[GitHub] [spark] sandeepvja commented on issue #24883: [SPARK-24898][DOC] Adding spark.checkpoint.compress to the docs

2019-06-16 Thread GitBox
sandeepvja commented on issue #24883: [SPARK-24898][DOC] Adding 
spark.checkpoint.compress to the docs
URL: https://github.com/apache/spark/pull/24883#issuecomment-502555484
 
 
   my JIRA Id: m.sandeep , Can you please add me as a contributor to the JIRA 
issue ? 


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[GitHub] [spark] gengliangwang commented on a change in pull request #24043: [SPARK-11412][SQL] Support merge schema for ORC

2019-06-16 Thread GitBox
gengliangwang commented on a change in pull request #24043: [SPARK-11412][SQL] 
Support merge schema for ORC
URL: https://github.com/apache/spark/pull/24043#discussion_r294153497
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/SchemaMergeUtils.scala
 ##
 @@ -0,0 +1,105 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.datasources
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.{FileStatus, Path}
+
+import org.apache.spark.SparkException
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.util.SerializableConfiguration
+
+object SchemaMergeUtils extends Logging {
+  /**
+   * Figures out a merged Parquet/ORC schema with a distributed Spark job.
+   */
+  def mergeSchemasInParallel(
+  sparkSession: SparkSession,
+  files: Seq[FileStatus],
+  schemaReader: (Seq[FileStatus], Configuration, Boolean) => 
Seq[StructType])
+  : Option[StructType] = {
+val serializedConf = new 
SerializableConfiguration(sparkSession.sessionState.newHadoopConf())
+
+// !! HACK ALERT !!
+//
+// Parquet/ORC requires `FileStatus`es to read footers.
 
 Review comment:
   Sorry, I check the code again and I think only Parquet requires 
`FileStatus`, while Orc requires only `Path`. So the comments here are not 
accurate. 
   We should explain that the hack is for Parquet, but it can be used by ORC as 
well.


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[GitHub] [spark] jerryshao commented on a change in pull request #24848: [SPARK-28014][core] All waiting apps will be changed to the wrong state of Running after master changed.

2019-06-16 Thread GitBox
jerryshao commented on a change in pull request #24848: [SPARK-28014][core] All 
waiting apps will be changed to the wrong state of Running after master changed.
URL: https://github.com/apache/spark/pull/24848#discussion_r294148376
 
 

 ##
 File path: core/src/main/scala/org/apache/spark/deploy/master/Master.scala
 ##
 @@ -561,7 +561,7 @@ private[deploy] class Master(
 apps.filter(_.state == ApplicationState.UNKNOWN).foreach(finishApplication)
 
 // Update the state of recovered apps to RUNNING
-apps.filter(_.state == ApplicationState.WAITING).foreach(_.state = 
ApplicationState.RUNNING)
+apps.filter(_.coresGranted > 0).foreach(_.state = ApplicationState.RUNNING)
 
 Review comment:
   Shall we also check the `state` to guarantee only the `WAITING` state and 
`coresGranted > 0` can be shifted to `RUNNING` ?


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[GitHub] [spark] AmplabJenkins commented on issue #24887: [SPARK-28039][SQL][TEST] Port float4.sql

2019-06-16 Thread GitBox
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[GitHub] [spark] AmplabJenkins commented on issue #24887: [SPARK-28039][SQL][TEST] Port float4.sql

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[GitHub] [spark] SparkQA removed a comment on issue #24887: [SPARK-28039][SQL][TEST] Port float4.sql

2019-06-16 Thread GitBox
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URL: https://github.com/apache/spark/pull/24887#issuecomment-502520033
 
 
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[GitHub] [spark] SparkQA commented on issue #24887: [SPARK-28039][SQL][TEST] Port float4.sql

2019-06-16 Thread GitBox
SparkQA commented on issue #24887: [SPARK-28039][SQL][TEST] Port float4.sql
URL: https://github.com/apache/spark/pull/24887#issuecomment-502548511
 
 
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* This patch passes all tests.
* This patch merges cleanly.
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[GitHub] [spark] zuotingbing commented on issue #24848: [SPARK-28014][core] All waiting apps will be changed to the wrong state of Running after master changed.

