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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala
---
@@ -294,3 +294,35 @@ object Substring {
appl
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--- Diff:
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Github user rxin commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala ---
@@ -71,43 +71,49 @@ private[spark] case class PythonUDF(
private[spark
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GitHub user FlytxtRnD opened a pull request:
https://github.com/apache/spark/pull/6737
[SPARK-8018][MLlib]KMeans should accept initial cluster centers as param
This allows Kmeans to be initialized using an existing set of cluster
centers provided as a KMeansModel object. This mode
Github user rxin commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala ---
@@ -71,43 +71,49 @@ private[spark] case class PythonUDF(
private[spark
Github user MechCoder commented on the pull request:
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jenkins retest this please
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala ---
@@ -71,43 +71,49 @@ private[spark] case class PythonUDF(
private[
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https://github.com/apache/spark/pull/6716#discussion_r32092034
--- Diff: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
---
@@ -145,6 +145,17 @@ class SQLQuerySuite extends QueryTest with
BeforeAndAfterAll
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Github user ankurdave commented on the pull request:
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It does send all keys to all partitions, because `ksByPartition` is
referenced in the closure passed to `context.runJob` and so is shipped in full
to all partitions. O
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--- Diff:
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---
@@ -164,13 +164,28 @@ class CodeGenContext {
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--- Diff:
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@@ -164,13 +164,28 @@ class CodeGenContext {
Github user davies commented on a diff in the pull request:
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--- Diff: sql/hive/src/test/resources/golden/timestamp cast
#5-0-dbd7bcd167d322d6617b884c02c7f247 ---
@@ -1 +1 @@
--0.0010009
+-0.001
-
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Github user josephlijia commented on the pull request:
https://github.com/apache/spark/pull/1297#issuecomment-110615752
Look at the code below:
def multiget(ks: Array[Id]): Map[Id, V] = {
val ksByPartition = ks.groupBy(k =>
self.partitioner.get.getPartition(k))
val r
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
---
@@ -155,6 +156,7 @@ class CodeGenContext {
Github user pwendell commented on the pull request:
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This looks good, but will wait until #6735 is merged for final sign off.
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Github user witgo commented on the pull request:
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LGTM
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Github user adrian-wang commented on a diff in the pull request:
https://github.com/apache/spark/pull/6718#discussion_r32091043
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/functions.scala ---
@@ -122,7 +122,7 @@ object functions {
* @group agg_funcs
* @sin
Github user ankurdave commented on the pull request:
https://github.com/apache/spark/pull/1297#issuecomment-110610103
@josephlijia Right, getting should generally be faster than putting.
However, for large batches of keys, multiget might be slower than multiput
because it currently br
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/6718#discussion_r32090941
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/functions.scala ---
@@ -122,7 +122,7 @@ object functions {
* @group agg_funcs
* @since 1.3.
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--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/MathFunctionsSuite.scala
---
@@ -163,6 +163,12 @@ class MathFunctionsSuit
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Well, I found that getting is slower than putting by using IndexedRDD. But
getting should be faster than putting, is it right? I am expecting your reply.
Thanks a lo
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retest this please
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Jenkins, add to whitelist.
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Can one of the admins verify this patch?
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https://github.com/apache/spark/pull/6736
[SPARK-8285] [SQL] CombineSum should be calculated as unlimited decimal
first
case cs @ CombineSum(expr) =>
val calcType = expr.dataType
expr.dataType match {
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/6712#discussion_r32089187
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala ---
@@ -71,43 +71,49 @@ private[spark] case class PythonUDF(
private[spark
Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/6718#discussion_r32089147
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/MathFunctionsSuite.scala
---
@@ -163,6 +163,12 @@ class MathFunctionsS
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/6712#discussion_r32089158
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -460,7 +460,7 @@ class Analyzer(
def apply(plan: Log
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https://github.com/apache/spark/pull/6716#discussion_r32089027
--- Diff: python/pyspark/sql/functions.py ---
@@ -138,6 +138,13 @@ def _():
'bitwiseNOT': 'Computes bitwise not.',
}
+_functions_1_5 = {
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/6716#discussion_r32089009
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/math.scala
---
@@ -100,6 +125,16 @@ abstract class BinaryMathExpression(f: (Doub
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--- Diff: python/pyspark/sql/functions.py ---
@@ -348,6 +358,24 @@ def randn(seed=None):
return Column(jc)
+@since(1.5)
+def e():
Github user rxin commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/functions.py ---
@@ -348,6 +358,24 @@ def randn(seed=None):
return Column(jc)
+@since(1.5)
+def e():
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/6716#discussion_r32088958
--- Diff: python/pyspark/sql/functions.py ---
@@ -188,11 +195,14 @@ def _():
globals()[_name] = since(1.4)(_create_binary_mathfunction(_name, _doc))
Github user rxin commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/functions.py ---
@@ -348,6 +358,24 @@ def randn(seed=None):
return Column(jc)
+@since(1.5)
+def e():
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Github user chenghao-intel commented on the pull request:
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And also add `sql` query for unittest, just be sure the UDF registration
works.
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--- Diff:
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@@ -163,6 +163,12 @@ class MathFunctionsS
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/functions.scala ---
@@ -1106,6 +1106,22 @@ object functions {
def log1p(columnName: String
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Please also add unit tests to DataFrameFunctionSuite.
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/functions.scala ---
@@ -1106,6 +1106,22 @@ object functions {
def log1p(columnName: String): Column
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/functions.scala ---
@@ -1106,6 +1106,22 @@ object functions {
def log1p(columnName: String): Column
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@@ -1106,6 +1106,22 @@ object functions {
def log1p(columnName: String):
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cc @ankurdave
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Github user kanzhang commented on the pull request:
https://github.com/apache/spark/pull/6676#issuecomment-110579838
> Nothing else in the rest of the code should need to change.
Yes, if you are extending the current model where there is a single secret
key for the whole clust
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/6714#issuecomment-110578345
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Github user vanzin commented on the pull request:
https://github.com/apache/spark/pull/6676#issuecomment-110578274
BTW, using an env variable is mostly a trivial change. You just change the
non-YARN path in `SecurityManager::generateSecretKey`; basically, on the driver
side, generate
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/6723#discussion_r32086331
--- Diff: sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala
---
@@ -81,6 +82,8 @@ private[hive] case class HiveSimpleUdf(funcWrapper:
HiveFu
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/6351#issuecomment-110578051
Can one of the admins verify this patch?
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Github user DoingDone9 closed the pull request at:
https://github.com/apache/spark/pull/5553
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GitHub user DoingDone9 reopened a pull request:
https://github.com/apache/spark/pull/6351
[SPARK-7824][SQL]Collapsing operator reordering and constant folding into a
single batch to push down the single side.
SQL
```
select * from tableA join tableB on (a > 3 and b = d) or
Github user kanzhang commented on the pull request:
https://github.com/apache/spark/pull/6676#issuecomment-110574239
Ok, that's exactly the kind of opinion I want to hear about. Do others feel
the same way?
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/6734#issuecomment-110574078
Merged build finished. Test PASSed.
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Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/6734#issuecomment-110574068
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Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/6724#discussion_r32085774
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/StringFunctionsSuite.scala
---
@@ -215,4 +215,15 @@ class StringFunctionsSuite e
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