Github user aray commented on the pull request:
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@rxin sure I'll put together a PR for the python API tonight
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@aray do you want to submit a pull request for python api too?
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Thanks! Merging to master and branch 1.6.
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LGTM pending jenkins.
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@yhuai I think this addresses everything we discussed, let me know if I
missed anything or if there is anything else I can do. Again, thanks for the
code review.
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@@ -248,6 +253,43 @@ class Analyzer(
}
}
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}
}
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala ---
@@ -273,6 +280,60 @@ class GroupedData protected[sql](
def sum(colNames: Stri
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@yhuai RE your questions (3 was already addressed above):
>1. Should we always ask users to provide pivot values?
The argument for not requiring values I think is con
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thi
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this
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Github user yhuai commented on the pull request:
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@aray This is very cool! Here are a few things I'd like to discuss.
1. Should we always ask users to provide pivot values?
2. For the type of pivot values, should we
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def sum(colNames: Stri
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}
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@@ -997,6 +1034,7 @@ class Analyzer(
case p if !p.re
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Github user rxin commented on the pull request:
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To give a status update -- I'm hoping to merge this this week.
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala ---
@@ -989,6 +989,41 @@ class DataFrame private[sql](
}
/**
+ *
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@rxin Updated, the values are now optional.
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BTW we can also later add a variant that allows users to specify values
directly, in order to avoid materializing the intermediate data.
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@aray I talked to a few more people about this. Most like the 2nd API more
(groupBy.pivot.agg).
I think it'd also be better to remove the requirement to specify val
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@aray sorry was away for spark summit - back now and will get to this today.
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Github user aray commented on the pull request:
https://github.com/apache/spark/pull/7841#issuecomment-150745807
@rxin, Not requiring the values would necessitate doing a separate query
for the distinct values of the column before the pivot query. It looks like at
least some DF operat
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/7841#issuecomment-150713518
I like your 2nd interface more (group by and then pivot), since it is
easier to get that working for both Java and Scala. We can implement a simpler
interface for Python/R
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Github user marmbrus commented on the pull request:
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ok to test
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Github user aray commented on the pull request:
https://github.com/apache/spark/pull/7841#issuecomment-150620321
@rxin here is my summary of other frameworks API's
I'm going to use an example dataset form the pandas doc for all the
examples (as df)
|A|B|C|D|
|---|
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/7841#issuecomment-150511647
@aray Thanks a lot for updating this. To help api design, can you take a
look at other frameworks and see what their signatures look like?
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