DataStream 如何转换为 Transformation ？

简介

本文就以中WordCount为例

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final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

DataStream<String> text = env.fromElements(WordCountData.WORDS);

text.flatMap(new Tokenizer())
    .keyBy(value -> value.f0).sum(1)
    .addSink(new CustomSink());

env.execute("Streaming WordCount");

flink-transformation.png

DataStreamSource

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public DataStreamSource(
		StreamExecutionEnvironment environment,
		TypeInformation<T> outTypeInfo,
		StreamSource<T, ?> operator,
		boolean isParallel,
		String sourceName,
		Boundedness boundedness) {
       // 传递给父类 DataStream, 并赋值, 后续调用的 flatMap, keyBy, aadSink 等算子都是调用 DataStream 的API
	super(environment, new LegacySourceTransformation<>(sourceName, operator, outTypeInfo, environment.getParallelism(), boundedness));

	this.isParallel = isParallel;
	if (!isParallel) {
		setParallelism(1);
	}
}

  • 调用 fromElements 算子,会构造出 DataStreamSource, LegacySourceTransformation（SourceTransformation）
  • 最后传递给父类 DataStream, 并赋值, 后续调用的 flatMap, keyBy, addSink 等算子都是调用 DataStream 的API

FlatMap

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protected <R> SingleOutputStreamOperator<R> doTransform(
		String operatorName,
		TypeInformation<R> outTypeInfo,
		StreamOperatorFactory<R> operatorFactory) {

	// 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,
			operatorFactory,
			outTypeInfo,
			environment.getParallelism());

	@SuppressWarnings({"unchecked", "rawtypes"})
	SingleOutputStreamOperator<R> returnStream = new SingleOutputStreamOperator(environment, resultTransform);
       // 把这个 transform 添加到 env的 list中
	getExecutionEnvironment().addOperator(resultTransform);

	return returnStream;
}
  • getExecutionEnvironment() 方法就是上节传递给 DataStream 的 env
  • addOperator 就是添加list元素

keyBy

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KeyedStream(
	DataStream<T> stream,
	PartitionTransformation<T> partitionTransformation,
	KeySelector<T, KEY> keySelector,
	TypeInformation<KEY> keyType) {

	super(stream.getExecutionEnvironment(), partitionTransformation);
	this.keySelector = clean(keySelector);
	this.keyType = validateKeyType(keyType);
}
  • keyBy 操作会重新构造构造 DataStream, 并把上游的 env 传递给新的 DataStream

addSink

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public DataStreamSink<T> addSink(SinkFunction<T> sinkFunction) {

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

	// configure the type if needed
	if (sinkFunction instanceof InputTypeConfigurable) {
		((InputTypeConfigurable) sinkFunction).setInputType(getType(), getExecutionConfig());
	}

	StreamSink<T> sinkOperator = new StreamSink<>(clean(sinkFunction));

	DataStreamSink<T> sink = new DataStreamSink<>(this, sinkOperator);

	getExecutionEnvironment().addOperator(sink.getTransformation());
	return sink;
}
  • 与 flatMap 类似

execute

  • 调用 execute 方法后会构造StreamGraph