ihji commented on a change in pull request #12754:
URL: https://github.com/apache/beam/pull/12754#discussion_r483286311
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File path: sdks/python/apache_beam/io/gcp/bigquery.py
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@@ -1198,8 +1209,34 @@ def process(self, element, *schema_side_inputs):
return self._flush_all_batches()
def finish_bundle(self):
+ current_millis = int(time.time() * 1000)
+ if BigQueryWriteFn.LATENCY_LOGGING_LOCK.acquire(False):
+ try:
+ if (BigQueryWriteFn.LATENCY_LOGGING_HISTOGRAM.total_count() > 0 and
+ (current_millis -
+ BigQueryWriteFn.LATENCY_LOGGING_LAST_REPORTED_MILLIS) >
+ self._latency_logging_frequency * 1000):
+ self._log_percentiles()
+ BigQueryWriteFn.LATENCY_LOGGING_HISTOGRAM.clear()
Review comment:
> Is there a reason why you clear? I think we need to have a good sample
of elements over a period of time to a decent latency breakdown. This seems
like it will be cleared quite frequently.
The default interval is 3 minutes so it isn't cleared that frequently. And
also the interval is configurable so we could increase it by specifying a
pipeline option.
> In the logging case, we would like to have something similar. I'm not
saying you need to make such a complex calculation to move things in and out of
the window.
Yes, it would have been great if we used sliding window for histogram
recording. We could improve the histogram object with time awareness in the
future.
> Though, maybe this is perfectly fine, for 180 seconds we can probably
record a decent number of requests.
😄
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