2019-06-16 Thread GitBox
zuotingbing commented on issue #24848: [SPARK-28014][core] All waiting apps 
will be changed to the wrong state of Running after master changed.
URL: https://github.com/apache/spark/pull/24848#issuecomment-502547480
 
 
   1. submit tow apps called A and B to the HA standalone cluster. APP A 
requests all resources, so app B is on waiting state.
   2. stop the active master(make sure APP A is still running after recovery 
completed)
   3. after recovery completed, app B is on running state but granted 0 cores


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[GitHub] [spark] wangyum commented on issue #24859: [SPARK-28033][SQL] String concatenation should low priority than other operators

2019-06-16 Thread GitBox
wangyum commented on issue #24859: [SPARK-28033][SQL] String concatenation 
should low priority than other operators
URL: https://github.com/apache/spark/pull/24859#issuecomment-502547155
 
 
   @mgaido91 @dongjoon-hyun  Should we update the migration guide? I think this 
is a bug fix, not a behavior change.


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2019-06-16 Thread GitBox
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[GitHub] [spark] SparkQA commented on issue #24830: [SPARK-27990][SQL][ML] Provide a way to recursively load data from datasource

2019-06-16 Thread GitBox
SparkQA commented on issue #24830: [SPARK-27990][SQL][ML] Provide a way to 
recursively load data from datasource
URL: https://github.com/apache/spark/pull/24830#issuecomment-502546093
 
 
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* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] SparkQA removed a comment on issue #24830: [SPARK-27990][SQL][ML] Provide a way to recursively load data from datasource

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[GitHub] [spark] dongjoon-hyun edited a comment on issue #24889: [SPARK-28072][SQL] Use `Iso8601TimestampFormatter` in `FromUnixTime` codegen to fix ICCE in JDK9+

2019-06-16 Thread GitBox
dongjoon-hyun edited a comment on issue #24889: [SPARK-28072][SQL] Use 
`Iso8601TimestampFormatter` in `FromUnixTime` codegen to fix ICCE in JDK9+
URL: https://github.com/apache/spark/pull/24889#issuecomment-502543663
 
 
   cc @MaxGekk and @cloud-fan 
   Also, cc @srowen and @kiszk .


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[GitHub] [spark] dongjoon-hyun commented on issue #24883: [SPARK-24898][DOC] Adding spark.checkpoint.compress to the docs

2019-06-16 Thread GitBox
dongjoon-hyun commented on issue #24883: [SPARK-24898][DOC] Adding 
spark.checkpoint.compress to the docs
URL: https://github.com/apache/spark/pull/24883#issuecomment-502545450
 
 
   @sandeepvja . What is your JIRA ID? You will be an Apache Spark contributor 
as the `Assignee` of https://issues.apache.org/jira/browse/SPARK-24898 .


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[GitHub] [spark] dongjoon-hyun closed pull request #24883: [SPARK-24898][DOC] Adding spark.checkpoint.compress to the docs

2019-06-16 Thread GitBox
dongjoon-hyun closed pull request #24883: [SPARK-24898][DOC] Adding 
spark.checkpoint.compress to the docs
URL: https://github.com/apache/spark/pull/24883
 
 
   


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[GitHub] [spark] viirya commented on a change in pull request #24846: [SPARK-28012][SQL] Hive UDF supports literal struct type

2019-06-16 Thread GitBox
viirya commented on a change in pull request #24846: [SPARK-28012][SQL] Hive 
UDF supports literal struct type
URL: https://github.com/apache/spark/pull/24846#discussion_r294144110
 
 

 ##
 File path: 
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala
 ##
 @@ -847,6 +847,8 @@ private[hive] trait HiveInspectors {
 
 ObjectInspectorFactory.getStandardConstantMapObjectInspector(keyOI, 
valueOI, jmap)
   }
+case Literal(_, dt: StructType) =>
+  toInspector(dt)
 
 Review comment:
   The fix looks correct.
   
   However, to use `toInspector` here is to invoke `toInspector(dataType: 
DataType)` for nested fields. For the fields, not constant object inspector is 
used anymore.
   
   Since it is literal, can we follow array and map literals logics, to use 
constant object inspector for nested fields?
   



