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[GitHub] [spark] SparkQA commented on issue #27676: [WIP][SQL] Prevent overflow in conversions of milliseconds to/from microseconds

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[GitHub] [spark] beliefer edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version information to the configuration of Network

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beliefer edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version 
information to the configuration of Network
URL: https://github.com/apache/spark/pull/27674#issuecomment-590024593
 
 
   > For easy-to-cherrypick to branch-3.0, I think its better to split the PR 
(to add the versions) into too small parts... we really need 10 subtickets for 
that? https://issues.apache.org/jira/browse/SPARK-30839
   
   First, the process of sorting is laborious. Secondly, this segmentation is 
convenient for PR review, otherwise there is too much content in a PR.I collect 
this information based on modules and files. If we want to add a version number 
to PR, unless I collect all the version numbers in my hand.
   If we divide PR by version number, there will be more tickets.
   Another problem is that according to the version number, the workload will 
have 'data skew'.


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[GitHub] [spark] SparkQA commented on issue #27677: [SPARK-30924][SQL][3.0] Add additional checks to Merge Into

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* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] maropu commented on a change in pull request #27675: [SPARK-30870][SQL] Fix nested column aliasing

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maropu commented on a change in pull request #27675: [SPARK-30870][SQL] Fix 
nested column aliasing
URL: https://github.com/apache/spark/pull/27675#discussion_r382969363
 
 

 ##
 File path: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/NestedColumnAliasing.scala
 ##
 @@ -129,7 +129,9 @@ object NestedColumnAliasing {
 // If all nested fields of `attr` are used, we don't need to introduce 
new aliases.
 // By default, ColumnPruning rule uses `attr` already.
 if (nestedFieldToAlias.nonEmpty &&
-nestedFieldToAlias.length < totalFieldNum(attr.dataType)) {
+nestedFieldToAlias
+  .map { case (nestedField, _) => 
totalFieldNum(nestedField.dataType) }
+  .sum < totalFieldNum(attr.dataType)) {
 
 Review comment:
   Ur, I see. nice catch.


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[GitHub] [spark] maropu commented on a change in pull request #27675: [SPARK-30870][SQL] Fix nested column aliasing

[GitBox]

maropu commented on a change in pull request #27675: [SPARK-30870][SQL] Fix 
nested column aliasing
URL: https://github.com/apache/spark/pull/27675#discussion_r382969306
 
 

 ##
 File path: 
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/NestedColumnAliasingSuite.scala
 ##
 @@ -215,12 +215,7 @@ class NestedColumnAliasingSuite extends SchemaPruningTest 
{
 
 val optimized = Optimize.execute(query)
 
-val expected = nestedRelation
-  .select(GetStructField('a, 0, Some("b")))
-  .limit(5)
-  .analyze
-
-comparePlans(optimized, expected)
+comparePlans(optimized, query)
 
 Review comment:
   btw, can you add tests in this suite, too?


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[GitHub] [spark] maropu commented on a change in pull request #27675: [SPARK-30870][SQL] Fix nested column aliasing

[GitBox]

maropu commented on a change in pull request #27675: [SPARK-30870][SQL] Fix 
nested column aliasing
URL: https://github.com/apache/spark/pull/27675#discussion_r382969291
 
 

 ##
 File path: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
 ##
 @@ -3393,6 +3393,16 @@ class SQLQuerySuite extends QueryTest with 
SharedSparkSession with AdaptiveSpark
   )
 }
   }
+
+  test("SPARK-30870: Fix nested column aliasing") {
 
 Review comment:
   Can you make the test title clearer?


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[GitHub] [spark] maropu commented on a change in pull request #27675: [SPARK-30870][SQL] Fix nested column aliasing

[GitBox]

maropu commented on a change in pull request #27675: [SPARK-30870][SQL] Fix 
nested column aliasing
URL: https://github.com/apache/spark/pull/27675#discussion_r382969272
 
 

 ##
 File path: 
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/NestedColumnAliasingSuite.scala
 ##
 @@ -215,12 +215,7 @@ class NestedColumnAliasingSuite extends SchemaPruningTest 
{
 
 val optimized = Optimize.execute(query)
 
-val expected = nestedRelation
-  .select(GetStructField('a, 0, Some("b")))
-  .limit(5)
-  .analyze
-
-comparePlans(optimized, expected)
+comparePlans(optimized, query)
 
