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Github user gczsjdy commented on the issue:
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Sorry, but I think this is inactive. Thanks for your attention. @wzhfy
@viirya @gatorsmile
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Github user srowen commented on the issue:
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Merged to master. I wasn't clear whether this was a pressing problem that
needed to be backported.
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Github user srowen commented on the issue:
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This comment seems valid. It's stating the question the test is trying to
answer. I'd close this please, as it would be trivial even if valid
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--- Diff:
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@@ -0,0 +1,43 @@
+/*
+ * Licensed
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LGTM
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Github user HyukjinKwon commented on the issue:
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> Write Arrow data with SESSION_LOCAL timestamp (as is currently in this PR)
BTW, could we just use `DateTimeUtils.defaultTimeZone()` instead of
`SQLConf.SESSION_LOCAL_TIMEZONE` if you r
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Github user gglanzani commented on the issue:
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@WeichenXu123 Done. Let me know.
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Github user kiszk commented on the issue:
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Let me summarize recent interesting PRs for code generation regarding JVM
bytecode limit for JIT compilation. These PRs encourages to apply JIT
compilation to more methods since most of JIT compilers
Github user WeichenXu123 commented on a diff in the pull request:
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--- Diff: python/pyspark/mllib/linalg/__init__.py ---
@@ -1131,14 +1131,20 @@ def __getitem__(self, indices):
return self.values[i + j
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return self.values[i + j * sel
Github user ueshin commented on the issue:
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I'd say I prefer 1, too. I'm just wondering what if we use timestamp in
nested types. Currently we don't support nested types but in the future?
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@kiszk Thanks for summarizing the PRs.
I just have a question about inlining method by JIT compiler. So you mean
JIT compiler will inline methods into larger unit and then do JIT compilation
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@WeichenXu123 Done again!
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I saw there are few images, just want to make sure, are those images are
safe of license issue to be included in Spark?
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GitHub user liutang123 opened a pull request:
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Spark 22233
## What changes were proposed in this pull request?
add spark.hadoop.filterOutEmptySplit confituration to allow user to filter
out empty split in HadoopRDD.
You can merge this p
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Can one of the admins verify this patch?
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Could you please update the title of this PR appropriately? e.g.
`[SPARK-22233][core] ...`
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@bdrillard Thank you very much
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@rxin @marmbrus
Is there another way to broadcast table with the spark-sql now, except by
`spark.sql.autoBroadcastJoinThreshold`?
And if no, is it a good way to broadcast table by user con
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Thanks, @hhbyyh.
I will create a JIRA for python API
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--- Diff: python/pyspark/mllib/linalg/__init__.py ---
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@gatorsmile Add this to white list!
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MLlibTestSpark
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Github user MLnick commented on the issue:
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Yes, fair enough
On Tue, 10 Oct 2017 at 14:09 Liang-Chi Hsieh
wrote:
> *@viirya* commented on this pull request.
> --
>
> In sql/core/src/
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(
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import org.apache.spark.sql.types.Struc
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o
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o
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mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala ---
@@ -187,6 +188,196 @@ class BucketizerSuite extends SparkFunSuite with
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/17819#discussion_r143730103
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala ---
@@ -187,6 +188,196 @@ class BucketizerSuite extends SparkFunSuite with
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/17819#discussion_r143728663
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala ---
@@ -187,6 +188,196 @@ class BucketizerSuite extends SparkFunSuite with
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/17819#discussion_r143733664
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/Bucketizer.scala
---
@@ -96,9 +99,71 @@ final class Bucketizer @Since("1.4.0") (@Since("1.4.0")
o
Github user pgandhi999 commented on the issue:
https://github.com/apache/spark/pull/19270
@ajbozarth I do not quite understand what you are saying. Everything seems
to be working fine on my test setup. Can you please let me know how do I
replicate the issue? Thank you.
---
Github user icexelloss commented on a diff in the pull request:
https://github.com/apache/spark/pull/18732#discussion_r143740078
--- Diff: python/pyspark/sql/tests.py ---
@@ -3376,6 +3376,151 @@ def test_vectorized_udf_empty_partition(self):
res = df.select(f(col('id'))
Github user icexelloss commented on a diff in the pull request:
https://github.com/apache/spark/pull/18732#discussion_r143740129
--- Diff: python/pyspark/sql/tests.py ---
@@ -3376,6 +3376,151 @@ def test_vectorized_udf_empty_partition(self):
res = df.select(f(col('id'))
Github user icexelloss commented on a diff in the pull request:
https://github.com/apache/spark/pull/18732#discussion_r143740157
--- Diff: python/pyspark/sql/tests.py ---
@@ -3376,6 +3376,151 @@ def test_vectorized_udf_empty_partition(self):
res = df.select(f(col('id'))
Github user icexelloss commented on a diff in the pull request:
https://github.com/apache/spark/pull/18732#discussion_r143740636
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/object.scala
---
@@ -519,3 +519,4 @@ case class CoGroup(
outp
Github user icexelloss commented on a diff in the pull request:
https://github.com/apache/spark/pull/18732#discussion_r143740773
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/pythonLogicalOperators.scala
---
@@ -0,0 +1,43 @@
+/*
+ * Lice
Github user icexelloss commented on a diff in the pull request:
https://github.com/apache/spark/pull/18732#discussion_r143740882
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/pythonLogicalOperators.scala
---
@@ -0,0 +1,43 @@
+/*
+ * Lice
Github user icexelloss commented on a diff in the pull request:
https://github.com/apache/spark/pull/18732#discussion_r143741944
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/ArrowEvalPythonExec.scala
---
@@ -44,14 +73,18 @@ case class ArrowEvalPythonExec
Github user icexelloss commented on a diff in the pull request:
https://github.com/apache/spark/pull/18732#discussion_r143744197
--- Diff: python/pyspark/sql/functions.py ---
@@ -2181,30 +2187,66 @@ def udf(f=None, returnType=StringType()):
@since(2.3)
def pandas_udf(f=Non
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