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--- Diff: docs/sql-programming-guide.md ---
@@ -1776,6 +1776,8 @@ options.
Note that, for DecimalType(38,0)*, the table above
intentionally
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* limitations under the
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala ---
@@ -537,9 +537,48 @@ class Dataset[T] private[sql](
*/
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[SPARK-22668][SQL] Exclude global variables from arguments of method split
by CodegenContext.splitExpressions()
## What changes were proposed in this pull request?
This PR fixes to make
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Github user hhbyyh commented on the issue:
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No it's not merged. Feel free to use the code as you wish.
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Merged to master.
Thanks for reviewing this @viirya, @jiangxb1987, @dongjoon-hyun and
@imatiach-msft.
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@jkbradley I think it is better to review #19857 (fix python model specific
optimization) and merge it first and then I rebase & update this PR. :)
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@ptkool are you still tracking this at all?
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@cloud-fan @viirya @gatorsmile @felixcheung @hvanhovell @HyukjinKwon
@dongjoon-hyun @liancheng
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[SPARK-22673][SQL] InMemoryRelation should utilize on-disk table stats
whenever possible
## What changes were proposed in this pull request?
The current implementation of
Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/19746
@WeichenXu123 From what I've seen, it's more common for people to use
VectorAssembler to assemble a bunch of Numeric columns, rather than a bunch of
Vector columns. I'd recommend we do things
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GitHub user dongjoon-hyun opened a pull request:
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[SPARK-22672][TEST][SQL] Move OrcTest to `sql/core`
## What changes were proposed in this pull request?
To support ORC tests without Hive, we had better have `OrcTest` in
`sql/core`
Github user jkbradley commented on the issue:
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Question about this PR description comment:
> Note that keep can't be used at the same time with dropLast as true.
Because they will conflict in encoded vector by producing a vector of zeros.
Github user gatorsmile commented on a diff in the pull request:
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--- Diff: docs/sql-programming-guide.md ---
@@ -1776,6 +1776,8 @@ options.
Note that, for DecimalType(38,0)*, the table above
intentionally
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--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/OneHotEncoder.scala ---
@@ -41,8 +41,12 @@ import org.apache.spark.sql.types.{DoubleType,
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Thanks! Merging to master.
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Github user holdenk commented on the issue:
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So it seems like the YARN changes are only going to happen in Hadoop 3+ so
this might make sense regardless of what happens in
https://github.com/apache/spark/pull/19267 (since folks like K8 or
Github user tdas commented on the issue:
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LGTM.
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LGTM but I'll leave it here a bit for others to take a look.
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Instead of setting `PYSPARK_PYTHON=~/anaconda3/envs/py3/bin/python`, what
happens if you set `PYSPARK_DRIVER_PYTHON=~/anaconda3/envs/py3/bin/python`?
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Github user wangyum commented on the issue:
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Instead of manually setting up table statistics, I'm just trying to
simulate the statistics for these tables by this way.
If `totalSize (or rawDataSize) > 0` and `rowCount = 0`, at least one
Github user setjet commented on the issue:
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@cloud-fan done, could you please have a look?
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Is this still WIP or ready?
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+1
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@@ -0,0 +1,210 @@
+/*
+ * Licensed to
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+/*
+ * Licensed to the
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Thank you so much, @cloud-fan .
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@@ -70,7 +70,8 @@ object SparkHadoopMapRedUtil extends Logging {
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--- Diff: project/MimaExcludes.scala ---
@@ -36,6 +36,12 @@ object MimaExcludes {
// Exclude rules for 2.3.x
lazy val v23excludes =
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@zsxwing
Any chance to go ahead with this?
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Can one of the admins verify this patch?
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Make SortMergeJoin read less data when wholeStageCodegen is off
## What changes were proposed in this pull request?
In SortMergeJoin(with wholeStageCodegen), an optimization already
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> If I understand what you're saying correctly, that should be considered a
security issue in that server application regardless of this change. The server
should not be exposing its environment
Github user tgravescs commented on a diff in the pull request:
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--- Diff: project/MimaExcludes.scala ---
@@ -36,6 +36,12 @@ object MimaExcludes {
// Exclude rules for 2.3.x
lazy val v23excludes =
Github user cloud-fan commented on the issue:
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Is it really an issue? If you manually set a wrong statistics, how would
you expect the system to do? I think data source tables don't allow you set the
statistics manually, so this problem is
Github user tgravescs commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/SecurityManager.scala ---
@@ -542,7 +496,54 @@ private[spark] class SecurityManager(
* Gets the
Github user cloud-fan commented on the issue:
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cc @jiangxb1987 who has more context.
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For
https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUDF.scala#L42,
I don't think it's a public API.
So, Scala
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[SPARK-22387][SQL] Propagate session configs to data source read/write
options
## What changes were proposed in this pull request?
Introduce a new interface `ConfigSupport` for
Github user tgravescs commented on the issue:
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thanks @cloud-fan
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@HyukjinKwon As requested, here are the related Scala API changes:
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[SPARK-22669][SQL] Avoid unnecessary function calls in code generation
## What changes were proposed in this pull request?
In many parts of the codebase for code generation, we are
Github user HyukjinKwon commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/typedaggregators.scala
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@@ -99,3 +94,91 @@ class TypedAverage[IN](val f:
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[SPARK-22634][BUILD] Update Bouncy Castle to 1.58
## What changes were proposed in this pull request?
Update Bouncy Castle to 1.58, and jets3t to 0.9.4 to (sort of) match.
## How
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/19846
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