 Review comment:
   Yea, it seems that's just a mistake. cc: @dongjoon-hyun  


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[GitHub] [spark] beliefer edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version information to the configuration of Network

[GitBox]

beliefer edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version 
information to the configuration of Network
URL: https://github.com/apache/spark/pull/27674#issuecomment-590024593
 
 
   > For easy-to-cherrypick to branch-3.0, I think its better to split the PR 
(to add the versions) into too small parts... we really need 10 subtickets for 
that? https://issues.apache.org/jira/browse/SPARK-30839
   
   First, the process of sorting is laborious. Secondly, this segmentation is 
convenient for PR review, otherwise there is too much content in a PR.I collect 
this information based on modules and files. If we want to add a version number 
to PR, unless I collect all the version numbers in my hand.
   If we divide PR by version number, there will be more tickets.


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[GitHub] [spark] huaxingao commented on a change in pull request #27570: [SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR

[GitBox]

huaxingao commented on a change in pull request #27570: 
[SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR
URL: https://github.com/apache/spark/pull/27570#discussion_r382965889
 
 

 ##
 File path: examples/src/main/r/ml/fmClassifier.R
 ##
 @@ -0,0 +1,45 @@
+#
+# 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.
+#
+
+# To run this example use
+# ./bin/spark-submit examples/src/main/r/ml/fmClassifier.R
+
+# Load SparkR library into your R session
+library(SparkR)
+
+# Initialize SparkSession
+sparkR.session(appName = "SparkR-ML-fmclasfier-example")
+
+# $example on:classification$
+# Load training data
+df <- read.df("data/mllib/sample_libsvm_data.txt", source = "libsvm")
+training <- df
+test <- df
+
+# Fit a FM classification model
+model <- spark.fmClassifier(df, label ~ features)
 
 Review comment:
   ```model <- spark.fmClassifier(df, label ~ features)``` 
   -> 
   ```model <- spark.fmClassifier(training, label ~ features)```
   I know we didn't really split ```df``` and ```df``` is the same as 
```training```, but since ```training``` is defined, we should use 
```training``` here.


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[GitHub] [spark] huaxingao commented on a change in pull request #27570: [SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR

[GitBox]

huaxingao commented on a change in pull request #27570: 
[SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR
URL: https://github.com/apache/spark/pull/27570#discussion_r382965256
 
 

 ##
 File path: docs/sparkr.md
 ##
 @@ -540,6 +540,7 @@ SparkR supports the following machine learning algorithms 
currently:
 * [`spark.mlp`](api/R/spark.mlp.html): [`Multilayer Perceptron 
(MLP)`](ml-classification-regression.html#multilayer-perceptron-classifier)
 * [`spark.naiveBayes`](api/R/spark.naiveBayes.html): [`Naive 
Bayes`](ml-classification-regression.html#naive-bayes)
 * [`spark.svmLinear`](api/R/spark.svmLinear.html): [`Linear Support Vector 
Machine`](ml-classification-regression.html#linear-support-vector-machine)
+* [`spark.fmClassifier`](api/R/fmClassifier.html): [`Factorization machines 
classifier`](ml-classification-regression.html#factorization-machines-classifier)
 
 Review comment:
   super nit: ```Factorization machines classifier``` -> ```Factorization 
Machines Classifier```


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[GitHub] [spark] huaxingao commented on a change in pull request #27570: [SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR

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huaxingao commented on a change in pull request #27570: 
[SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR
URL: https://github.com/apache/spark/pull/27570#discussion_r382964867
 
 

 ##
 File path: docs/ml-classification-regression.md
 ##
 @@ -563,6 +563,15 @@ Refer to the [Python API 
docs](api/python/pyspark.ml.html#pyspark.ml.classificat
 {% include_example python/ml/fm_classifier_example.py %}
 
 
+
+
+More details on parameters can be found in the [R API 
documentation](api/R/spark.fmClassifier.html).
 
 Review comment:
   Nit: Can we change this to ```Refer to the [R API 
docs](api/R/spark.fmClassifier.html) for more details```  so it is consistent 
with other places?


