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https://issues.apache.org/jira/browse/BEAM-11986?focusedWorklogId=671057&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-671057
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ASF GitHub Bot logged work on BEAM-11986:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 27/Oct/21 21:32
Start Date: 27/Oct/21 21:32
Worklog Time Spent: 10m
Work Description: pabloem commented on pull request #15294:
URL: https://github.com/apache/beam/pull/15294#issuecomment-953327915
oh yeah I know why. `MetricsEnvironment` is a runtime class that a runner
utilizes at runtime. `MetricsEnvironment` will give you metrics info if the job
runs locally, but not if the job runs on Dataflow.
After looking at other metrics tests, they all test mocked-out instances of
BQ/BigTable, etc.
So - I think you should make these tests run only on DirectRunner, and skip
on Dataflow.
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Issue Time Tracking
-------------------
Worklog Id: (was: 671057)
Time Spent: 17h 20m (was: 17h 10m)
> Python Spanner - Implement IO Request Count metric
> --------------------------------------------------
>
> Key: BEAM-11986
> URL: https://issues.apache.org/jira/browse/BEAM-11986
> Project: Beam
> Issue Type: Test
> Components: io-py-gcp
> Reporter: Alex Amato
> Priority: P3
> Time Spent: 17h 20m
> Remaining Estimate: 0h
>
> Reference PRs (See BigQuery IO example) and detailed explanation of what's
> needed to instrument this IO with Request Count metrics is found in this
> handoff doc:
> [https://docs.google.com/document/d/1lrz2wE5Dl4zlUfPAenjXIQyleZvqevqoxhyE85aj4sc/edit'|https://docs.google.com/document/d/1lrz2wE5Dl4zlUfPAenjXIQyleZvqevqoxhyE85aj4sc/edit'?authuser=0]
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