Github user sohum2002 commented on the issue:
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Thank you all for your comments. I hope to improve in my future PRs. Cheers!
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Github user rxin commented on the issue:
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Honestly I don't think it is worth doing this.
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Github user rxin commented on the issue:
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I actually think this can be confusing on Dataset[T], when the Dataset is
just untyped and a DataFrame. Do we throw a runtime exception there?
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Github user rxin commented on the issue:
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Is this worth doing?
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Github user sohum2002 commented on the issue:
https://github.com/apache/spark/pull/19454
@HyukjinKwon - Thank you for your comments and analysis of this PR. I will
also try to improve the `flatMap(identity)` as mentioned by @srowen. Also, will
add a python implementation.
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/19454
BTW, for the answer to
https://github.com/apache/spark/pull/19454#issuecomment-335138642, I think you
should take a look at, for example, `flatMap` as a reference in `rdd.py` and
related tests,
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/19454
I think @srowen requested to fix it in a more performant way as well, for
example, referring https://github.com/apache/spark/pull/16276, if I understood
correctly and otherwise closing it.
Github user AmplabJenkins commented on the issue:
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Github user HyukjinKwon commented on the issue:
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Let's fix up the PR title from `[SPARK-18855 ][SQL]` to
`[SPARK-18855][SQL]` BTW.
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Github user sohum2002 commented on the issue:
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Would appreciate some help in the Python implementation of the `flatten`
function as I have never used pyspark. Could someone help me out?
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Github user srowen commented on the issue:
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This is missing from Python and Java. It also doesn't bother to implement
this more efficiently than flatMap(identity). I am not sure this is worth while?
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Github user HyukjinKwon commented on the issue:
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ok to test
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Github user kiszk commented on the issue:
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Could you please add test cases?
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Can one of the admins verify this patch?
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