Flink的CoGroup如何使用

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CoGroup算子：将两个数据流按照key进行group分组，并将数据流按key进行分区的处理，最终合成一个数据流（与join有区别，不管key有没有关联上,最终都会合并成一个数据流）

示例环境

java.version: 1.8.xflink.version: 1.11.1

示例数据源 （项目码云下载）

Flink 系例 之 搭建开发环境与数据

CoGroup.java

package com.flink.examples.functions;import com.flink.examples.DataSource;import com.google.gson.Gson;import org.apache.flink.api.common.eventtime.SerializableTimestampAssigner;import org.apache.flink.api.common.eventtime.WatermarkStrategy;import org.apache.flink.api.common.functions.CoGroupFunction;import org.apache.flink.api.java.functions.KeySelector;import org.apache.flink.api.java.tuple.Tuple3;import org.apache.flink.streaming.api.TimeCharacteristic;import org.apache.flink.streaming.api.datastream.DataStream;import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;import org.apache.flink.streaming.api.windowing.assigners.TumblingEventTimeWindows;import org.apache.flink.streaming.api.windowing.time.Time;import org.apache.flink.util.Collector;import java.time.Duration;import java.util.Arrays;import java.util.List;/** * @Description CoGroup算子：将两个数据流按照key进行group分组，并将数据流按key进行分区的处理，最终合成一个数据流（与join有区别，不管key有没有关联上,最终都会合并成一个数据流） */public class CoGroup {    /**     * 两个数据流集合，对相同key进行内联，分配到同一个窗口下，合并并打印     * @param args     * @throws Exception     */    public static void main(String[] args) throws Exception {        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();        env.setParallelism(1);        env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);        //watermark 自动添加水印调度时间        //env.getConfig().setAutoWatermarkInterval(200);        List> tuple3List1 = DataSource.getTuple3ToList();        List> tuple3List2 = Arrays.asList(                new Tuple3<>("伍七", "girl", 18),                new Tuple3<>("吴八", "man", 30)        );        //Datastream 1        DataStream> dataStream1 = env.fromCollection(tuple3List1)                //添加水印窗口,如果不添加，则时间窗口会一直等待水印事件时间，不会执行apply                .assignTimestampsAndWatermarks(WatermarkStrategy                        .>forBoundedOutOfOrderness(Duration.ofSeconds(2))                        .withTimestampAssigner((element, timestamp) -> System.currentTimeMillis()));        //Datastream 2        DataStream> dataStream2 = env.fromCollection(tuple3List2)                //添加水印窗口,如果不添加，则时间窗口会一直等待水印事件时间，不会执行apply                .assignTimestampsAndWatermarks(WatermarkStrategy                        .>forBoundedOutOfOrderness(Duration.ofSeconds(2))                        .withTimestampAssigner(new SerializableTimestampAssigner>() {                            @Override                            public long extractTimestamp(Tuple3 element, long timestamp) {                                return System.currentTimeMillis();                            }                        })                );        //对dataStream1和dataStream2两个数据流进行关联，没有关联也保留        //Datastream 3        DataStream newDataStream = dataStream1.coGroup(dataStream2)                .where(new KeySelector, String>() {                    @Override                    public String getKey(Tuple3 value) throws Exception {                        return value.f1;                    }                })                .equalTo(t3->t3.f1)                .window(TumblingEventTimeWindows.of(Time.seconds(1)))                .apply(new CoGroupFunction, Tuple3, String>() {                    @Override                    public void coGroup(Iterable> first, Iterable> second, Collector out) throws Exception {                        StringBuilder sb = new StringBuilder();                        Gson gson = new Gson();                        //datastream1的数据流集合                        for (Tuple3 tuple3 : first) {                            sb.append(gson.toJson(tuple3)).append("\n");                        }                        //datastream2的数据流集合                        for (Tuple3 tuple3 : second) {                            sb.append(gson.toJson(tuple3)).append("\n");                        }                        out.collect(sb.toString());                    }                });        newDataStream.print();        env.execute("flink CoGroup job");    }}

打印结果

{"f0":"张三","f1":"man","f2":20}{"f0":"王五","f1":"man","f2":29}{"f0":"吴八","f1":"man","f2":30}{"f0":"吴八","f1":"man","f2":30}{"f0":"李四","f1":"girl","f2":24}{"f0":"刘六","f1":"girl","f2":32}{"f0":"伍七","f1":"girl","f2":18}{"f0":"伍七","f1":"girl","f2":18}

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