• Flink流式计算


    Structured Streaming

    1. A stream is converted into a dynamic table.
    2. A continuous query is evaluated on the dynamic table yielding a new dynamic table.
    3. The resulting dynamic table is converted back into a stream.

    Defining a Table on a Stream

     Continuous Queries

    Handling Event-time

    TUMBLE(time_attr, interval),定义一个个连续的时间窗口,这样每行数据只可能出现在一个窗口内,窗口之间不会出现重叠Defines a tumbling time window. A tumbling time window assigns rows to non-overlapping, continuous windows with a fixed duration (interval). For example, a tumbling window of 5 minutes groups rows in 5 minutes intervals. Tumbling windows can be defined on event-time (stream + batch) or processing-time (stream).
    TUMBLE_START(time_attr, interval). 返回时间窗口的下限时间戳.Returns the timestamp of the inclusive lower bound of the corresponding tumbling, hopping, or session window.

    Handling Late Data

    Bob 12:54:00 ./xxx 到达时间14:01:00如何处理?

    Watermarks定义在cTime,允许延迟2hour, 14:00:00-2hour<13:00:00,窗口12:00:00-13::00:00仍保持
    Watermarks定义在cTime,允许延迟5min,14:00:00-5min>13:00:00,时间窗口12:00:00-13:00:00已过期,数据被丢弃

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  • 原文地址:https://www.cnblogs.com/killianxu/p/11026800.html
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