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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
@PublicEvolving
public class SlidingEventTimeWindows extends WindowAssigner<Object, TimeWindow> {
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<TimeWindow> assignWindows(Object element, long timestamp, WindowAssignerContext context) {
if (timestamp > Long.MIN_VALUE) {
List<TimeWindow> 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<Object, TimeWindow> 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<TimeWindow> getWindowSerializer(ExecutionConfig executionConfig) {
return new TimeWindow.Serializer();
}
@Override
public boolean isEventTime() {
return true;
}
}
- 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<Object, TimeWindow> {
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<TimeWindow> assignWindows(Object element, long timestamp, WindowAssignerContext context) {
timestamp = context.getCurrentProcessingTime();
List<TimeWindow> 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<Object, TimeWindow> 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<TimeWindow> getWindowSerializer(ExecutionConfig executionConfig) {
return new TimeWindow.Serializer();
}
@Override
public boolean isEventTime() {
return false;
}
}
- 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
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