Flink Trigger实例

1、需求：统计每天的人员出现次数，按天开窗，并且每10s进行一次输出。

import org.apache.flink.api.common.eventtime.SerializableTimestampAssigner;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.common.state.ReducingState;
import org.apache.flink.api.common.state.ReducingStateDescriptor;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.tuple.Tuple3;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.streaming.api.windowing.assigners.TumblingEventTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.triggers.Trigger;
import org.apache.flink.streaming.api.windowing.triggers.TriggerResult;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;

import java.time.Duration;
import java.util.Random;

public class TriggerTest {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.getConfig().setAutoWatermarkInterval(100l);

        env.addSource(new SourceFunction<Tuple2<String, Long>>() {
            boolean flag = true;

            @Override
            public void run(SourceContext<Tuple2<String, Long>> ctx) throws Exception {
                String[] s = {"张三", "王五", "李四", "秋英"};
                while (flag) {
                    Thread.sleep(1000);
                    int i = new Random().nextInt(4);
                    ctx.collect(new Tuple2<String, Long>(s[i], System.currentTimeMillis()));
                }
            }

            @Override
            public void cancel() {
                flag = false;
            }
        }).assignTimestampsAndWatermarks(WatermarkStrategy.<Tuple2<String,Long>>forBoundedOutOfOrderness(Duration.ofSeconds(3))
        .withTimestampAssigner(new SerializableTimestampAssigner<Tuple2<String,Long>>() {
            @Override
            public long extractTimestamp(Tuple2<String, Long> stringLongTuple2, long l) {
                return stringLongTuple2.f1;
            }
        })).map(new MapFunction<Tuple2<String, Long>, Tuple3<String, Long, Integer>>() {
            @Override
            public Tuple3<String, Long, Integer> map(Tuple2<String, Long> stringLongTuple2) throws Exception {
                System.out.println(stringLongTuple2.f0 + stringLongTuple2.f1);
                return new Tuple3<String, Long, Integer>(stringLongTuple2.f0,stringLongTuple2.f1,1);
            }
        }).keyBy(new KeySelector<Tuple3<String, Long, Integer>, String>() {
            @Override
            public String getKey(Tuple3<String, Long, Integer> stringLongIntegerTuple3) throws Exception {
                return stringLongIntegerTuple3.f0;
            }
        }).window(TumblingEventTimeWindows.of(Time.days(1),Time.hours(-8))) 
                .trigger(new Trigger<Tuple3<String, Long, Integer>, TimeWindow>() {
                    // 10s触发一次
                    private final long interval = 10 * 1000l;
                    //每次调用add()方法，就调用一次MinTime.reduce()方法，ReducingState也可以换成ValueState，但是要把MinTime.reduce()方法体写到onElement()和onEventTime()方法体中
                    private final ReducingStateDescriptor<Long> lastTimeStateDescoriptor = new ReducingStateDescriptor<Long>("lastTime",new MinTime(),Long.class);

                    // 每个元素都执行该方法
                    @Override
                    public TriggerResult onElement(Tuple3<String, Long, Integer> element, long timestamp, TimeWindow window, TriggerContext ctx) throws Exception {
                        // 水位大于等于该窗口最后时间戳时触发计算
                        if(window.maxTimestamp() <= ctx.getCurrentWatermark()){
                            return TriggerResult.FIRE;
                        } else {
                            ctx.registerEventTimeTimer(window.maxTimestamp());
                        }

                        ReducingState<Long> lastTimeState = ctx.getPartitionedState(lastTimeStateDescoriptor);
                        Long lastTime = lastTimeState.get();

                        // 第一条数据进入时执行
                        if(lastTime == null){
                            // 当前10s触发时段的开始时间戳
                            Long start = timestamp - (timestamp % interval);
                            // 当前10s触发时段的触发时间
                            Long nextTimer = start + interval;
                            ctx.registerEventTimeTimer(nextTimer);
                            // 这里触发ReducingState -> MinTime.class -> reduce()
                            lastTimeState.add(nextTimer);
                        }

                        return TriggerResult.CONTINUE;
                    }

                    // 处理时间触发
                    @Override
                    public TriggerResult onProcessingTime(long time, TimeWindow window, TriggerContext ctx) throws Exception {
                        return TriggerResult.CONTINUE;
                    }

                    // 事件时间触发
                    @Override
                    public TriggerResult onEventTime(long time, TimeWindow window, TriggerContext ctx) throws Exception {
                        // 判断是否最后触发窗口计算
                        if(time == window.maxTimestamp()){
                            return TriggerResult.FIRE;
                        }

                        // 10s触发时
                        ReducingState<Long> lastTimeState = ctx.getPartitionedState(lastTimeStateDescoriptor);
                        Long lastTime = lastTimeState.get();
                        Long nextTimer = lastTime + interval;
                        if(time == lastTime){
                            // 此处可以保证如果10s内无数据，依然10s触发一次
                            lastTimeState.clear();
                            lastTimeState.add(nextTimer);
                            ctx.registerEventTimeTimer(nextTimer);
                            return TriggerResult.FIRE;
                        }

                        return TriggerResult.CONTINUE;
                    }

                    @Override
                    public void clear(TimeWindow window, TriggerContext ctx) throws Exception {
                        ReducingState<Long> lastTimeState = ctx.getPartitionedState(lastTimeStateDescoriptor);
                        Long lastTime = lastTimeState.get();
                        if(lastTime != null){
                            ctx.deleteEventTimeTimer(lastTime);
                            lastTimeState.clear();
                        }
                    }
                }).reduce(new ReduceFunction<Tuple3<String, Long, Integer>>() {
            @Override
            public Tuple3<String, Long, Integer> reduce(Tuple3<String, Long, Integer> stringLongIntegerTuple3, Tuple3<String, Long, Integer> t1) throws Exception {
                return new Tuple3<String, Long, Integer>(stringLongIntegerTuple3.f0,stringLongIntegerTuple3.f1,stringLongIntegerTuple3.f2 + t1.f2);
            }
        }).print();

        env.execute("trigger");

    }



    private static class MinTime implements ReduceFunction<Long>{

        @Override
        public Long reduce(Long aLong, Long t1) throws Exception {
            // 合并时，将所有fire时间戳中最低的一个作为新的fire时间戳
            return Math.min(aLong,t1);
        }
    }
}

以上代码可以使用.trigger(ContinuousEventTimeTrigger.of(Time.seconds(10)))，效果一样。

最后

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