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[GitHub] [spark] viirya commented on a change in pull request #24846: [SPARK-28012][SQL] Hive UDF supports literal struct type

2019-06-16 Thread GitBox
viirya commented on a change in pull request #24846: [SPARK-28012][SQL] Hive 
UDF supports literal struct type
URL: https://github.com/apache/spark/pull/24846#discussion_r294144110
 
 

 ##
 File path: 
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala
 ##
 @@ -847,6 +847,8 @@ private[hive] trait HiveInspectors {
 
 ObjectInspectorFactory.getStandardConstantMapObjectInspector(keyOI, 
valueOI, jmap)
   }
+case Literal(_, dt: StructType) =>
+  toInspector(dt)
 
 Review comment:
   The fix looks correct.
   
   However, to use `toInspector` here is to invoke `toInspector(dataType: 
DataType)` for nested fields. For the fields, not constant object inspector is 
used anymore.
   
   Can we follow array and map literals logics, to use constant object 
inspector for nested fields?
   



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[GitHub] [spark] SparkQA commented on issue #24861: [SPARK-26985][CORE] Fix "access only some column of the all of columns " for big endian architecture BUG

2019-06-16 Thread GitBox
SparkQA commented on issue #24861: [SPARK-26985][CORE] Fix "access only some 
column of the all of columns " for big endian architecture BUG
URL: https://github.com/apache/spark/pull/24861#issuecomment-502544368
 
 
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[GitHub] [spark] AmplabJenkins commented on issue #24861: [SPARK-26985][CORE] Fix "access only some column of the all of columns " for big endian architecture BUG

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[GitHub] [spark] dongjoon-hyun commented on issue #24889: [SPARK-28072][SQL] Use `Iso8601TimestampFormatter` in `FromUnixTime` codegen to fix ICCE in JDK9+

2019-06-16 Thread GitBox
dongjoon-hyun commented on issue #24889: [SPARK-28072][SQL] Use 
`Iso8601TimestampFormatter` in `FromUnixTime` codegen to fix ICCE in JDK9+
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   cc @MaxGekk and @cloud-fan 


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[GitHub] [spark] gengliangwang commented on issue #24843: [SPARK-28004][UI] Update jquery to 3.4.1

2019-06-16 Thread GitBox
gengliangwang commented on issue #24843: [SPARK-28004][UI] Update jquery to 
3.4.1
URL: https://github.com/apache/spark/pull/24843#issuecomment-502543856
 
 
   A late LGTM. I also tried `grep -r "jquery-1.12.4.min.js" *` and there is no 
matched results.


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[GitHub] [spark] jerryshao commented on issue #24848: [SPARK-28014][core] All waiting apps will be changed to the wrong state of Running after master changed.

2019-06-16 Thread GitBox
jerryshao commented on issue #24848: [SPARK-28014][core] All waiting apps will 
be changed to the wrong state of Running after master changed.
URL: https://github.com/apache/spark/pull/24848#issuecomment-502542514
 
 
   How to reproduce this issue?


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[GitHub] [spark] dongjoon-hyun commented on issue #24884: [SPARK-28066][CORE] Optimize UTF8String.trim() for common case of no whitespace

2019-06-16 Thread GitBox
dongjoon-hyun commented on issue #24884: [SPARK-28066][CORE] Optimize 
UTF8String.trim() for common case of no whitespace
URL: https://github.com/apache/spark/pull/24884#issuecomment-502541397
 
 
   Thank you for updating, @srowen . The sentence looks correct since it 
describes the content of the return value. However, can we explicitly describe 
both `return this` and `the memory copy` cases separately? `@return this 
string` seems to give an impression to reuse the underlying memory space. But, 
we do copy for the 10% of the input strings.


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[GitHub] [spark] sandeepvja commented on issue #24883: [SPARK-24898][DOC] Adding spark.checkpoint.compress to the docs

2019-06-16 Thread GitBox
sandeepvja commented on issue #24883: [SPARK-24898][DOC] Adding 
spark.checkpoint.compress to the docs
URL: https://github.com/apache/spark/pull/24883#issuecomment-502539646
 
 
   > Thank you for your first contribution, @sandeepvja .
   > 
   > * I left a minor comment.
   > * Please attach the generated screenshot to the PR description.
   