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[GitHub] [spark] huaxingao commented on a change in pull request #27570: [SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR

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huaxingao commented on a change in pull request #27570: 
[SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR
URL: https://github.com/apache/spark/pull/27570#discussion_r382965167
 
 

 ##
 File path: docs/ml-classification-regression.md
 ##
 @@ -563,6 +563,15 @@ Refer to the [Python API 
docs](api/python/pyspark.ml.html#pyspark.ml.classificat
 {% include_example python/ml/fm_classifier_example.py %}
 
 
+
+
+More details on parameters can be found in the [R API 
documentation](api/R/spark.fmClassifier.html).
+
+Note: At the moment SparkR doesn't suport feature scaling.
+
+{% include_example binomial r/ml/fmClassifier.R %}
 
 Review comment:
   This should be ```{% include_example classification r/ml/fmClassifier.R 
%}```. 


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[GitHub] [spark] beliefer edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version information to the configuration of Network

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beliefer edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version 
information to the configuration of Network
URL: https://github.com/apache/spark/pull/27674#issuecomment-590024593
 
 
   > For easy-to-cherrypick to branch-3.0, I think its better to split the PR 
(to add the versions) into too small parts... we really need 10 subtickets for 
that? https://issues.apache.org/jira/browse/SPARK-30839
   
   First, the process of sorting is laborious. Secondly, this segmentation is 
convenient for PR review, otherwise there is too much content in a PR.I collect 
this information based on modules and files. If we want to add a version number 
to PR, unless I collect all the version numbers in my hand.


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[GitHub] [spark] imback82 commented on a change in pull request #27391: [SPARK-30612][SQL] Resolve qualified column name with v2 tables

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imback82 commented on a change in pull request #27391: [SPARK-30612][SQL] 
Resolve qualified column name with v2 tables
URL: https://github.com/apache/spark/pull/27391#discussion_r382964704
 
 

 ##
 File path: 
sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
 ##
 @@ -678,6 +678,44 @@ class DataSourceV2SQLSuite
 }
   }
 
+  test("qualified column names for v2 tables") {
+val t = "testcat.ns1.ns2.tbl"
+withTable(t) {
+  sql(s"CREATE TABLE $t (id bigint, point struct) 
USING foo")
+  sql(s"INSERT INTO $t VALUES (1, (10, 20))")
+
+  checkAnswer(
+sql(s"SELECT testcat.ns1.ns2.tbl.id, testcat.ns1.ns2.tbl.point.x FROM 
$t"),
+Row(1, 10))
+  checkAnswer(sql(s"SELECT ns1.ns2.tbl.id, ns1.ns2.tbl.point.x FROM $t"), 
Row(1, 10))
+  checkAnswer(sql(s"SELECT ns2.tbl.id, ns2.tbl.point.x FROM $t"), Row(1, 
10))
+  checkAnswer(sql(s"SELECT tbl.id, tbl.point.x FROM $t"), Row(1, 10))
+
+  val ex = intercept[AnalysisException] {
+sql(s"SELECT ns1.ns2.ns3.tbl.id from $t")
+  }
+  assert(ex.getMessage.contains("cannot resolve '`ns1.ns2.ns3.tbl.id`"))
+}
+  }
+
+  test("qualified column names for v1 tables") {
+// unset this config to use the default v2 session catalog.
+spark.conf.unset(V2_SESSION_CATALOG_IMPLEMENTATION.key)
+
+withTable("t") {
+  sql("CREATE TABLE t USING json AS SELECT 1 AS i")
+  checkAnswer(sql("select default.t.i from spark_catalog.t"), Row(1))
+  checkAnswer(sql("select t.i from spark_catalog.default.t"), Row(1))
+  checkAnswer(sql("select default.t.i from spark_catalog.default.t"), 
Row(1))
+
+  // catalog name cannot be used for v1 tables.
 
 Review comment:
   Using catalog name for v1 tables requires changes on the existing resolution 
rule (`matchWithTwoOrLessQualifierParts`) unless we fall back to new rule. This 
will be a 3.1 feature and I can update `matchWithTwoOrLessQualifierParts` now? 
I wanted to make sure before I get started. Thanks!


