Github user maropu commented on the issue:
https://github.com/apache/spark/pull/13802
yea, thanks!
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Github user hvanhovell commented on the issue:
https://github.com/apache/spark/pull/13802
@maropu could you close this one? It is not that relevant anymore. Thanks
for working on it though!
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Github user maropu commented on the issue:
https://github.com/apache/spark/pull/13802
okay
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Github user hvanhovell commented on the issue:
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Could you have a go? Would be great!
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Github user maropu commented on the issue:
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No, I'd like to fix incorrect comments.
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Github user hvanhovell commented on the issue:
https://github.com/apache/spark/pull/13802
What do you want to fix? WindowAggregateFunctions?
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Github user maropu commented on the issue:
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Is it okay to make a new pr to fix these?
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Github user maropu commented on the issue:
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Thanks for your explanation!
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Github user hvanhovell commented on the issue:
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I think we should rename and document `supportsPartial` to reflect what it
actually does.
`Rank` and `RowNumer` are window functions. They both rely on ordered
evaluation, and they shoul
Github user maropu commented on the issue:
https://github.com/apache/spark/pull/13802
As for `supportPartial`, I could understand that `collect` and `hive_udaf`
has such a limitation though,
how about `AggregateWindowFunction`? It seems these functions `RowNumber`
and `Rank` work
Github user maropu commented on the issue:
https://github.com/apache/spark/pull/13802
@hvanhovell As for `UnsafeMapData`, could you check #13847?
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Github user hvanhovell commented on the issue:
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@maropu all aggregates that current set `supportsPartial = false` cannot be
partially aggregated and require that the entire group is processed in one
step. So the name is a bit misleading. I sup
Github user maropu commented on the issue:
https://github.com/apache/spark/pull/13802
@hvanhovell oh, I see. okay, I'll check we can implement mutable
`ArrayData` and `MapData`.
btw, I have some question;
1. Any reason to use `SortAggregateExec` for all the non-partial
aggreg
Github user hvanhovell commented on the issue:
https://github.com/apache/spark/pull/13802
@maropu this won't work for other `hive_udf`s since these also maintain
internal state, and currently require per group processing. This also has a
greater potential of creating out-of-memory err
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