flink系列(7)-streamGraph

StreamGraph是flink四層執行圖中的第一層圖，代碼在org.apache.flink.streaming.api.graph包中，第一層graph主要作的事情是將全部的stransformation添加到DAG中，並設置並行度，設置slot槽位

具體涉及到的transformation大概有11個，繼承圖以下

首先咱們來看一下如何獲取StreamTransformation

public <OUT> DataStreamSource<OUT> addSource(SourceFunction<OUT> function, String sourceName, TypeInformation<OUT> typeInfo) {

		if (typeInfo == null) {
			if (function instanceof ResultTypeQueryable) {
				typeInfo = ((ResultTypeQueryable<OUT>) function).getProducedType();
			} else {
				try {
					typeInfo = TypeExtractor.createTypeInfo(
							SourceFunction.class,
							function.getClass(), 0, null, null);
				} catch (final InvalidTypesException e) {
					typeInfo = (TypeInformation<OUT>) new MissingTypeInfo(sourceName, e);
				}
			}
		}

		boolean isParallel = function instanceof ParallelSourceFunction;

		clean(function);
		StreamSource<OUT, ?> sourceOperator;
		if (function instanceof StoppableFunction) {
			sourceOperator = new StoppableStreamSource<>(cast2StoppableSourceFunction(function));
		} else {
			sourceOperator = new StreamSource<>(function);
		}

		return new DataStreamSource<>(this, typeInfo, sourceOperator, isParallel, sourceName);
	}

最終返回的是DataStreamSource，內部封裝了SourceTransformation，下面看一下DataStream的類圖結構

能夠看到DataStreamSource是DataStream的子類

DataStreamSource是DataStream的數據流抽象，StreamSource是StreamOperator的抽象，在 flink 中一個 DataStream 封裝了一次數據流轉換，一個 StreamOperator 封裝了一個函數接口，好比 map、reduce、keyBy等。下面咱們在看一下StreamOperator的類圖關係

能夠看到StreamMap/StreamFlatMap都是operator的子類，下面來看一段具體生成operator和transformation的代碼

/**
	 * Applies a Map transformation on a {@link DataStream}. The transformation
	 * calls a {@link MapFunction} for each element of the DataStream. Each
	 * MapFunction call returns exactly one element. The user can also extend
	 * {@link RichMapFunction} to gain access to other features provided by the
	 * {@link org.apache.flink.api.common.functions.RichFunction} interface.
	 *
	 * @param mapper
	 *            The MapFunction that is called for each element of the
	 *            DataStream.
	 * @param <R>
	 *            output type
	 * @return The transformed {@link DataStream}.
	 */
	public <R> SingleOutputStreamOperator<R> map(MapFunction<T, R> mapper) {

		TypeInformation<R> outType = TypeExtractor.getMapReturnTypes(clean(mapper), getType(),
				Utils.getCallLocationName(), true);

		return transform("Map", outType, new StreamMap<>(clean(mapper)));
	}

/**
	 * Method for passing user defined operators along with the type
	 * information that will transform the DataStream.
	 *
	 * @param operatorName
	 *            name of the operator, for logging purposes
	 * @param outTypeInfo
	 *            the output type of the operator
	 * @param operator
	 *            the object containing the transformation logic
	 * @param <R>
	 *            type of the return stream
	 * @return the data stream constructed
	 */
	@PublicEvolving
	public <R> SingleOutputStreamOperator<R> transform(String operatorName, TypeInformation<R> outTypeInfo, OneInputStreamOperator<T, R> operator) {

		// read the output type of the input Transform to coax out errors about MissingTypeInfo
		transformation.getOutputType();

		OneInputTransformation<T, R> resultTransform = new OneInputTransformation<>(
				this.transformation,
				operatorName,
				operator,
				outTypeInfo,
				environment.getParallelism());

		@SuppressWarnings({ "unchecked", "rawtypes" })
		SingleOutputStreamOperator<R> returnStream = new SingleOutputStreamOperator(environment, resultTransform);

		getExecutionEnvironment().addOperator(resultTransform);

		return returnStream;
	}

到這裏基本說完了DataStream和StreamOperator，包含transformation的產生，DataStream的操做等，下一篇咱們在來講一下transformation的轉換