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https://issues.apache.org/jira/browse/BEAM-12529?focusedWorklogId=614776&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-614776
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ASF GitHub Bot logged work on BEAM-12529:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 25/Jun/21 00:11
Start Date: 25/Jun/21 00:11
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on a change in pull request
#15073:
URL: https://github.com/apache/beam/pull/15073#discussion_r658365970
##########
File path: sdks/python/apache_beam/dataframe/schemas.py
##########
@@ -305,7 +305,7 @@ def _dtype_to_fieldtype(dtype):
elif dtype.kind == 'S':
return bytes
else:
- raise TypeError("Unsupported dtype in proxy: '%s'" % dtype)
+ return Any
Review comment:
Note the execution time unbatching code "just works" because it always
iterates over the Series' values. The only thing blocking this was finding an
appropriate type mapping.
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Issue Time Tracking
-------------------
Worklog Id: (was: 614776)
Time Spent: 20m (was: 10m)
> to_pcollection does not support timestamp types
> -----------------------------------------------
>
> Key: BEAM-12529
> URL: https://issues.apache.org/jira/browse/BEAM-12529
> Project: Beam
> Issue Type: Improvement
> Components: dsl-dataframe
> Reporter: Brian Hulette
> Assignee: Brian Hulette
> Priority: P2
> Fix For: 2.32.0
>
> Time Spent: 20m
> Remaining Estimate: 0h
>
> We do not currently support converting timestamps directly from a deferred
> dataframe to a schema'd PCollection. It will raise an error like:
> {code}
> TypeError: Unsupported dtype in proxy: 'datetime64[ns]'
> {code}
> Note that pandas timestamps are nanosecond precision by default, while Beam's
> Timestamp type is microsecond precision.
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