   @dongjoon-hyun Thanks for reviewing my first PR. Attached the screenshot to 
the issue.


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[GitHub] [spark] sandeepvja commented on issue #24883: [SPARK-24898][DOC] Adding spark.checkpoint.compress to the docs

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URL: https://github.com/apache/spark/pull/24883#issuecomment-502539270
 
 
   ![Screen Shot 2019-06-17 at 10 51 51 
AM](https://user-images.githubusercontent.com/3538013/59580409-a7013080-90ee-11e9-9b2c-3d29015f597e.png)
   


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[GitHub] [spark] dongjoon-hyun opened a new pull request #24889: [SPARK-28072][SQL] Use `Iso8601TimestampFormatter` in `FromUnixTime` to fix `IncompatibleClassChangeError` in JDK9+

2019-06-16 Thread GitBox
dongjoon-hyun opened a new pull request #24889: [SPARK-28072][SQL] Use 
`Iso8601TimestampFormatter` in `FromUnixTime` to fix 
`IncompatibleClassChangeError` in JDK9+
URL: https://github.com/apache/spark/pull/24889
 
 
   ## 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 was tested. E.g. unit tests, integration 
tests, manual tests)
   (If this patch involves UI changes, please attach a screenshot; otherwise, 
remove this)
   
   Please review https://spark.apache.org/contributing.html before opening a 
pull request.
   


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[GitHub] [spark] sandeepvja commented on a change in pull request #24883: [SPARK-24898][DOC] Adding spark.checkpoint.compress to the docs

2019-06-16 Thread GitBox
sandeepvja commented on a change in pull request #24883: [SPARK-24898][DOC] 
Adding spark.checkpoint.compress to the docs
URL: https://github.com/apache/spark/pull/24883#discussion_r294139294
 
 

 ##
 File path: docs/configuration.md
 ##
 @@ -1107,6 +1107,14 @@ Apart from these, the following properties are also 
available, and may be useful
 Compression will use spark.io.compression.codec.
   
 
+
+  spark.checkpoint.compress
+  false
+  
+Whether to compress RDD checkpoints. Generally a good idea.
+Compression will use spark.io.compression.codec
 
 Review comment:
   @dongjoon-hyun added a `.` at the end of the sentence



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[GitHub] [spark] AmplabJenkins removed a comment on issue #24884: [SPARK-28066][CORE] Optimize UTF8String.trim() for common case of no whitespace

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[GitHub] [spark] SparkQA removed a comment on issue #24884: [SPARK-28066][CORE] Optimize UTF8String.trim() for common case of no whitespace

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[GitHub] [spark] SparkQA commented on issue #24884: [SPARK-28066][CORE] Optimize UTF8String.trim() for common case of no whitespace

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SparkQA commented on issue #24884: [SPARK-28066][CORE] Optimize 
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URL: https://github.com/apache/spark/pull/24884#issuecomment-502531644
 
 
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[GitHub] [spark] AmplabJenkins removed a comment on issue #24888: [SPARK-28040][SPARK-28070][R] Write type object s3

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[GitHub] [spark] AmplabJenkins commented on issue #24888: [SPARK-28040][SPARK-28070][R] Write type object s3

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[GitHub] [spark] AmplabJenkins commented on issue #24888: [SPARK-28040][SPARK-28070][R] Write type object s3

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[GitHub] [spark] MichaelChirico commented on issue #24885: [SPARK-28040][R] Add serialization for glue type

2019-06-16 Thread GitBox
MichaelChirico commented on issue #24885: [SPARK-28040][R] Add serialization 
for glue type
URL: https://github.com/apache/spark/pull/24885#issuecomment-502528014
 
 
   Have also filed https://github.com/apache/spark/pull/24888; leaving this PR 
open for now since the latter is a lot more involved / may take a tad longer to 
work out all the kinks


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[GitHub] [spark] MichaelChirico opened a new pull request #24888: [SPARK-28040][SPARK-28070][R] Write type object s3

2019-06-16 Thread GitBox
MichaelChirico opened a new pull request #24888: [SPARK-28040][SPARK-28070][R] 
Write type object s3
URL: https://github.com/apache/spark/pull/24888
 
 
   ## What changes were proposed in this pull request?
   
   Follow-on to https://github.com/apache/spark/pull/24885 -- implement 
`writeType` and `writeObject` as S3 methods
   
   ## How was this patch tested?
   
   Untested; please advise
   
   Please review https://spark.apache.org/contributing.html before opening a 
pull request.
   