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[GitHub] [spark] maropu edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version information to the configuration of Network

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maropu edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version 
information to the configuration of Network
URL: https://github.com/apache/spark/pull/27674#issuecomment-590015119
 
 
   For easy-to-cherrypicking to branch-3.0, I think its better to split the PR 
(to add the versions) into coarse-grained parts... we really need 10 subtickets 
for that? https://issues.apache.org/jira/browse/SPARK-30839


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[GitHub] [spark] imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 table name should be fully qualified if catalog name is provided

[GitBox]

imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 
table name should be fully qualified if catalog name is provided
URL: https://github.com/apache/spark/pull/27642#discussion_r382962850
 
 

 ##
 File path: 
sql/hive/src/test/scala/org/apache/spark/sql/hive/CachedTableSuite.scala
 ##
 @@ -102,18 +102,18 @@ class CachedTableSuite extends QueryTest with 
SQLTestUtils with TestHiveSingleto
   }
 
   test("uncache of nonexistent tables") {
-val expectedErrorMsg = "Table or view not found: nonexistentTable"
+val expectedErrorMsg = "Table or view not found:"
 // make sure table doesn't exist
 var e = 
intercept[AnalysisException](spark.table("nonexistentTable")).getMessage
-assert(e.contains(expectedErrorMsg))
+assert(e.contains(s"$expectedErrorMsg nonexistentTable"))
 
 Review comment:
   `spark.table` just creates `UnresolvedRelation(multipartIdentifier)`, so it 
doesn't add current namespace. 
   


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[GitHub] [spark] maropu edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version information to the configuration of Network

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maropu edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version 
information to the configuration of Network
URL: https://github.com/apache/spark/pull/27674#issuecomment-590015119
 
 
   For easy-to-cherrypick to branch-3.0, I think its better to split the PR (to 
add the versions) into fine-grained parts... we really need 10 subtickets for 
that? https://issues.apache.org/jira/browse/SPARK-30839


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[GitHub] [spark] maropu edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version information to the configuration of Network

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maropu edited a comment on issue #27674: [SPARK-30888][CORE][DOC] Add version 
information to the configuration of Network
URL: https://github.com/apache/spark/pull/27674#issuecomment-590015119
 
 
   For easy-to-cherrypick to branch-3.0, I think its better to split the PR (to 
add the versions) into coarse-grained parts... we really need 10 subtickets for 
that? https://issues.apache.org/jira/browse/SPARK-30839


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[GitHub] [spark] imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 table name should be fully qualified if catalog name is provided

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imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 
table name should be fully qualified if catalog name is provided
URL: https://github.com/apache/spark/pull/27642#discussion_r382962850
 
 

 ##
 File path: 
sql/hive/src/test/scala/org/apache/spark/sql/hive/CachedTableSuite.scala
 ##
 @@ -102,18 +102,18 @@ class CachedTableSuite extends QueryTest with 
SQLTestUtils with TestHiveSingleto
   }
 
   test("uncache of nonexistent tables") {
-val expectedErrorMsg = "Table or view not found: nonexistentTable"
+val expectedErrorMsg = "Table or view not found:"
 // make sure table doesn't exist
 var e = 
intercept[AnalysisException](spark.table("nonexistentTable")).getMessage
-assert(e.contains(expectedErrorMsg))
+assert(e.contains(s"$expectedErrorMsg nonexistentTable"))
 
 Review comment:
   `spark.table` just creates `UnresolvedRelation(multipartIdentifier)`, so it 
doesn't add current namespace. 
   
   Perhaps, should we retain the original multipart names somehow and use it 
inside `CheckAnalysis`? For `SELECT * FROM tbl`, what is a more desirable error 
message, `Table or view not found: tbl` or `Table or view not found: 
default.tbl`?
   
   Note that this PR always adds the current namespace to the identifier and 
postgres seems to use the original identifier given.


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[GitHub] [spark] imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 table name should be fully qualified if catalog name is provided

[GitBox]

imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 
table name should be fully qualified if catalog name is provided
URL: https://github.com/apache/spark/pull/27642#discussion_r382962850
 
 

 ##
 File path: 
sql/hive/src/test/scala/org/apache/spark/sql/hive/CachedTableSuite.scala
 ##
 @@ -102,18 +102,18 @@ class CachedTableSuite extends QueryTest with 
SQLTestUtils with TestHiveSingleto
   }
 
   test("uncache of nonexistent tables") {
-val expectedErrorMsg = "Table or view not found: nonexistentTable"
+val expectedErrorMsg = "Table or view not found:"
 // make sure table doesn't exist
 var e = 
intercept[AnalysisException](spark.table("nonexistentTable")).getMessage
-assert(e.contains(expectedErrorMsg))
+assert(e.contains(s"$expectedErrorMsg nonexistentTable"))
 
 Review comment:
   `spark.table` just creates `UnresolvedRelation(multipartIdentifier)`, so it 
doesn't add current namespace. 
   
