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2017-12-27 Thread icexelloss
Github user icexelloss commented on the issue: https://github.com/apache/spark/pull/19872 @ueshin I pushed some more change to address your comments. There is one regression in existing test `SQLTests.test_udf_with_aggregate_function`. I will try to fix it tomorrow. ---

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2017-12-19 Thread ueshin
Github user ueshin commented on the issue: https://github.com/apache/spark/pull/19872 @ramacode2014 Hi, I'm not sure why you received notifications from this PR, but I guess you can unsubscribe by the "Unsubscribe" button in the right column of this page. Sorry for the inconvenience.

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2017-12-19 Thread ramacode2014
Github user ramacode2014 commented on the issue: https://github.com/apache/spark/pull/19872 Please unsubscribe me from this spam On Wed, Dec 20, 2017 at 10:46 AM, Takuya UESHIN wrote: > *@ueshin* commented on this pull request. >

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2017-12-07 Thread ueshin
Github user ueshin commented on the issue: https://github.com/apache/spark/pull/19872 @icexelloss I'm sorry for the late response. Actually I tried to implement prototypes of Pandas UDAF with partial aggregation and combining existing aggregate functions, but they are still much

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2017-12-07 Thread icexelloss
Github user icexelloss commented on the issue: https://github.com/apache/spark/pull/19872 And to @holdenk 's question. Pandas group_agg udf fundamentally uses different physical plan than the existing java/scala udf and therefore it's hard to combine them together. I don't know a

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2017-12-07 Thread icexelloss
Github user icexelloss commented on the issue: https://github.com/apache/spark/pull/19872 I end up removing `UDFColumn` class and using the existing `Aggregate` logical plan for pandas group_agg UDF. This reuses a lot of code being to existing `Aggregate` and minimize the code

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2017-12-04 Thread icexelloss
Github user icexelloss commented on the issue: https://github.com/apache/spark/pull/19872 > I thought @ueshin is working on this BTW. Oh, I certainly don't want to duplicate @ueshin 's work. I am under the impression that @ueshin is working on two-stage PySpark UDAF with

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2017-12-03 Thread icexelloss
Github user icexelloss commented on the issue: https://github.com/apache/spark/pull/19872 cc @HyukjinKwon @holdenk @ueshin Passing some basic tests. I will work on this more next week to clean up and add more testing. ---

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