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[GitHub] [spark] SparkQA removed a comment on issue #24846: [SPARK-28012][SQL] Hive UDF supports literal struct type

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[GitHub] [spark] SparkQA commented on issue #24846: [SPARK-28012][SQL] Hive UDF supports literal struct type

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[GitHub] [spark] WeichenXu123 commented on a change in pull request #24830: [SPARK-27990][SQL][ML] Provide a way to recursively load data from datasource

2019-06-16 Thread GitBox
WeichenXu123 commented on a change in pull request #24830: 
[SPARK-27990][SQL][ML] Provide a way to recursively load data from datasource
URL: https://github.com/apache/spark/pull/24830#discussion_r294129122
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningAwareFileIndex.scala
 ##
 @@ -96,30 +102,36 @@ abstract class PartitioningAwareFileIndex(
 
   def allFiles(): Seq[FileStatus] = {
 val files = if (partitionSpec().partitionColumns.isEmpty) {
-  // For each of the root input paths, get the list of files inside them
-  rootPaths.flatMap { path =>
-// Make the path qualified (consistent with listLeafFiles and 
bulkListLeafFiles).
-val fs = path.getFileSystem(hadoopConf)
-val qualifiedPathPre = fs.makeQualified(path)
-val qualifiedPath: Path = if (qualifiedPathPre.isRoot && 
!qualifiedPathPre.isAbsolute) {
-  // SPARK-17613: Always append `Path.SEPARATOR` to the end of parent 
directories,
-  // because the `leafFile.getParent` would have returned an absolute 
path with the
-  // separator at the end.
-  new Path(qualifiedPathPre, Path.SEPARATOR)
-} else {
-  qualifiedPathPre
-}
-
-// There are three cases possible with each path
-// 1. The path is a directory and has children files in it. Then it 
must be present in
-//leafDirToChildrenFiles as those children files will have been 
found as leaf files.
-//Find its children files from leafDirToChildrenFiles and include 
them.
-// 2. The path is a file, then it will be present in leafFiles. 
Include this path.
-// 3. The path is a directory, but has no children files. Do not 
include this path.
+  if (recursive) {
+leafFiles.values.toSeq
 
 Review comment:
   I think "leafFiles" represent all nodes in a tree except "internal nodes". 
("internal nodes" is directories in the tree structure)


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[GitHub] [spark] SparkQA commented on issue #24830: [SPARK-27990][SQL][ML] Provide a way to recursively load data from datasource

2019-06-16 Thread GitBox
SparkQA commented on issue #24830: [SPARK-27990][SQL][ML] Provide a way to 
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[GitHub] [spark] SparkQA commented on issue #24043: [SPARK-11412][SQL] Support merge schema for ORC

2019-06-16 Thread GitBox
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[GitHub] [spark] MichaelChirico commented on a change in pull request #24885: [SPARK-28040][R] Add serialization for glue type

2019-06-16 Thread GitBox
MichaelChirico commented on a change in pull request #24885: [SPARK-28040][R] 
Add serialization for glue type
URL: https://github.com/apache/spark/pull/24885#discussion_r294128553
 
 

 ##
 File path: R/pkg/R/serialize.R
 ##
 @@ -71,18 +69,19 @@ writeObject <- function(con, object, writeType = TRUE) {
   switch(serdeType,
  NULL = writeVoid(con),
  integer = writeInt(con, object),
+ glue =,
  character = writeString(con, object),
  logical = writeBoolean(con, object),
- double = writeDouble(con, object),
+ double =,
 
 Review comment:
   readability is in the eye of the beholder 🙃 
   
   anyway this `switch` will go away after 28070


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[GitHub] [spark] MichaelChirico commented on a change in pull request #24885: [SPARK-28040][R] Add serialization for glue type

