[GitHub] spark issue #14918: [SPARK-17360][PYSPARK] Support generator in createDataFr...

2017-01-25 Thread Stibbons
Github user Stibbons commented on the issue: https://github.com/apache/spark/pull/14918 Ok, abandonning --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or

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2017-01-24 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/14918 I do not agree with this change too by the same reason in https://github.com/apache/spark/pull/14918#issuecomment-250882422. --- If your project is set up for it, you can reply to this email an

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2016-10-05 Thread holdenk
Github user holdenk commented on the issue: https://github.com/apache/spark/pull/14918 Do we have any usecases or benchmarks for cases where this would be helpful? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your p

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2016-09-30 Thread holdenk
Github user holdenk commented on the issue: https://github.com/apache/spark/pull/14918 I'm not sure about its value - since it only applies to equivalent of parallelize which by definition should be used on relatively small datasets. --- If your project is set up for it, you can rep

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2016-09-22 Thread Stibbons
Github user Stibbons commented on the issue: https://github.com/apache/spark/pull/14918 For information, I continue to look at these kind of simple optimisations that does not cost too much. Python is a pretty slow language, very productive in term of code writing, but inefficient in

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2016-09-22 Thread Stibbons
Github user Stibbons commented on the issue: https://github.com/apache/spark/pull/14918 Rebased --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the f

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2016-09-09 Thread Stibbons
Github user Stibbons commented on the issue: https://github.com/apache/spark/pull/14918 Indeed, i dont think it will be feasible to propagate the generator up to the jvm. It would be cool, because when we have the schema there is no need to iterate several time on the complete sequenc

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2016-09-09 Thread holdenk
Github user holdenk commented on the issue: https://github.com/apache/spark/pull/14918 So I'm not super sure I understand the point of the refactor - at some point we are forced to materialize the entire contents of the generator on the driver anyways to copy to the JVM since parallel

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2016-09-06 Thread Stibbons
Github user Stibbons commented on the issue: https://github.com/apache/spark/pull/14918 at last, tests pass ! :) --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishe

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