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聊聊flink的window操作

聊聊flink的window操作

作者: go4it | 来源:发表于2019-01-01 11:49 被阅读41次

    本文主要研究一下flink的window操作

    window

    DataStream

    flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/DataStream.java

        public AllWindowedStream<T, TimeWindow> timeWindowAll(Time size) {
            if (environment.getStreamTimeCharacteristic() == TimeCharacteristic.ProcessingTime) {
                return windowAll(TumblingProcessingTimeWindows.of(size));
            } else {
                return windowAll(TumblingEventTimeWindows.of(size));
            }
        }
    
        public AllWindowedStream<T, TimeWindow> timeWindowAll(Time size, Time slide) {
            if (environment.getStreamTimeCharacteristic() == TimeCharacteristic.ProcessingTime) {
                return windowAll(SlidingProcessingTimeWindows.of(size, slide));
            } else {
                return windowAll(SlidingEventTimeWindows.of(size, slide));
            }
        }
    
        public AllWindowedStream<T, GlobalWindow> countWindowAll(long size) {
            return windowAll(GlobalWindows.create()).trigger(PurgingTrigger.of(CountTrigger.of(size)));
        }
    
        public AllWindowedStream<T, GlobalWindow> countWindowAll(long size, long slide) {
            return windowAll(GlobalWindows.create())
                    .evictor(CountEvictor.of(size))
                    .trigger(CountTrigger.of(slide));
        }
    
        @PublicEvolving
        public <W extends Window> AllWindowedStream<T, W> windowAll(WindowAssigner<? super T, W> assigner) {
            return new AllWindowedStream<>(this, assigner);
        }
    
    • 对于非KeyedStream,有timeWindowAll、countWindowAll、windowAll操作,其中最主要的是windowAll操作,它的parallelism为1,它需要一个WindowAssigner参数,返回的是AllWindowedStream

    KeyedStream

    flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/KeyedStream.java

        public WindowedStream<T, KEY, TimeWindow> timeWindow(Time size) {
            if (environment.getStreamTimeCharacteristic() == TimeCharacteristic.ProcessingTime) {
                return window(TumblingProcessingTimeWindows.of(size));
            } else {
                return window(TumblingEventTimeWindows.of(size));
            }
        }
    
        public WindowedStream<T, KEY, TimeWindow> timeWindow(Time size, Time slide) {
            if (environment.getStreamTimeCharacteristic() == TimeCharacteristic.ProcessingTime) {
                return window(SlidingProcessingTimeWindows.of(size, slide));
            } else {
                return window(SlidingEventTimeWindows.of(size, slide));
            }
        }
    
        public WindowedStream<T, KEY, GlobalWindow> countWindow(long size) {
            return window(GlobalWindows.create()).trigger(PurgingTrigger.of(CountTrigger.of(size)));
        }
    
        public WindowedStream<T, KEY, GlobalWindow> countWindow(long size, long slide) {
            return window(GlobalWindows.create())
                    .evictor(CountEvictor.of(size))
                    .trigger(CountTrigger.of(slide));
        }
    
        @PublicEvolving
        public <W extends Window> WindowedStream<T, KEY, W> window(WindowAssigner<? super T, W> assigner) {
            return new WindowedStream<>(this, assigner);
        }
    
    • 对于KeyedStream除了继承了DataStream的window相关操作,它主要用的是timeWindow、countWindow、window操作,其中最主要的是window操作,它也需要一个WindowAssigner参数,返回的是WindowedStream

    WindowedStream

    flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/WindowedStream.java

    @Public
    public class WindowedStream<T, K, W extends Window> {
    
        /** The keyed data stream that is windowed by this stream. */
        private final KeyedStream<T, K> input;
    
        /** The window assigner. */
        private final WindowAssigner<? super T, W> windowAssigner;
    
        /** The trigger that is used for window evaluation/emission. */
        private Trigger<? super T, ? super W> trigger;
    
        /** The evictor that is used for evicting elements before window evaluation. */
        private Evictor<? super T, ? super W> evictor;
    
        /** The user-specified allowed lateness. */
        private long allowedLateness = 0L;
    
        /**
         * Side output {@code OutputTag} for late data. If no tag is set late data will simply be
         * dropped.
         */
        private OutputTag<T> lateDataOutputTag;
    