2019-06-16 Thread GitBox
MichaelChirico commented on a change in pull request #24885: [SPARK-28040][R] 
Add serialization for glue type
URL: https://github.com/apache/spark/pull/24885#discussion_r294128470
 
 

 ##
 File path: R/pkg/R/serialize.R
 ##
 @@ -36,15 +36,15 @@
 # nolint end
 
 getSerdeType <- function(object) {
-  type <- class(object)[[1]]
-  if (is.atomic(object) & !is.raw(object) & length(object) > 1) {
+  type <- class(object)[[1L]]
 
 Review comment:
   no, just a microoptimization while i'm in this source


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[GitHub] [spark] HyukjinKwon commented on a change in pull request #24885: [SPARK-28040][R] Add serialization for glue type

2019-06-16 Thread GitBox
HyukjinKwon commented on a change in pull request #24885: [SPARK-28040][R] Add 
serialization for glue type
URL: https://github.com/apache/spark/pull/24885#discussion_r294127967
 
 

 ##
 File path: R/pkg/R/serialize.R
 ##
 @@ -36,15 +36,15 @@
 # nolint end
 
 getSerdeType <- function(object) {
-  type <- class(object)[[1]]
-  if (is.atomic(object) & !is.raw(object) & length(object) > 1) {
+  type <- class(object)[[1L]]
 
 Review comment:
   btw why did we change 1 -> 1L? Is it related with the fix?


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[GitHub] [spark] HyukjinKwon commented on a change in pull request #24885: [SPARK-28040][R] Add serialization for glue type

2019-06-16 Thread GitBox
HyukjinKwon commented on a change in pull request #24885: [SPARK-28040][R] Add 
serialization for glue type
URL: https://github.com/apache/spark/pull/24885#discussion_r294127821
 
 

 ##
 File path: R/pkg/R/serialize.R
 ##
 @@ -71,18 +69,19 @@ writeObject <- function(con, object, writeType = TRUE) {
   switch(serdeType,
  NULL = writeVoid(con),
  integer = writeInt(con, object),
+ glue =,
  character = writeString(con, object),
  logical = writeBoolean(con, object),
- double = writeDouble(con, object),
+ double =,
 
 Review comment:
   I think it's better to keep it anyway. Looks previous one is better to read.


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[GitHub] [spark] AmplabJenkins removed a comment on issue #24887: [SPARK-28039][SQL][TEST] Port float4.sql

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[GitHub] [spark] AmplabJenkins removed a comment on issue #24887: [SPARK-28039][SQL][TEST] Port float4.sql

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[GitHub] [spark] SparkQA commented on issue #24887: [SPARK-28039][SQL][TEST] Port float4.sql

2019-06-16 Thread GitBox
SparkQA commented on issue #24887: [SPARK-28039][SQL][TEST] Port float4.sql
URL: https://github.com/apache/spark/pull/24887#issuecomment-502520033
 
 
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[GitHub] [spark] SparkQA removed a comment on issue #24868: [SPARK-28044][ML][PYTHON] MulticlassClassificationEvaluator support more metrics

2019-06-16 Thread GitBox
SparkQA removed a comment on issue #24868: [SPARK-28044][ML][PYTHON] 
MulticlassClassificationEvaluator support more metrics
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[GitHub] [spark] AmplabJenkins removed a comment on issue #24868: [SPARK-28044][ML][PYTHON] MulticlassClassificationEvaluator support more metrics

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[GitHub] [spark] AmplabJenkins commented on issue #24868: [SPARK-28044][ML][PYTHON] MulticlassClassificationEvaluator support more metrics

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[GitHub] [spark] HyukjinKwon commented on a change in pull request #24846: [SPARK-28012][SQL] Hive UDF supports literal struct type

2019-06-16 Thread GitBox
HyukjinKwon commented on a change in pull request #24846: [SPARK-28012][SQL] 
Hive UDF supports literal struct type
URL: https://github.com/apache/spark/pull/24846#discussion_r294124007
 
 

 ##
 File path: 
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala
 ##
 @@ -847,6 +847,8 @@ private[hive] trait HiveInspectors {
 
 ObjectInspectorFactory.getStandardConstantMapObjectInspector(keyOI, 
valueOI, jmap)
   }
+case Literal(_, dt: StructType) =>
+  toInspector(dt)
 
 Review comment:
   I think technically `named_struct` isn't a literal in this case. It's 
foldable expression in the example above. Can you fix the PR title and 
description accordingly to prevent confusion?