   Perhaps, should we retaine the original multipart names in 
`UnresolvedRelation`, etc. and use it inside `CheckAnalysis`? For `SELECT * 
FROM tbl`, what is a more desirable message, `Table or view not found: tbl` or 
`Table or view not found: default.tbl`?
   
   Note that this PR always adds the current namespace to the identifier and 
postgres seems to use the original identifier given.


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[GitHub] [spark] imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 table name should be fully qualified if catalog name is provided

[GitBox]

imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 
table name should be fully qualified if catalog name is provided
URL: https://github.com/apache/spark/pull/27642#discussion_r382961099
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/execution/command/tables.scala
 ##
 @@ -1085,47 +1085,42 @@ case class ShowCreateTableCommand(table: 
TableIdentifier)
 
   override def run(sparkSession: SparkSession): Seq[Row] = {
 val catalog = sparkSession.sessionState.catalog
-if (catalog.isTemporaryTable(table)) {
 
 Review comment:
   reverted.


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[GitHub] [spark] imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 table name should be fully qualified if catalog name is provided

[GitBox]

imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 
table name should be fully qualified if catalog name is provided
URL: https://github.com/apache/spark/pull/27642#discussion_r382962397
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
 ##
 @@ -659,14 +669,7 @@ class ResolveSessionCatalog(
   object SessionCatalogAndTable {
 def unapply(nameParts: Seq[String]): Option[(CatalogPlugin, Seq[String])] 
= nameParts match {
   case SessionCatalogAndIdentifier(catalog, ident) =>
-if (nameParts.length == 1) {
 
 Review comment:
   OK. I will do it as a follow up. (I couldn't just remove the check because 
of `SPARK-30799: temp view name can't contain catalog name`, but I will think 
about it as a follow up).


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[GitHub] [spark] imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 table name should be fully qualified if catalog name is provided

[GitBox]

imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 
table name should be fully qualified if catalog name is provided
URL: https://github.com/apache/spark/pull/27642#discussion_r382961153
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
 ##
 @@ -257,9 +257,10 @@ class ResolveSessionCatalog(
 case v1Table: V1Table =>
   DescribeColumnCommand(tbl.asTableIdentifier, colNameParts, 
isExtended)
   }.getOrElse {
-if (isTempView(tbl)) {
 
 Review comment:
   updated.


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[GitHub] [spark] imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 table name should be fully qualified if catalog name is provided

[GitBox]

imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 
table name should be fully qualified if catalog name is provided
URL: https://github.com/apache/spark/pull/27642#discussion_r382962230
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
 ##
 @@ -449,8 +454,17 @@ class ResolveSessionCatalog(
 partitionSpec)
 
 case ShowColumnsStatement(tbl, ns) =>
+  if (ns.isDefined && ns.get.length > 1) {
+throw new AnalysisException(
+  s"Namespace name should have only one part if specified: 
${ns.get.quoted}")
+  }
+  val nameParts = if (ns.isDefined && tbl.length == 1) {
 
 Review comment:
   Added.


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[GitHub] [spark] imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 table name should be fully qualified if catalog name is provided

[GitBox]

imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 
table name should be fully qualified if catalog name is provided
URL: https://github.com/apache/spark/pull/27642#discussion_r382961077
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
 ##
 @@ -396,7 +397,7 @@ class ResolveSessionCatalog(
   }
 
 case AnalyzeColumnStatement(tbl, columnNames, allColumns) =>
-  val v1TableName = parseV1Table(tbl, "ANALYZE TABLE")
+  val v1TableName = parseTempViewOrV1Table(tbl, "ANALYZE TABLE")
 
 Review comment:
   yes, and this command supports temp views.


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[GitHub] [spark] beliefer commented on issue #27674: [SPARK-30888][CORE][DOC] Add version information to the configuration of Network

[GitBox]

beliefer commented on issue #27674: [SPARK-30888][CORE][DOC] Add version 
information to the configuration of Network
URL: https://github.com/apache/spark/pull/27674#issuecomment-590024593
 
 
   > For easy-to-cherrypick to branch-3.0, I think its better to split the PR 
(to add the versions) into too small parts... we really need 10 subtickets for 
that? https://issues.apache.org/jira/browse/SPARK-30839
   
   First, the process of sorting is laborious. Secondly, this segmentation is 
convenient for PR review, otherwise there is too much content in a PR.


