIds;} else {Iterator var3 = parentTransformations.iterator();while(var3.hasNext()) {Transformation<?> transformation = (Transformation)var3.next();allInputIds.add(this.transform(transformation));}return allInputIds;}}private String determineSlotSharingGroup(String specifiedGroup, Collection<Integer> inputIds) {if (specifiedGroup != null) {return specifiedGroup;} else {String inputGroup = null;Iterator var4 = inputIds.iterator();while(var4.hasNext()) {int id = (Integer)var4.next();String inputGroupCandidate = this.streamGraph.getSlotSharingGroup(id);if (inputGroup == null) {inputGroup = inputGroupCandidate;} else if (!inputGroup.equals(inputGroupCandidate)) {return "default";}}return inputGroup == null ? "default" : inputGroup;}}static {DEFAULT_TIME_CHARACTERISTIC = TimeCharacteristic.ProcessingTime;Map<Class<? extends Transformation>, TransformationTranslator<?, ? extends Transformation>> tmp = new HashMap();tmp.put(OneInputTransformation.class, new OneInputTransformationTranslator());tmp.put(TwoInputTransformation.class, new TwoInputTransformationTranslator());tmp.put(MultipleInputTransformation.class, new MultiInputTransformationTranslator());tmp.put(KeyedMultipleInputTransformation.class, new MultiInputTransformationTranslator());tmp.put(SourceTransformation.class, new SourceTransformationTranslator());tmp.put(SinkTransformation.class, new SinkTransformationTranslator());tmp.put(LegacySinkTransformation.class, new LegacySinkTransformationTranslator());tmp.put(LegacySourceTransformation.class, new LegacySourceTransformationTranslator());tmp.put(UnionTransformation.class, new UnionTransformationTranslator());tmp.put(PartitionTransformation.class, new PartitionTransformationTranslator());tmp.put(SideOutputTransformation.class, new SideOutputTransformationTranslator());tmp.put(ReduceTransformation.class, new ReduceTransformationTranslator());tmp.put(TimestampsAndWatermarksTransformation.class, new TimestampsAndWatermarksTransformationTranslator());tmp.put(BroadcastStateTransformation.class, new BroadcastStateTransformationTranslator());tmp.put(KeyedBroadcastStateTransformation.class, new KeyedBroadcastStateTransformationTranslator());translatorMap = Collections.unmodifiableMap(tmp);iterationIdCounter = 0;} 
}