Flink 自定义触发器实现带超时时间的 CountWindow-技术圈

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Flink 的 window 有两个基本款，TimeWindow 和 CountWindow。
TimeWindow 是到时间就触发窗口，CountWindow 是到数量就触发。

如果我需要到时间就触发，并且到时间之前如果已经积累了足够数量的数据；或者在限定时间内没有积累足够数量的数据，我依然希望触发窗口业务，那么就需要自定义触发器。

import org.apache.flink.api.common.functions.ReduceFunction;import org.apache.flink.api.common.state.ReducingState;import org.apache.flink.api.common.state.ReducingStateDescriptor;import org.apache.flink.api.common.typeutils.base.LongSerializer;import org.apache.flink.streaming.api.TimeCharacteristic;import org.apache.flink.streaming.api.windowing.triggers.Trigger;import org.apache.flink.streaming.api.windowing.triggers.TriggerResult;import org.apache.flink.streaming.api.windowing.windows.TimeWindow;import org.slf4j.Logger;import org.slf4j.LoggerFactory;
/** * 带超时的计数窗口触发器 */public class CountTriggerWithTimeout<T> extends Trigger<T, TimeWindow> {    private static Logger LOG = LoggerFactory.getLogger(CountTriggerWithTimeout.class);
    /**     * 窗口最大数据量     */    private int maxCount;    /**     * event time / process time     */    private TimeCharacteristic timeType;    /**     * 用于储存窗口当前数据量的状态对象     */    private ReducingStateDescriptor countStateDescriptor =            new ReducingStateDescriptor("counter", new Sum(), LongSerializer.INSTANCE);

    public CountTriggerWithTimeout(int maxCount, TimeCharacteristic timeType) {
        this.maxCount = maxCount;        this.timeType = timeType;    }

    private TriggerResult fireAndPurge(TimeWindow window, TriggerContext ctx) throws Exception {        clear(window, ctx);        return TriggerResult.FIRE_AND_PURGE;    }

    @Override    public TriggerResult onElement(T element, long timestamp, TimeWindow window, TriggerContext ctx) throws Exception {        ReducingState countState = ctx.getPartitionedState(countStateDescriptor);        countState.add(1L);
        if (countState.get() >= maxCount) {            LOG.info("fire with count: " + countState.get());            return fireAndPurge(window, ctx);        }        if (timestamp >= window.getEnd()) {            LOG.info("fire with tiem: " + timestamp);            return fireAndPurge(window, ctx);        } else {            return TriggerResult.CONTINUE;        }    }
    @Override    public TriggerResult onProcessingTime(long time, TimeWindow window, TriggerContext ctx) throws Exception {        if (timeType != TimeCharacteristic.ProcessingTime) {            return TriggerResult.CONTINUE;        }
        if (time >= window.getEnd()) {            return TriggerResult.CONTINUE;        } else {            LOG.info("fire with process tiem: " + time);            return fireAndPurge(window, ctx);        }    }
    @Override    public TriggerResult onEventTime(long time, TimeWindow window, TriggerContext ctx) throws Exception {        if (timeType != TimeCharacteristic.EventTime) {            return TriggerResult.CONTINUE;        }
        if (time >= window.getEnd()) {            return TriggerResult.CONTINUE;        } else {            LOG.info("fire with event tiem: " + time);            return fireAndPurge(window, ctx);        }    }
    @Override    public void clear(TimeWindow window, TriggerContext ctx) throws Exception {        ReducingState countState = ctx.getPartitionedState(countStateDescriptor);        countState.clear();    }
    /**     * 计数方法     */    class Sum implements ReduceFunction<Long> {
        @Override        public Long reduce(Long value1, Long value2) throws Exception {            return value1 + value2;        }    }}

使用示例（超时时间 10 秒，数据量上限 1000）：

stream        .timeWindowAll(Time.seconds(10))        .trigger(                new CountTriggerWithTimeout(1000, TimeCharacteristic.ProcessingTime)        )        .process(new XxxxWindowProcessFunction())        .addSink(new XxxSinkFunction())        .name("Xxx");

即可。

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