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[GitHub] [spark] imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 table name should be fully qualified if catalog name is provided

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imback82 commented on a change in pull request #27642: [SPARK-30885][SQL] V1 
table name should be fully qualified if catalog name is provided
URL: https://github.com/apache/spark/pull/27642#discussion_r382960538
 
 

 ##
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/V2SessionCatalog.scala
 ##
 @@ -171,8 +171,6 @@ class V2SessionCatalog(catalog: SessionCatalog, conf: 
SQLConf)
   ident.namespace match {
 case Array(db) =>
   TableIdentifier(ident.name, Some(db))
-case Array() =>
 
 Review comment:
   Yes, good idea!


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[GitHub] [spark] brkyvz opened a new pull request #27677: [SPARK-30924][SQL] Add additional checks to Merge Into

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brkyvz opened a new pull request #27677: [SPARK-30924][SQL] Add additional 
checks to Merge Into
URL: https://github.com/apache/spark/pull/27677
 
 
   ### What changes were proposed in this pull request?
   
   Merge Into is currently missing additional validation around:
   
1. The lack of any WHEN statements
2. The first WHEN MATCHED statement needs to have a condition if there are 
two WHEN MATCHED statements.
3. Single use of UPDATE/DELETE
   
   This PR introduces these validations.
   (1) is required, because otherwise the MERGE statement is useless.
   (2) is required, because otherwise the second WHEN MATCHED condition becomes 
dead code
   (3) is up for debate, but the idea there is that a single expression should 
be sufficient to specify when you would like to update or delete your records. 
We restrict it for now to reduce surface area and ambiguity.
   
   ### Why are the changes needed?
   
   To ease DataSource developers when building implementations for MERGE
   
   ### Does this PR introduce any user-facing change?
   
   Adds additional validation checks
   
   ### How was this patch tested?
   
   Unit tests


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[GitHub] [spark] nandini57 commented on issue #27056: [SPARK-27217][SQL] Nested schema pruning with Aggregation

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nandini57 commented on issue #27056: [SPARK-27217][SQL] Nested schema pruning 
with Aggregation
URL: https://github.com/apache/spark/pull/27056#issuecomment-590015859
 
 
   Thanks takeshi for the quick reply.i utilized extra optimization to include
   spark 4502 changes and it works pretty well.Very interested in including
   27217 as well
   
   On Sat, Feb 22, 2020 at 7:36 PM Takeshi Yamamuro 
   wrote:
   
   > Probably, you'd be better to ask that in the spark mailing list. Anyway,
   > we already have SparkSessionExtensions (or
   > SparkSession.experimental.extraOptimizations) for injecting custom rules
   > in 3rd-party projects. So, you can do so by using these interfaces (they
   > are experimental interfaces though).
   >
   > —
   > You are receiving this because you commented.
   > Reply to this email directly, view it on GitHub
   > 
,
   > or unsubscribe
   > 

   > .
   >
   


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[GitHub] [spark] maropu commented on issue #27674: [SPARK-30888][CORE][DOC] Add version information to the configuration of Network

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maropu commented on issue #27674: [SPARK-30888][CORE][DOC] Add version 
information to the configuration of Network
URL: https://github.com/apache/spark/pull/27674#issuecomment-590015119
 
 
   For easy-to-cherrypick to branch-3.0, I think its better to split the PR (to 
add the versions) into too small parts... we really need 10 subtickets for 
that? https://issues.apache.org/jira/browse/SPARK-30839


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[GitHub] [spark] viirya commented on a change in pull request #27617: [SPARK-30865][SQL] Refactor DateTimeUtils

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viirya commented on a change in pull request #27617: [SPARK-30865][SQL] 
Refactor DateTimeUtils
URL: https://github.com/apache/spark/pull/27617#discussion_r382953681
 
 

 ##
 File path: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala
 ##
 @@ -407,137 +397,141 @@ object DateTimeUtils {
 }
   }
 
-  private def localTimestamp(microsec: SQLTimestamp, zoneId: ZoneId): 
LocalDateTime = {
-microsToInstant(microsec).atZone(zoneId).toLocalDateTime
+  private def getLocalDateTime(micros: Long, zoneId: ZoneId): LocalDateTime = {
+microsToInstant(micros).atZone(zoneId).toLocalDateTime
   }
 
