Watermark 案例

/**
 *
 * Watermark 案例
 *
 * Created by xuwei.tech.
 */

```java
public class StreamingWindowWatermark {
    
    
 
    public static void main(String[] args) throws Exception {
    
    
        //定义socket的端口号
        int port = 9000;
        //获取运行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
 
        //设置使用eventtime，默认是使用processtime
        env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
 
        //设置并行度为1,默认并行度是当前机器的cpu数量
        env.setParallelism(1);
 
        //连接socket获取输入的数据
        DataStream<String> text = env.socketTextStream("hadoop100", port, "\n");
 
        //解析输入的数据
        DataStream<Tuple2<String, Long>> inputMap = text.map(new MapFunction<String, Tuple2<String, Long>>() {
    
    
            @Override
            public Tuple2<String, Long> map(String value) throws Exception {
    
    
                String[] arr = value.split(",");
                return new Tuple2<>(arr[0], Long.parseLong(arr[1]));
            }
        });
 
        //抽取timestamp和生成watermark
        DataStream<Tuple2<String, Long>> waterMarkStream = inputMap.assignTimestampsAndWatermarks(
			new AssignerWithPeriodicWatermarks<Tuple2<String, Long>>() {
    
    
 
            Long currentMaxTimestamp = 0L;
            final Long maxOutOfOrderness = 10000L;// 最大允许的乱序时间是10s
 
            SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss.SSS");
            /**
             * 定义生成watermark的逻辑
             * 默认100ms被调用一次
             */
            @Nullable
            @Override
            public Watermark getCurrentWatermark() {
    
    
                return new Watermark(currentMaxTimestamp - maxOutOfOrderness);
            }
 
            //定义如何提取timestamp
            @Override
            public long extractTimestamp(Tuple2<String, Long> element, long previousElementTimestamp) {
    
    
                long timestamp = element.f1;
                currentMaxTimestamp = Math.max(timestamp, currentMaxTimestamp);
                System.out.println("key:"+element.f0+",eventtime:["+element.f1+"|"+sdf.format(element.f1)+"],currentMaxTimestamp:["+currentMaxTimestamp+"|"+
                        sdf.format(currentMaxTimestamp)+"],watermark:["+getCurrentWatermark().getTimestamp()+"|"+sdf.format(getCurrentWatermark().getTimestamp())+"]");
                return timestamp;
            }
        });
 
        //分组，聚合
        DataStream<String> window = waterMarkStream.keyBy(0)
                .window(TumblingEventTimeWindows.of(Time.seconds(3)))//按照消息的EventTime分配窗口，和调用TimeWindow效果一样
                .apply(new WindowFunction<Tuple2<String, Long>, String, Tuple, TimeWindow>() {
    
    
                    /**
                     * 对window内的数据进行排序，保证数据的顺序
                     * @param tuple
                     * @param window
                     * @param input
                     * @param out
                     * @throws Exception
                     */
                    @Override
                    public void apply(Tuple tuple, TimeWindow window, Iterable<Tuple2<String, Long>> input, Collector<String> out) throws Exception {
    
    
                        String key = tuple.toString();
                        List<Long> arrarList = new ArrayList<Long>();
                        Iterator<Tuple2<String, Long>> it = input.iterator();
                        while (it.hasNext()) {
    
    
                            Tuple2<String, Long> next = it.next();
                            arrarList.add(next.f1);
                        }
                        Collections.sort(arrarList);
                        SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss.SSS");
                        String result = key + "," + arrarList.size() + "," + sdf.format(arrarList.get(0)) + "," + sdf.format(arrarList.get(arrarList.size() - 1))
                                + "," + sdf.format(window.getStart()) + "," + sdf.format(window.getEnd());
                        out.collect(result);
                    }
                });
        //测试-把结果打印到控制台即可
        window.print();
 
        //注意：因为flink是懒加载的，所以必须调用execute方法，上面的代码才会执行
        env.execute("eventtime-watermark");
 
    }
 
}