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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Github user sethah commented on the issue:
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This is already fixed in #20332.
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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 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 ---
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values directly.
:param
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--- Diff: python/pyspark/sql/window.py ---
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values directly.
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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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@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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jenkins retest this please
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this has been failing due to #19892 which was recently reverted
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--- Diff: python/pyspark/ml/wrapper.py ---
@@ -118,10 +118,9 @@ def _transfer_params_to_java(self):
"""
Transforms the
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Github user jiangxb1987 commented on the issue:
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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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--- Diff: python/pyspark/sql/udf.py ---
@@ -188,6 +188,9 @@ def asNondeterministic(self):
.. versionadded:: 2.3
"""
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--- Diff: python/pyspark/sql/window.py ---
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Thanks! Merging to master and 2.3.
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I think that the problem is not SPARK-22797. The problem is that before
this PR, the Python API considers as Defined but not Set all the parameters
with a default value, while the Scala/Java class
Github user jiangxb1987 commented on the issue:
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Updated the title, does it sound good to have this PR? I'll open another
one to address the RDD.repartition() issue (which will target to 2.4).
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Github user sameeragarwal commented on the issue:
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LGTM but we should get a broader consensus on this. In the meantime, I'm
merging this patch to master/2.3.
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[SPARK-23242][SS][Tests]Don't run tests in KafkaSourceSuiteBase twice
## What changes were proposed in this pull request?
KafkaSourceSuiteBase should be abstract class, otherwise
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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
Github user MLnick commented on the issue:
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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 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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Retest this please.
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@jiangxb1987 Btw, we could argue this is a correctness issue since we added
repartition - so not necessarily blocker :-)
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SPARK-23234 is reverted now.
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--- Diff: docs/ml-classification-regression.md ---
@@ -111,10 +110,9 @@ Continuing the earlier example:
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retest this please
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I'll take a look at the code when I have a moment, but from a UI
perspective only have one issue. Having the status of `Blacklisted in Stages:
[...]` when an exec is Active could be easily
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--- Diff: python/pyspark/sql/window.py ---
@@ -124,16 +124,19 @@ def rangeBetween(start, end):
values directly.
:param
Github user gatorsmile commented on a diff in the pull request:
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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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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala ---
@@ -1216,7 +1216,7 @@ class Dataset[T] private[sql](
*/
GitHub user zsxwing opened a pull request:
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[SC-9624][SS][TESTS] Don't access `lastExecution.executedPlan` in StreamTest
## What changes were proposed in this pull request?
`lastExecution.executedPlan` is lazy val so accessing it in
Github user gatorsmile commented on a diff in the pull request:
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--- Diff: docs/sql-programming-guide.md ---
@@ -1640,6 +1640,133 @@ Configuration of Hive is done by placing your
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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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cc @jose-torres @tdas
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I'm fine with merging this -- I just dont want to this issue to be
forgotten for RDDs as I think its a major correctness issue.
@mridulm @sameeragarwal Lets continue the discussion on
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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 tdas commented on the issue:
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LGTM. My bad, I should caught this in the original PR that @jose-torres
made.
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Hi, @rxin , @cloud-fan , @sameeragarwal , @HyukjinKwon .
Could you give me some opinions about this PR? I know that Xiao Li is busy
for this period, so I didn't ping hime. For me,
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Another (possibly cleaner) approach here would be to make the shuffle block
fetch order deterministic but I agree that it might not be safe to include it
in 2.3 this late.
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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
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retest this please
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Github user jiangxb1987 commented on the issue:
https://github.com/apache/spark/pull/20393
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
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