【随记】Flink 时间窗口的起始时间_flink 获取每个窗口起始时间

话不多说，直接上手今天的主题，探索一个容易让人忽略和困惑的问题：Flink 时间窗口的起始时间

就以最简单的demo为例：

timeWindow(Time.seconds(5))

       上述定义一个步长为5s的滚动窗口，就以这个简单的入口进入Flink的源码开始探索

1）timeWindow的定义

public WindowedStream<T, KEY, TimeWindow> timeWindow(Time size) {
    if (environment.getStreamTimeCharacteristic() == TimeCharacteristic.ProcessingTime) {
		    return window(TumblingProcessingTimeWindows.of(size));
    } else {
		    return window(TumblingEventTimeWindows.of(size));
    }
}

       这段源码比较贴近大众，就是一个普通的判断，而且environment.getStreamTimeCharacteristic()这个东西我们再熟悉不过了，判断当前是ProcessingTime还是EventTime，当然除了EventTime还有IngestionTime，但是比较常用的还是ProcessingTime和EventTime，所以我们就非ProcessingTime即EventTime这样理解，因为生产环境比较常用的是EventTime，所以我们就进入else的代码继续查看

2）TumblingEventTimeWindows的定义

window(TumblingEventTimeWindows.of(size))这段代码，window利用TumblingEventTimeWindows来分配元素，所以我们要了解的核心是TumblingEventTimeWindows.of(size)的定义

public static TumblingEventTimeWindows of(Time size) {
	return new TumblingEventTimeWindows(size.toMilliseconds(), 0);
}
 
 
protected TumblingEventTimeWindows(long size, long offset) {
	if (Math.abs(offset) >= size) {
			throw new IllegalArgumentException
            ("TumblingEventTimeWindows parameters must satisfy abs(offset) < size");
	}
 
	this.size = size;
	this.offset = offset;
}

可以看到通过of方法我们构建了一个offset为0，size为5的TumblingEventTimeWindows对象，然后就是我们需要的核心方法，assignWindows，窗口分配元素的核心方法

@Override
public Collection<TimeWindow> assignWindows(Object element, long timestamp, WindowAssignerContext context) {
	if (timestamp > Long.MIN_VALUE) {
		// Long.MIN_VALUE is currently assigned when no timestamp is present
		long start = TimeWindow.getWindowStartWithOffset(timestamp, offset, size);
		return Collections.singletonList(new TimeWindow(start, start + size));
	} else {
		throw new RuntimeException(
             "Record has Long.MIN_VALUE timestamp (= no timestamp marker). " +
             "Is the time characteristic set to 'ProcessingTime', 
             or did you forget to call " +
            "'DataStream.assignTimestampsAndWatermarks(...)'?");
	}
}

重点来了

long start = TimeWindow.getWindowStartWithOffset(timestamp, offset, size);

/**
  * Method to get the window start for a timestamp.
  *
  * @param timestamp epoch millisecond to get the window start.
  * @param offset The offset which window start would be shifted by.
  * @param windowSize The size of the generated windows.
  * @return window start
*/
public static long getWindowStartWithOffset(long timestamp, long offset, long windowSize) {
	return timestamp - (timestamp - offset + windowSize) % windowSize;
}

Method to get the window start for a timestamp.翻译过来就是这个方法用来获取窗口的开始时间戳

核心算法就是

timestamp - (timestamp - offset + windowSize) % windowSize

 上一段代码小测一下

  case class TestData(timestamp:Long,word:String)
 
  def main(args: Array[String]): Unit = {
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
    // 便于输出，设置并行度为1
    env.setParallelism(1)
    val socketStream = env.socketTextStream("localhost",9999)
    val windowedStream = socketStream
        .map(row=>TestData(row.split(" ")(0).toLong,row.split(" ")(0)))
        .assignTimestampsAndWatermarks(new             
           BoundedOutOfOrdernessTimestampExtractor[TestData](Time.seconds(1)) {
            override def extractTimestamp(element: TestData): Long 
                = element.timestamp * 1000
           })
        .keyBy(_.word)
        .timeWindow(Time.seconds(5))
        .reduce((r1,r2)=>TestData(r1.timestamp,"hello "+r2.word))
    windowedStream.print("window output is")
    socketStream.print("input data is")
    env.execute("window_test_job")
  }

准备一下测试数据
1599623712 word（2020-09-09 11:55:12）
1599623715 word（2020-09-09 11:55:15）

根据公式算出开始时间：
 
1599623712 - (1599623712 - 0 + 5) % 5 == 1599623710
 
也就是开始时间为 1599623710，步长为5s，也就是下次触发窗口计算为1599623715

验证一下：
    nc录入数据：

1599623712 word
1599623715 word

    控制台输出结果：

input data is> 1599623712 word
input data is> 1599623715 word
window output is> TestData(1599623712,word)

结果验证了公式结果即为窗口的开始时间，ProcessingTime与之类似就不测试了，其实也可以看到公式的计算结果一般为自然时间的开始，如2020-09-09 11:55:12的开始时间为2020-09-09 11:55:10