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https://issues.apache.org/jira/browse/BEAM-7528?focusedWorklogId=278193&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-278193
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ASF GitHub Bot logged work on BEAM-7528:
----------------------------------------
Author: ASF GitHub Bot
Created on: 17/Jul/19 11:54
Start Date: 17/Jul/19 11:54
Worklog Time Spent: 10m
Work Description: kkucharc commented on pull request #8941: [BEAM-7528]
Save load test metrics according to distribution name
URL: https://github.com/apache/beam/pull/8941#discussion_r304360938
##########
File path:
sdks/python/apache_beam/testing/load_tests/load_test_metrics_utils.py
##########
@@ -138,8 +143,25 @@ def as_dict(self):
class CounterMetric(Metric):
def __init__(self, counter_dict, submit_timestamp, metric_id):
super(CounterMetric, self).__init__(submit_timestamp, metric_id)
- self.value = counter_dict.committed
self.label = str(counter_dict.key.metric.name)
+ self.value = counter_dict.committed
+
+
+class DistributionMetrics(Metric):
Review comment:
I understand your point, calculating one value might "save" some space in
BigQuery. Unfortunately distribution metrics doesn't support with median or
other percentiles out of the box (maybe it's a good idea for feature request?)
and I am not sure if it's good idea to introduce such logic in util for reading
metrics. Mainly because in the situation when we would like save some external
(not expected in MetricsReader) metrics which we don't know what mean (but
still may be valuable for the others ex. tfx team) calculating median or any
aggregates may cause loosing meaningful info (maybe someone who defined those
external metrics needs max, min, sum or mean). Do you agree?
As it comes to time windows, also distribution doesn't store such thing. It
is possible to retrieve the step name in which metrics would be collected. And
this I can add to metric label we save.
This is confusing problem. To sum everything up:
- What to do with metrics that weren't collected in our pipeline but
somewhere deeper? It is decided to save them. But I can suggest here that it
would help to have pipeline option called `save_external_metrics`. WDYT?
- In what shape we should save metrics that we don't know nothing about
them? IMO probably as raw as possible, because we don't know what is useful for
user that collects them.
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Issue Time Tracking
-------------------
Worklog Id: (was: 278193)
Time Spent: 5h 20m (was: 5h 10m)
> Save correctly Python Load Tests metrics according to it's namespace
> --------------------------------------------------------------------
>
> Key: BEAM-7528
> URL: https://issues.apache.org/jira/browse/BEAM-7528
> Project: Beam
> Issue Type: Bug
> Components: testing
> Reporter: Kasia Kucharczyk
> Assignee: Kasia Kucharczyk
> Priority: Major
> Time Spent: 5h 20m
> Remaining Estimate: 0h
>
> Bug discovered when metrics monitored more than one distribution and saved
> all as `runtime`.
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