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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;
}
}
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<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;
}
}
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