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Thank you, @felixcheung and @srowen .
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merged to master/2.3/2.2
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@henryr could you update this PR to only include EXCEPT DISTINCT without
the notes
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[SPARK-23069] fix R doc for describe missing text
## What changes were proposed in this pull request?
fix doc truncated
## How was this patch tested?
manually
You
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Branch 2.2
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
## How was this patch tested?
(Please explain how this patch
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thanks! merged to master/2.3
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@@ -883,6 +908,41 @@ abstract class DDLSuite extends QueryTest
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Thanks, let me try to reproduce it locally.
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LGTM
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--- Diff:
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@@ -546,10 +577,111 @@ object KMeans {
.run(data)
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}
/**
- *
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--- Diff: python/pyspark/sql/tests.py ---
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def test_udf3(self):
twoargs =
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--- Diff: python/pyspark/sql/catalog.py ---
@@ -256,27 +258,56 @@ def registerFunction(self, name, f,
returnType=StringType()):
>>>
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returnType=StringType()):
>>>
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--- Diff: python/pyspark/sql/context.py ---
@@ -204,15 +206,31 @@ def registerFunction(self, name, f,
returnType=StringType()):
>>>
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--- Diff: python/pyspark/sql/tests.py ---
@@ -3616,6 +3622,21 @@ def test_vectorized_udf_basic(self):
bool_f(col('bool')))
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--- Diff: python/pyspark/sql/tests.py ---
@@ -4037,6 +4075,21 @@ def test_simple(self):
expected =
Github user viirya commented on the issue:
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Seems to me this doesn't need to be urgent to be in 2.3.
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@bdrillard @viirya @cloud-fan are we still targeting this for 2.3?
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verified changes to the release scripts and a did simple grep check -- both
LGTM. Thanks!
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[SPARK-22885][ML][TEST] ML test for StructuredStreaming: spark.ml.tuning
## What changes were proposed in this pull request?
ML test for StructuredStreaming: spark.ml.tuning
Github user ArtRand commented on the issue:
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Hello @rvesse thanks for this patch! With Mesos having [reference
secrets](https://github.com/apache/mesos/blob/master/include/mesos/mesos.proto#L2596)
now I think providing this as a file is a
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Github user dongjoon-hyun commented on the issue:
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Hi, @HyukjinKwon and @gatorsmile .
It's ready for review again. Thanks!
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Mind if I ask what you expect to fix @gatorsmile? It's clear and explans
the results.
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the tests which are failing are because of the tests added about the
current behavior of Spark (which are introduced looking forward to introduce a
Hive compliant mode).
Therefore, before
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LGTM except a minor comment.
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Overall, the proposal looks good to me. We need a test case in
`HiveExplainSuite`
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cc @cloud-fan @gatorsmile @sameeragarwal for review
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.run(data)
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@gatorsmile as far as I know, Hive implementation is consistent with MS SQL
Server 2006 and the implementation is taken by the description of its behavior
in MSDN blogs. DB2 implementation I think
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The newly added description is not clear to most Spark users. I think the
descriptions added by this PR does not explain the common error cases pointed
out in the JIRA.
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The proposal of this PR is to follow Hive instead of MS SQL Server and DB2.
I read the comments in HIVE-15331. Nobody pointed out why Hive decided to
introduce new behaviors which are actually
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}
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/19340#discussion_r161379537
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala ---
@@ -546,10 +577,109 @@ object KMeans {
.run(data)
}
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/19340#discussion_r161379568
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala ---
@@ -149,4 +173,38 @@ object KMeansModel extends Loader[KMeansModel] {
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