聊聊flink的Sliding Window-白红宇

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本文主要研究一下flink的Sliding Window

SlidingEventTimeWindows

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/windowing/assigners/SlidingEventTimeWindows.java

@PublicEvolvingpublic class SlidingEventTimeWindows extends WindowAssigner
    
      {	private static final long serialVersionUID = 1L;	private final long size;	private final long slide;	private final long offset;	protected SlidingEventTimeWindows(long size, long slide, long offset) {		if (offset < 0 || offset >= slide || size <= 0) {			throw new IllegalArgumentException("SlidingEventTimeWindows parameters must satisfy 0 <= offset < slide and size > 0");		}		this.size = size;		this.slide = slide;		this.offset = offset;	}	@Override	public Collection
     
       assignWindows(Object element, long timestamp, WindowAssignerContext context) {		if (timestamp > Long.MIN_VALUE) {			List
      
        windows = new ArrayList<>((int) (size / slide));			long lastStart = TimeWindow.getWindowStartWithOffset(timestamp, offset, slide);			for (long start = lastStart;				start > timestamp - size;				start -= slide) {				windows.add(new TimeWindow(start, start + size));			}			return windows;		} 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(...)'?");		}	}	public long getSize() {		return size;	}	public long getSlide() {		return slide;	}	@Override	public Trigger
       
         getDefaultTrigger(StreamExecutionEnvironment env) {		return EventTimeTrigger.create();	}	@Override	public String toString() {		return "SlidingEventTimeWindows(" + size + ", " + slide + ")";	}	public static SlidingEventTimeWindows of(Time size, Time slide) {		return new SlidingEventTimeWindows(size.toMilliseconds(), slide.toMilliseconds(), 0);	}	public static SlidingEventTimeWindows of(Time size, Time slide, Time offset) {		return new SlidingEventTimeWindows(size.toMilliseconds(), slide.toMilliseconds(),			offset.toMilliseconds() % slide.toMilliseconds());	}	@Override	public TypeSerializer
        
          getWindowSerializer(ExecutionConfig executionConfig) {		return new TimeWindow.Serializer();	}	@Override	public boolean isEventTime() {		return true;	}}复制代码

SlidingEventTimeWindows继承了Window，其中元素类型为Object，而窗口类型为TimeWindow；它有三个参数，一个是size，一个是slide，一个是offset，其中offset必须大于等于0，offset必须大于slide，size必须大于0

assignWindows方法以slide作为size通过TimeWindow.getWindowStartWithOffset(timestamp, offset, slide)计算lastStart，然后以为start + size > timestamp为循环条件，每次对start减去slide，挨个计算TimeWindow(start, start + size)；getDefaultTrigger方法返回的是EventTimeTrigger；getWindowSerializer方法返回的是TimeWindow.Serializer()；isEventTime返回的为true

SlidingEventTimeWindows提供了of静态工厂方法，可以指定size、slide及offset参数，它对于传入的offset参数转为毫秒然后与slide.toMilliseconds()取余作为最后的offset值

SlidingProcessingTimeWindows

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/windowing/assigners/SlidingProcessingTimeWindows.java

public class SlidingProcessingTimeWindows extends WindowAssigner
    
      {	private static final long serialVersionUID = 1L;	private final long size;	private final long offset;	private final long slide;	private SlidingProcessingTimeWindows(long size, long slide, long offset) {		if (offset < 0 || offset >= slide || size <= 0) {			throw new IllegalArgumentException("SlidingProcessingTimeWindows parameters must satisfy 0 <= offset < slide and size > 0");		}		this.size = size;		this.slide = slide;		this.offset = offset;	}	@Override	public Collection
     
       assignWindows(Object element, long timestamp, WindowAssignerContext context) {		timestamp = context.getCurrentProcessingTime();		List
      
        windows = new ArrayList<>((int) (size / slide));		long lastStart = TimeWindow.getWindowStartWithOffset(timestamp, offset, slide);		for (long start = lastStart;			start > timestamp - size;			start -= slide) {			windows.add(new TimeWindow(start, start + size));		}		return windows;	}	public long getSize() {		return size;	}	public long getSlide() {		return slide;	}	@Override	public Trigger
       
         getDefaultTrigger(StreamExecutionEnvironment env) {		return ProcessingTimeTrigger.create();	}	@Override	public String toString() {		return "SlidingProcessingTimeWindows(" + size + ", " + slide + ")";	}	public static SlidingProcessingTimeWindows of(Time size, Time slide) {		return new SlidingProcessingTimeWindows(size.toMilliseconds(), slide.toMilliseconds(), 0);	}	public static SlidingProcessingTimeWindows of(Time size, Time slide, Time offset) {		return new SlidingProcessingTimeWindows(size.toMilliseconds(), slide.toMilliseconds(),			offset.toMilliseconds() % slide.toMilliseconds());	}	@Override	public TypeSerializer
        
          getWindowSerializer(ExecutionConfig executionConfig) {		return new TimeWindow.Serializer();	}	@Override	public boolean isEventTime() {		return false;	}}复制代码

SlidingProcessingTimeWindows继承了Window，其中元素类型为Object，而窗口类型为TimeWindow；它有三个参数，一个是size，一个是slide，一个是offset，其中offset必须大于等于0，offset必须大于slide，size必须大于0

assignWindows方法以slide作为size通过TimeWindow.getWindowStartWithOffset(timestamp, offset, slide)计算lastStart(与SlidingEventTimeWindows不同的是SlidingProcessingTimeWindows的这个方法里头使用context.getCurrentProcessingTime()值重置了timestamp)，然后以为start + size > timestamp为循环条件，每次对start减去slide，挨个计算TimeWindow(start, start + size)；getDefaultTrigger方法返回的是ProcessingTimeTrigger；getWindowSerializer方法返回的是TimeWindow.Serializer()；isEventTime返回的为false

SlidingEventTimeWindows提供了of静态工厂方法，可以指定size、slide及offset参数，它对于传入的offset参数转为毫秒然后与slide.toMilliseconds()取余作为最后的offset值

小结

flink的Sliding Window分为SlidingEventTimeWindows及SlidingProcessingTimeWindows，它们都继承了WindowAssigner，其中元素类型为Object，而窗口类型为TimeWindow；它有三个参数，一个是size，一个是slide，一个是offset，其中offset必须大于等于0，offset必须大于slide，size必须大于0

WindowAssigner定义了assignWindows、getDefaultTrigger、getWindowSerializer、isEventTime这几个抽象方法，同时定义了抽象静态类WindowAssignerContext；它有两个泛型，其中T为元素类型，而W为窗口类型；SlidingEventTimeWindows及SlidingProcessingTimeWindows的窗口类型为TimeWindow，它有start及end属性，其中start为inclusive，而end为exclusive，maxTimestamp返回的是end-1，它还提供了mergeWindows及getWindowStartWithOffset静态方法；前者用于合并重叠的时间窗口，后者用于获取指定timestamp、offset、windowSize的window start

SlidingEventTimeWindows及SlidingProcessingTimeWindows的不同在于assignWindows、getDefaultTrigger、isEventTime方法；前者assignWindows使用的是参数中的timestamp，而后者使用的是context.getCurrentProcessingTime()；前者的getDefaultTrigger返回的是EventTimeTrigger，而后者返回的是ProcessingTimeTrigger；前者isEventTime方法返回的为true，而后者返回的为false

序

SlidingEventTimeWindows

SlidingProcessingTimeWindows

小结

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