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https://issues.apache.org/jira/browse/BEAM-12246?focusedWorklogId=598192&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-598192
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ASF GitHub Bot logged work on BEAM-12246:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 17/May/21 18:42
Start Date: 17/May/21 18:42
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on a change in pull request
#14778:
URL: https://github.com/apache/beam/pull/14778#discussion_r633767654
##########
File path: sdks/python/apache_beam/runners/interactive/recording_manager.py
##########
@@ -298,8 +298,12 @@ def _watch(self, pcolls):
watched_pcollections.add(val)
elif isinstance(val, DeferredBase):
watched_dataframes.add(val)
- # Convert them all in a single step for efficiency.
- for pcoll in to_pcollection(*watched_dataframes, always_return_tuple=True):
+
+ # Convert them one-by-one to generate a unique label for each. This allows
+ # caching at a more fine-grained granularity.
+ for df in watched_dataframes:
+ pcoll = to_pcollection(
+ df, yield_elements='pandas', label=str(id(df._expr._id)))
Review comment:
Ah I guess the examples in `test_dataframe_same_cell_twice` are [falling
through to the default
case](https://github.com/apache/beam/blob/dd2f67bb8ec49e542635035743a754421cce3a75/sdks/python/apache_beam/dataframe/convert.py#L244),
`ToPCollection(...)`, since the dataframes aren't assigned to variables. The
label is generated for the `DataframeTransform` though, not the output
PCollections. I wouldn't think it would impact PCollection caching.
##########
File path: sdks/python/apache_beam/runners/interactive/interactive_beam.py
##########
@@ -529,6 +534,11 @@ def collect(pcoll, n='inf', duration='inf',
include_window_info=False):
n: (optional) max number of elements to visualize. Default 'inf'.
duration: (optional) max duration of elements to read in integer seconds or
a string duration. Default 'inf'.
+ include_window_info: (optional) if True, appends the windowing information
+ to each row. Default False.
+ reset_unnamed_indexes: (optional) If True, resets unnamed indices. This is
+ useful because the Beam DataFrame model has non-deterministic index
+ values for DataFrames with unnamed indexes. Default True.
Review comment:
Ok, thank you
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Issue Time Tracking
-------------------
Worklog Id: (was: 598192)
Time Spent: 5.5h (was: 5h 20m)
> ib.collect doesn't preserve the index from DeferredDataFrame instances
> ----------------------------------------------------------------------
>
> Key: BEAM-12246
> URL: https://issues.apache.org/jira/browse/BEAM-12246
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Affects Versions: 2.29.0
> Reporter: Brian Hulette
> Assignee: Sam Rohde
> Priority: P2
> Labels: dataframe-api
> Time Spent: 5.5h
> Remaining Estimate: 0h
>
> This happens because it use {{to_pcollection(yield='schemas',
> include_indexes=False)}} (the default values for those arguments). To fix
> this we should avoid converting to beam schemas and collect the raw
> dataframes with {{to_pcollectiion(yield='pandas')}}.
> See https://github.com/apache/beam/pull/14356#discussion_r620647659
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