   /**
* Returns the hour value of a given timestamp value. The timestamp is 
expressed in microseconds.
*/
-  def getHours(microsec: SQLTimestamp, zoneId: ZoneId): Int = {
-localTimestamp(microsec, zoneId).getHour
+  def getHours(micros: Long, zoneId: ZoneId): Int = {
+getLocalDateTime(micros, zoneId).getHour
   }
 
   /**
* Returns the minute value of a given timestamp value. The timestamp is 
expressed in
-   * microseconds.
+   * microseconds since the epoch.
*/
-  def getMinutes(microsec: SQLTimestamp, zoneId: ZoneId): Int = {
-localTimestamp(microsec, zoneId).getMinute
+  def getMinutes(micros: Long, zoneId: ZoneId): Int = {
+getLocalDateTime(micros, zoneId).getMinute
   }
 
   /**
* Returns the second value of a given timestamp value. The timestamp is 
expressed in
-   * microseconds.
+   * microseconds since the epoch.
*/
-  def getSeconds(microsec: SQLTimestamp, zoneId: ZoneId): Int = {
-localTimestamp(microsec, zoneId).getSecond
+  def getSeconds(micros: Long, zoneId: ZoneId): Int = {
+getLocalDateTime(micros, zoneId).getSecond
   }
 
   /**
* Returns the seconds part and its fractional part with microseconds.
*/
-  def getSecondsWithFraction(microsec: SQLTimestamp, zoneId: ZoneId): Decimal 
= {
-Decimal(getMicroseconds(microsec, zoneId), 8, 6)
+  def getSecondsWithFraction(micros: Long, zoneId: ZoneId): Decimal = {
+Decimal(getMicroseconds(micros, zoneId), 8, 6)
   }
 
   /**
-   * Returns seconds, including fractional parts, multiplied by 1000. The 
timestamp
-   * is expressed in microseconds since the epoch.
+   * Returns local seconds, including fractional parts, multiplied by 1000.
+   *
+   * @param micros The number of microseconds since the epoch.
+   * @param zoneId The time zone id which milliseconds should be obtained in.
*/
-  def getMilliseconds(timestamp: SQLTimestamp, zoneId: ZoneId): Decimal = {
-Decimal(getMicroseconds(timestamp, zoneId), 8, 3)
+  def getMilliseconds(micros: Long, zoneId: ZoneId): Decimal = {
+Decimal(getMicroseconds(micros, zoneId), 8, 3)
   }
 
   /**
-   * Returns seconds, including fractional parts, multiplied by 100. The 
timestamp
-   * is expressed in microseconds since the epoch.
+   * Returns local seconds, including fractional parts, multiplied by 100.
 
 Review comment:
   Returns local microseconds?


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[GitHub] [spark] viirya commented on a change in pull request #27617: [SPARK-30865][SQL] Refactor DateTimeUtils

[GitBox]

viirya commented on a change in pull request #27617: [SPARK-30865][SQL] 
Refactor DateTimeUtils
URL: https://github.com/apache/spark/pull/27617#discussion_r382953704
 
 

 ##
 File path: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala
 ##
 @@ -407,137 +397,141 @@ object DateTimeUtils {
 }
   }
 
-  private def localTimestamp(microsec: SQLTimestamp, zoneId: ZoneId): 
LocalDateTime = {
-microsToInstant(microsec).atZone(zoneId).toLocalDateTime
+  private def getLocalDateTime(micros: Long, zoneId: ZoneId): LocalDateTime = {
+microsToInstant(micros).atZone(zoneId).toLocalDateTime
   }
 
   /**
* Returns the hour value of a given timestamp value. The timestamp is 
expressed in microseconds.
*/
-  def getHours(microsec: SQLTimestamp, zoneId: ZoneId): Int = {
-localTimestamp(microsec, zoneId).getHour
+  def getHours(micros: Long, zoneId: ZoneId): Int = {
+getLocalDateTime(micros, zoneId).getHour
   }
 
   /**
* Returns the minute value of a given timestamp value. The timestamp is 
expressed in
-   * microseconds.
+   * microseconds since the epoch.
*/
-  def getMinutes(microsec: SQLTimestamp, zoneId: ZoneId): Int = {
-localTimestamp(microsec, zoneId).getMinute
+  def getMinutes(micros: Long, zoneId: ZoneId): Int = {
+getLocalDateTime(micros, zoneId).getMinute
   }
 