        @PublicEvolving
        public WindowedStream(KeyedStream<T, K> input,
                WindowAssigner<? super T, W> windowAssigner) {
            this.input = input;
            this.windowAssigner = windowAssigner;
            this.trigger = windowAssigner.getDefaultTrigger(input.getExecutionEnvironment());
        }
    
        @PublicEvolving
        public WindowedStream<T, K, W> trigger(Trigger<? super T, ? super W> trigger) {
            if (windowAssigner instanceof MergingWindowAssigner && !trigger.canMerge()) {
                throw new UnsupportedOperationException("A merging window assigner cannot be used with a trigger that does not support merging.");
            }
    
            if (windowAssigner instanceof BaseAlignedWindowAssigner) {
                throw new UnsupportedOperationException("Cannot use a " + windowAssigner.getClass().getSimpleName() + " with a custom trigger.");
            }
    
            this.trigger = trigger;
            return this;
        }
    
        @PublicEvolving
        public WindowedStream<T, K, W> allowedLateness(Time lateness) {
            final long millis = lateness.toMilliseconds();
            checkArgument(millis >= 0, "The allowed lateness cannot be negative.");
    
            this.allowedLateness = millis;
            return this;
        }
    
        @PublicEvolving
        public WindowedStream<T, K, W> sideOutputLateData(OutputTag<T> outputTag) {
            Preconditions.checkNotNull(outputTag, "Side output tag must not be null.");
            this.lateDataOutputTag = input.getExecutionEnvironment().clean(outputTag);
            return this;
        }
    
        @PublicEvolving
        public WindowedStream<T, K, W> evictor(Evictor<? super T, ? super W> evictor) {
            if (windowAssigner instanceof BaseAlignedWindowAssigner) {
                throw new UnsupportedOperationException("Cannot use a " + windowAssigner.getClass().getSimpleName() + " with an Evictor.");
            }
            this.evictor = evictor;
            return this;
        }
    
        // ------------------------------------------------------------------------
        //  Operations on the keyed windows
        // ------------------------------------------------------------------------
    
        //......
    }
    
    • WindowedStream有几个参数,其中构造器要求的是input及windowAssigner参数,然后还有Trigger、Evictor、allowedLateness、OutputTag这几个可选参数;另外还必须设置operation function,主要有ReduceFunction、AggregateFunction、FoldFunction(废弃)、ProcessWindowFunction这几个
    • windowAssigner主要用来决定元素如何划分到window中,这里主要有TumblingEventTimeWindows/TumblingProcessingTimeWindows、SlidingEventTimeWindows/SlidingProcessingTimeWindows、EventTimeSessionWindows/ProcessingTimeSessionWindows、GlobalWindows这几个
    • Trigger用来触发window的发射,Evictor用来在发射window的时候剔除元素,allowedLateness用于指定允许元素落后于watermark的最大时间,超出则被丢弃(仅仅对于event-time window有效),OutputTag用于将late数据输出到side output,可以通过SingleOutputStreamOperator.getSideOutput(OutputTag)方法来获取

    AllWindowedStream的属性/操作基本跟WindowedStream类似,这里就不详细展开

    小结

    • window操作是处理无限数据流的核心,它将数据流分割为有限大小的buckets,然后就可以在这些有限数据上进行相关的操作。flink的window操作主要分为两大类,一类是针对KeyedStream的window操作,一个是针对non-key stream的windowAll操作
    • window操作主要有几个参数,WindowAssigner是必不可少的参数,主要有TumblingEventTimeWindows/TumblingProcessingTimeWindows、SlidingEventTimeWindows/SlidingProcessingTimeWindows、EventTimeSessionWindows/ProcessingTimeSessionWindows、GlobalWindows这几个;另外还必须设置operation function,主要有ReduceFunction、AggregateFunction、FoldFunction(废弃)、ProcessWindowFunction这几个
    • Trigger、Evictor、allowedLateness、OutputTag这几个为可选参数,Trigger用来触发window的发射,Evictor用来在发射window的时候剔除元素,allowedLateness用于指定允许元素落后于watermark的最大时间,超出则被丢弃(仅仅对于event-time window有效),OutputTag用于将late数据输出到side output,可以通过SingleOutputStreamOperator.getSideOutput(OutputTag)方法来获取

    doc

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