Github user HyukjinKwon commented on the issue:
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Is this a duplicate of https://github.com/apache/spark/pull/14660? I think
the PR tries to deal with the exact same case.
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Github user eyalfa commented on a diff in the pull request:
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala
---
@@ -174,59 +174,32 @@ case class
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Github user gglanzani commented on the issue:
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@thunderdb thanks! In that case I'll update the DenseMatrix equality as
well, as I've used it as an inspiration!
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@hvanhovell
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[SPARK-17551][SQL] complete the NULL ordering support in DataFrame APIs
## What changes were proposed in this pull request?
This PR is to complete the feature - NULLS FIRST | LAST in sorting
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@shivaram
Oh...I found this way still has problems, Array[Nothing] in scala, after
compiling with type erasing, at last it turned into type `Ljava.lang.object`,
but primitive type Array
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Can we move this into catalyst.expressions in sql/catalyst?
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Thank you @clockfly @hvanhovell @gatorsmile
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jenkins test this please
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I'm going to close this one for now since I found there was a huge
regression for `MiscBenchmark."filter & aggregate without group"`.
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Thanks, @hhbyyh. This is what I get for running `sbt "testOnly ..."` I'll
push a fix.
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Hi @willb Good catch. This is a valid issue.
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@koeninger Thanks a lot for looking at this PR.
- The duplicated codes are mostly because we don't want to depend on Spark
DStream in structured streaming source. Anyway, we can create a
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cc @maver1ck @srowen
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[SPARK-16439] [SQL] bring back the separator in SQL UI
## What changes were proposed in this pull request?
Currently, the SQL metrics looks like `number of rows: `, it's
very
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Agreed. Let's continue to discuss on [JIRA](SPARK-16407) for more
visibility.
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For our vectorized parquet reader, we try to take care of these type
conversions here:
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Github user jodersky commented on the issue:
https://github.com/apache/spark/pull/14691
I totally agree! This PR LGTM, but I think a discussion on enabling truly
pluggable sources through providers will require more discussion on a more
visible channel. @zsxwing, what do you think?
Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/14691
It also lets you do things with dynamically created sink providers with
custom functions which the string based API really doesn't have good support
for (beside the string based param API for
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