Flink自定义FLatMap方法

Flink自定义FLatMap方法

• flatMap是将数据先map在打平，输入一个元素，可以输出0到多个元素
• 调用DataStream的transformation方法传入java的Lambda表达式，
• 如果返回的数据封装到一个带有泛型的包装类中（TupleN）
• 或是使用Collector将数据输出，必须加上returns

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.operators.AbstractStreamOperator;
import org.apache.flink.streaming.api.operators.OneInputStreamOperator;
import org.apache.flink.streaming.runtime.streamrecord.StreamRecord;
import org.apache.flink.util.Collector;



public class FlatMapDemo {
    public static void main(String[] args) throws Exception {
        Configuration configuration = new Configuration();
        configuration.setInteger("rest.port", 8081);
        StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironmentWithWebUI(configuration);

        DataStreamSource lines = env.socketTextStream("localhost", 8888);


//        SingleOutputStreamOperator words = lines.flatMap((String line, Collector out) -> {
//            for (String word : line.split(" ")) {
//                out.collect(word);
//            }
//        }).returns(Types.STRING);


        SingleOutputStreamOperator words = lines.transform("MyFlatMap", TypeInformation.of(String.class), new MyStreamFlatMap());
        words.print();
        env.execute();
    }
    private static class MyStreamFlatMap extends AbstractStreamOperator implements OneInputStreamOperator {
        
        @Override
        public void processElement(StreamRecord element) throws Exception {
            //取出输入的数据
            String in = element.getValue();
            //对数据进行切分压平
            String[] words = in.split(" ");
            //循环
            for (String word : words) {
                output.collect(new StreamRecord<>(word));
            }
        }
    }