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https://issues.apache.org/jira/browse/BEAM-10824?focusedWorklogId=481022&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-481022
]
ASF GitHub Bot logged work on BEAM-10824:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 09/Sep/20 19:41
Start Date: 09/Sep/20 19:41
Worklog Time Spent: 10m
Work Description: aaltay commented on a change in pull request #12756:
URL: https://github.com/apache/beam/pull/12756#discussion_r485870278
##########
File path: sdks/python/apache_beam/transforms/stats_test.py
##########
@@ -41,13 +40,15 @@
from apache_beam.transforms.display import DisplayData
from apache_beam.transforms.display_test import DisplayDataItemMatcher
from apache_beam.transforms.stats import ApproximateQuantilesCombineFn
+from apache_beam.transforms.stats import ApproximateUniqueCombineFn
class ApproximateUniqueTest(unittest.TestCase):
- """Unit tests for ApproximateUnique.Globally and ApproximateUnique.PerKey.
- Hash() with Python3 is nondeterministic, so Approximation algorithm generates
- different result each time and sometimes error rate is out of range, so add
- retries for all tests who actually running approximation algorithm."""
+ """Unit tests for ApproximateUnique.Globally, ApproximateUnique.PerKey,
+ and ApproximateUniqueCombineFn.
Review comment:
I did not know about py3 hash being non deterministic. That is strange.
In that case I agree with this change. Let's make it optional so that the
getting started experience does not change and any actual execution environment
could install it as needed. (i.e. add it here :
https://github.com/apache/beam/blob/master/sdks/python/container/base_image_requirements.txt
in this PR.)
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Issue Time Tracking
-------------------
Worklog Id: (was: 481022)
Remaining Estimate: 10h 20m (was: 10.5h)
Time Spent: 13h 40m (was: 13.5h)
> Hash in stats.ApproximateUniqueCombineFn NON-deterministic
> ----------------------------------------------------------
>
> Key: BEAM-10824
> URL: https://issues.apache.org/jira/browse/BEAM-10824
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Reporter: Monica Song
> Priority: P1
> Labels: hash
> Original Estimate: 24h
> Time Spent: 13h 40m
> Remaining Estimate: 10h 20m
>
> The python hash() function is non-deterministic. As a result, different
> workers will map identical values to different hashes. This leads to
> overestimation of the number of unique values (by several magnitudes, in my
> experience x1000) in a distributed processing model.
> [https://github.com/apache/beam/blob/master/sdks/python/apache_beam/transforms/stats.py#L218]
>
>
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