[
https://issues.apache.org/jira/browse/BEAM-10475?focusedWorklogId=521958&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-521958
]
ASF GitHub Bot logged work on BEAM-10475:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 09/Dec/20 00:37
Start Date: 09/Dec/20 00:37
Worklog Time Spent: 10m
Work Description: nehsyc commented on a change in pull request #13493:
URL: https://github.com/apache/beam/pull/13493#discussion_r538914797
##########
File path: sdks/python/apache_beam/transforms/util.py
##########
@@ -72,6 +72,9 @@
from apache_beam.transforms.window import NonMergingWindowFn
from apache_beam.transforms.window import TimestampCombiner
from apache_beam.transforms.window import TimestampedValue
+from apache_beam.typehints.sharded_key_type import ShardedKeyType
+from apache_beam.typehints.typehints import IterableTypeConstraint
+from apache_beam.typehints.typehints import TupleConstraint
Review comment:
Updated the code to use `Tuple` and `Iterable` directly. Couldn't add
`ShardedKeyType` to `apache_beam/typehints/__init__.py` due to circular imports
in coders
```
ImportError while loading conftest
'/usr/local/google/home/sychen/Documents/GitHub/working_dir/beam/sdks/python/conftest.py'.
conftest.py:23: in <module>
from apache_beam.options import pipeline_options
apache_beam/__init__.py:95: in <module>
from apache_beam import coders
apache_beam/coders/__init__.py:19: in <module>
from apache_beam.coders.coders import *
apache_beam/coders/coders.py:52: in <module>
from apache_beam.typehints import typehints
apache_beam/typehints/__init__.py:25: in <module>
from apache_beam.typehints.sharded_key_type import ShardedKeyType
apache_beam/typehints/sharded_key_type.py:22: in <module>
from apache_beam.coders import typecoders
apache_beam/coders/typecoders.py:81: in <module>
from apache_beam.coders.coders import CoderElementType
E ImportError: cannot import name 'CoderElementType' from partially
initialized module 'apache_beam.coders.coders' (most likely due to a circular
import)
(/usr/local/google/home/sychen/Documents/GitHub/working_dir/beam/sdks/python/apache_beam/coders/coders.py)
```
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Issue Time Tracking
-------------------
Worklog Id: (was: 521958)
Time Spent: 24h 10m (was: 24h)
> GroupIntoBatches with Runner-determined Sharding
> ------------------------------------------------
>
> Key: BEAM-10475
> URL: https://issues.apache.org/jira/browse/BEAM-10475
> Project: Beam
> Issue Type: Improvement
> Components: runner-dataflow
> Reporter: Siyuan Chen
> Assignee: Siyuan Chen
> Priority: P2
> Labels: GCP, performance
> Time Spent: 24h 10m
> Remaining Estimate: 0h
>
> [https://s.apache.org/sharded-group-into-batches|https://s.apache.org/sharded-group-into-batches__]
> Improve the existing Beam transform, GroupIntoBatches, to allow runners to
> choose different sharding strategies depending on how the data needs to be
> grouped. The goal is to help with the situation where the elements to process
> need to be co-located to reduce the overhead that would otherwise be incurred
> per element, while not losing the ability to scale the parallelism. The
> essential idea is to build a stateful DoFn with shardable states.
>
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