watermark

• watermark的作用
  就是延迟触发窗口，让乱序到达的元素依然能够落在正确的窗口内。为啥能实现这个效果，一直通过公式更新watermark,如果乱序到的元素就不能更新watermark,相当于就是延迟触发计算操作。
• 触发时间
  watermark 大于窗口的最大值
• allowedLateness
  允许迟到的时间，到底啥时到的元素算迟到元素,如果元素的窗口满足下面这个公式，那这个窗口就去被清掉，这个元素就会认为是迟到元素。
  窗口的最大值是固定值
  allowedLateness 是设置的固定值
  剩下来看就和watermark有关，如果有新元素不断来，一直更新watermark,那么之前这个窗口很短时间后就会被清理掉了。换个说法说，如果watermark没有更新，如果一直来的元素都满足下面的条件，那么之前的窗口就会一直输出。

window.maxTimestamp() + allowedLateness <=watermark

代码

  StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        env.setParallelism(1);

        DataStreamSource<String> localhost = env.socketTextStream("localhost", 9093);
        final OutputTag<Tuple3<String, Long, Integer>> lateTag = new OutputTag<Tuple3<String, Long, Integer>>("late-data") {
        };


        SingleOutputStreamOperator<Tuple3<String, Long, Integer>> reduce = localhost.assignTimestampsAndWatermarks(new AssignerWithPeriodicWatermarksAdapter.Strategy<>(new BoundedOutOfOrdernessTimestampExtractor<String>(Duration.ofSeconds(0)) {
                    @Override
                    public long extractTimestamp(String element) {
                        String[] split = element.split(",");
                        return Long.valueOf(split[0]);
                    }
                })).map(new MapFunction<String, Tuple3<String, Long, Integer>>() {
                    @Override
                    public Tuple3<String, Long, Integer> map(String value) throws Exception {
                        String[] split = value.split(",");
                        return new Tuple3<>(split[1], System.currentTimeMillis(), 1);
                    }
                }).keyBy(new KeySelector<Tuple3<String, Long, Integer>, String>() {

                    @Override
                    public String getKey(Tuple3<String, Long, Integer> value) throws Exception {
                        return value.f0;
                    }
                }).window(TumblingEventTimeWindows.of(Duration.ofMinutes(1))).allowedLateness(Duration.ofMinutes(1)).sideOutputLateData(lateTag).
                reduce(new ReduceFunction<Tuple3<String, Long, Integer>>() {
                    @Override
                    public Tuple3<String, Long, Integer> reduce(Tuple3<String, Long, Integer> value1, Tuple3<String, Long, Integer> value2) throws Exception {

                        value1.f2 = value1.f2 + value2.f2;
                        return value1;
                    }
                });
        reduce.print();

        reduce.getSideOutput(lateTag).print();


        try {
            env.execute("aa");
        } catch (Exception e) {
            throw new RuntimeException(e);
        }