   /**
* Returns the second value of a given timestamp value. The timestamp is 
expressed in
-   * microseconds.
+   * microseconds since the epoch.
*/
-  def getSeconds(microsec: SQLTimestamp, zoneId: ZoneId): Int = {
-localTimestamp(microsec, zoneId).getSecond
+  def getSeconds(micros: Long, zoneId: ZoneId): Int = {
+getLocalDateTime(micros, zoneId).getSecond
   }
 
   /**
* Returns the seconds part and its fractional part with microseconds.
*/
-  def getSecondsWithFraction(microsec: SQLTimestamp, zoneId: ZoneId): Decimal 
= {
-Decimal(getMicroseconds(microsec, zoneId), 8, 6)
+  def getSecondsWithFraction(micros: Long, zoneId: ZoneId): Decimal = {
+Decimal(getMicroseconds(micros, zoneId), 8, 6)
   }
 
   /**
-   * Returns seconds, including fractional parts, multiplied by 1000. The 
timestamp
-   * is expressed in microseconds since the epoch.
+   * Returns local seconds, including fractional parts, multiplied by 1000.
 
 Review comment:
   Returns local milliseconds?


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[GitHub] [spark] SparkQA commented on issue #27593: [SPARK-30818][SPARKR][ML] Add SparkR LinearRegression wrapper

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SparkQA commented on issue #27593: [SPARK-30818][SPARKR][ML] Add SparkR 
LinearRegression wrapper
URL: https://github.com/apache/spark/pull/27593#issuecomment-590014445
 
 
   **[Test build #118822 has 
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/118822/testReport)**
 for PR 27593 at commit 
[`cf46b18`](https://github.com/apache/spark/commit/cf46b1878c2747984eb8cdcce626961af8b2f4fe).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] SparkQA removed a comment on issue #27593: [SPARK-30818][SPARKR][ML] Add SparkR LinearRegression wrapper

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SparkQA removed a comment on issue #27593: [SPARK-30818][SPARKR][ML] Add SparkR 
LinearRegression wrapper
URL: https://github.com/apache/spark/pull/27593#issuecomment-590009798
 
 
   **[Test build #118822 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/118822/testReport)**
 for PR 27593 at commit 
[`cf46b18`](https://github.com/apache/spark/commit/cf46b1878c2747984eb8cdcce626961af8b2f4fe).


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[GitHub] [spark] maropu commented on issue #27651: [SPARK-30903][SQL] Fail fast on duplicate columns when analyze columns

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maropu commented on issue #27651: [SPARK-30903][SQL] Fail fast on duplicate 
columns when analyze columns
URL: https://github.com/apache/spark/pull/27651#issuecomment-590014317
 
 
   Thanks! Merged to master/3.0!
   
   Just in case, I've checked that pgSQL has the same behaivour;
   ```
   postgres=# \d t
Table "public.t"
Column |  Type   | Collation | Nullable | Default 
   +-+---+--+-
k  | integer |   |  | 
v  | integer |   |  | 
   
   postgres=# analyze t (k, k);
   ERROR:  column "k" of relation "t" appears more than once
   ```


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[GitHub] [spark] maropu closed pull request #27651: [SPARK-30903][SQL] Fail fast on duplicate columns when analyze columns

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maropu closed pull request #27651: [SPARK-30903][SQL] Fail fast on duplicate 
columns when analyze columns
URL: https://github.com/apache/spark/pull/27651
 
 
   


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[GitHub] [spark] AmplabJenkins commented on issue #27570: [SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR

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AmplabJenkins commented on issue #27570: [SPARK-30820][SPARKR][ML] Add 
FMClassifier to SparkR
URL: https://github.com/apache/spark/pull/27570#issuecomment-590014116
 
 
   Test PASSed.
   Refer to this link for build results (access rights to CI server needed): 
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[GitHub] [spark] AmplabJenkins removed a comment on issue #27570: [SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR

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AmplabJenkins removed a comment on issue #27570: [SPARK-30820][SPARKR][ML] Add 
FMClassifier to SparkR
URL: https://github.com/apache/spark/pull/27570#issuecomment-590014114
 
 
   Merged build finished. Test PASSed.


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