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[GitHub] [spark] HyukjinKwon commented on a change in pull request #24846: [SPARK-28012][SQL] Hive UDF supports literal struct type

2019-06-16 Thread GitBox
HyukjinKwon commented on a change in pull request #24846: [SPARK-28012][SQL] 
Hive UDF supports literal struct type
URL: https://github.com/apache/spark/pull/24846#discussion_r294121586
 
 

 ##
 File path: 
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUDFSuite.scala
 ##
 @@ -652,6 +652,17 @@ class HiveUDFSuite extends QueryTest with 
TestHiveSingleton with SQLTestUtils {
   }
 }
   }
+  test("SPARK-28012 Hive UDF supports literal struct type") {
+withUserDefinedFunction("testLiteralStructType" -> false) {
+  // Simulate a hive udf that supports struct parameters
+  sql(s"CREATE FUNCTION testLiteralStructType AS '" +
 
 Review comment:
   leading `s` seems not needed.


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[GitHub] [spark] AmplabJenkins commented on issue #24868: [SPARK-28044][ML][PYTHON] MulticlassClassificationEvaluator support more metrics

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MulticlassClassificationEvaluator support more metrics
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[GitHub] [spark] SparkQA commented on issue #24868: [SPARK-28044][ML][PYTHON] MulticlassClassificationEvaluator support more metrics

2019-06-16 Thread GitBox
SparkQA commented on issue #24868: [SPARK-28044][ML][PYTHON] 
MulticlassClassificationEvaluator support more metrics
URL: https://github.com/apache/spark/pull/24868#issuecomment-502519527
 
 
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[`344784d`](https://github.com/apache/spark/commit/344784d992e51727adb82015c5ccb27b371ae72b).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] wangyum opened a new pull request #24887: [SPARK-28039][SQL][TEST] Port float4.sql

2019-06-16 Thread GitBox
wangyum opened a new pull request #24887: [SPARK-28039][SQL][TEST] Port 
float4.sql
URL: https://github.com/apache/spark/pull/24887
 
 
   ## What changes were proposed in this pull request?
   
   This PR is to port float4.sql from PostgreSQL regression tests. 
https://github.com/postgres/postgres/blob/REL_12_BETA1/src/test/regress/sql/float4.sql
   
   The expected results can be found in the link: 
https://github.com/postgres/postgres/blob/REL_12_BETA1/src/test/regress/expected/float4.out
   
   When porting the test cases, found three PostgreSQL specific features that 
do not exist in Spark SQL:
   [SPARK-28060](https://issues.apache.org/jira/browse/SPARK-28060): Float type 
can not accept some special inputs
   [SPARK-28027](https://issues.apache.org/jira/browse/SPARK-28027): Spark SQL 
does not support prefix operator `@`
   [SPARK-28061](https://issues.apache.org/jira/browse/SPARK-28061): Support 
for converting float to binary format
   
   Also, found a bug:
   [SPARK-28024](https://issues.apache.org/jira/browse/SPARK-28024): Incorrect 
value when out of range
   
   Also, found three inconsistent behavior:
   [SPARK-27923](https://issues.apache.org/jira/browse/SPARK-27923): Spark SQL 
insert there bad inputs to NULL
   [SPARK-28028](https://issues.apache.org/jira/browse/SPARK-28028): Cast 
numeric to integral type need round
   [SPARK-27923](https://issues.apache.org/jira/browse/SPARK-27923): Spark SQL 
returns NULL when dividing by zero
   
   ## How was this patch tested?
   
   N/A
   


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[GitHub] [spark] dongjoon-hyun closed pull request #24882: [SPARK-28063][SQL] Replace deprecated `.newInstance()` in DSv2 `Catalogs`

2019-06-16 Thread GitBox
dongjoon-hyun closed pull request #24882: [SPARK-28063][SQL] Replace deprecated 
`.newInstance()` in DSv2 `Catalogs`
URL: https://github.com/apache/spark/pull/24882
 
 
   


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