后期数据处理|阿帕奇光束 [英] Late data handling | Apache Beam

问题描述

如

Late data which has missed the window and .withAllowedLateness period is dropped off from the pipeline as documented here

I have a few questions on this behavior:

1. How to handle late data which is dropped off from the pipeline? Can we add default behavior? Say all late data should be logged somewhere like catch-all bucket?
2. Can we have a Metric(Google Dataflow Metrics/Beam) to say how many of these messages are dropped off from pipeline due to huge latency?

解决方案

1. In general we define late data as elements that, by the time they arrive, we just prefer to drop them and do not want to process any further. As far as I know, adding extra functionality to handle those messages would require substantial effort to modify the Java SDK. However, if you just want to log them this is done by the LateDataDroppingDoFnRunner code, which is responsible for dropping data from expired windows:

for (WindowedValue<InputT> input : concatElements) {
  BoundedWindow window = Iterables.getOnlyElement(input.getWindows());
  if (canDropDueToExpiredWindow(window)) {
    // The element is too late for this window.
    droppedDueToLateness.inc();
    WindowTracing.debug(
        "{}: Dropping element at {} for key:{}; window:{} "
            + "since too far behind inputWatermark:{}; outputWatermark:{}",
        LateDataFilter.class.getSimpleName(),
        input.getTimestamp(),
        key,
        window,
        timerInternals.currentInputWatermarkTime(),
        timerInternals.currentOutputWatermarkTime());
  }
}

Note that the log has DEBUG level so you might not see it. As explained here, to override the level in Dataflow, you can use --defaultWorkerLogLevel=DEBUG or, even better, specify a particular class such as --workerLogLevelOverrides={"org.apache.beam.sdk.util.WindowTracing":"DEBUG"}. Choosing your keys wisely can help expose information to identify the dropped message (i.e. data lineage).

2. As can be seen in the previous snippet, droppedDueToLateness is a Counter metric that is incremented each time we drop an element: droppedDueToLateness.inc();. You can monitor it using Stackdriver with resource type dataflow_job and metric custom.googleapis.com/dataflow/droppedDueToLateness.

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