Github user dongjoon-hyun commented on the issue:
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Retest this please.
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Github user mridulm commented on the issue:
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@jiangxb1987 Other than hash partitioning, I dont see how this can be
handled reliably ...
You are right, this is a basic correctness issue - unfortunately I never
used this family of methods
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@sethah ok thanks!
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Github user jiangxb1987 commented on the issue:
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Another simple way to ensure correctness of RDD.repartition() is to do
HashPartitioning instead of current RoundRobinPartitioning, but that will lead
to regression when you have skew input
Github user MLnick commented on the issue:
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I reverted this (see #20410 for details) - we can re-open it once that
issue is solved.
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I reverted #19892 in master (f5911d4894700eb48f794133cbd363bf3b7c8c8e) /
branch-2.3 (a8a3e9b7cf7b9346c43cfbbf7b26fd2fd28dd521), so that other test runs
can be unblocked.
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Github user jiangxb1987 commented on the issue:
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Actually the similar approach cannot apply to fix RDD.repartition(), as in
RDD[T], the data type `T` can be non-comparable, so we are not able to perform
a local sort before actually
Github user rekhajoshm commented on the issue:
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Thank you @srowen I admire you for doing what you do over all the jira/PR's
I have studied, and followed up.
If its ok, will keep this PR open for few days, and close if jira is
getting to
Github user squito commented on a diff in the pull request:
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--- Diff:
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@@ -75,6 +75,17 @@ private[spark] class
Github user atallahhezbor commented on the issue:
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@liufengdb @gatorsmile I'm happy to write a unit test if you require it.
Though as I mentioned before, I did not see a clear way of testing the
functionality in
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retest this please
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Fully agree with @mridulm 's big picture suggestion, and I also think
supporting IPv6 should be designed as a integral feature, instead of just
putting together some PRs.
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Github user mridulm commented on a diff in the pull request:
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Github user MLnick commented on the issue:
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I think this is somewhat related to #15113
cc @BryanCutler
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--- Diff: python/pyspark/sql/window.py ---
@@ -124,16 +124,19 @@ def rangeBetween(start, end):
values directly.
:param
Github user jiangxb1987 commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/window.py ---
@@ -124,16 +124,19 @@ def rangeBetween(start, end):
values directly.
:param
Github user MLnick commented on the issue:
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We should just revert SPARK-22797 for now to unblock others.
SPARK-22799 itself is not the cause per se (it passed tests) but after it
was merged SPARK-22797 causes the failure.
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--- Diff: python/pyspark/sql/window.py ---
@@ -124,16 +124,19 @@ def rangeBetween(start, end):
values directly.
:param
Github user mridulm commented on the issue:
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To rephrase @jiangxb1987's question - supporting IPv6 is a much larger
effort, which spark currently does not. We should be addressing that as the
problem to solve, and fix this as part of IPv6
Github user sethah commented on the issue:
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This is already fixed in #20332.
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CC @zhengruifeng @MLnick
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Updated screens:
Github user BryanCutler commented on the issue:
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Thanks everyone for reviewing! I think I addressed all the comments, so
please take one more look.
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--- Diff: docs/sql-programming-guide.md ---
@@ -1640,6 +1640,133 @@ Configuration of Hive is done by placing your
`hive-site.xml`, `core-site.xml` a
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GitHub user WeichenXu123 opened a pull request:
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[SPARK-17139][ML][FOLLOW-UP] update LogisticRegressionSummaryExample code
## What changes were proposed in this pull request?
New method `trainingSummary.asBinary` added so in this
Github user jaceklaskowski commented on the issue:
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Looks like the tests failed due to _"java.io.IOException: Failed to delete:
/home/jenkins/workspace/SparkPullRequestBuilder/target/tmp/spark-5a9b5811-306d-4ba0-8bfb-9e263ddf47b8"_
Is this
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala ---
@@ -1216,7 +1216,7 @@ class Dataset[T] private[sql](
*/
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@holdenk and @HyukjinKwon , is there any further testing you guys can think
that needs to be done to verify this is ok?
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> Wait, so we left out cloudpickle#113 even though its in 0.4.2?
That patch is in here and this exactly matches 0.4.2. I also manually
verified that cloudpickle will pickle named
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--- Diff: python/pyspark/sql/udf.py ---
@@ -188,6 +188,9 @@ def asNondeterministic(self):
.. versionadded:: 2.3
"""
+
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LGTM
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--- Diff: docs/sql-programming-guide.md ---
@@ -1640,6 +1640,129 @@ Configuration of Hive is done by placing your
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FYI @ptkool.
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--- Diff:
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@@ -1045,9 +1045,10 @@ object SQLConf {
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Thanks! Merged to master/2.3
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@@ -17,15 +17,149 @@
package
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Thank you for review, @jerryshao and @srowen .
Yep. This is all I found about `Trigger`.
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Jenkins, okay to test
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https://github.com/apache/spark/pull/20408
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Github user dongjoon-hyun commented on a diff in the pull request:
https://github.com/apache/spark/pull/20395#discussion_r164160869
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sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnarBatchBenchmark.scala
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@@ -479,10 +475,10 @@ object
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