[jira] [Updated] (SPARK-42655) Incorrect ambiguous column reference error
[
https://issues.apache.org/jira/browse/SPARK-42655?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ASF GitHub Bot updated SPARK-42655:
---
Labels: pull-request-available (was: )
> Incorrect ambiguous column reference error
> --
>
> Key: SPARK-42655
> URL: https://issues.apache.org/jira/browse/SPARK-42655
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
>Affects Versions: 3.2.0
>Reporter: Shrikant Prasad
>Assignee: Shrikant Prasad
>Priority: Major
> Labels: pull-request-available
> Fix For: 3.4.0
>
>
> val df1 =
> sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
> "col5")
> val op_cols_same_case = List("id","col2","col3","col4", "col5", "id")
> val df2 = df1.select(op_cols_same_case.head, op_cols_same_case.tail: _*)
> df2.select("id").show()
>
> This query runs fine.
>
> But when we change the casing of the op_cols to have mix of upper & lower
> case ("id" & "ID") it throws an ambiguous col ref error:
>
> val df1 =
> sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
> "col5")
> val op_cols_mixed_case = List("id","col2","col3","col4", "col5", "ID")
> val df3 = df1.select(op_cols_mixed_case.head, op_cols_mixed_case.tail: _*)
> df3.select("id").show()
> org.apache.spark.sql.AnalysisException: Reference 'id' is ambiguous, could
> be: id, id.
> at
> org.apache.spark.sql.catalyst.expressions.package$AttributeSeq.resolve(package.scala:363)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveChildren(LogicalPlan.scala:112)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$resolveExpressionByPlanChildren$1(Analyzer.scala:1857)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$resolveExpression$2(Analyzer.scala:1787)
> at
> org.apache.spark.sql.catalyst.analysis.package$.withPosition(package.scala:60)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.innerResolve$1(Analyzer.scala:1794)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.resolveExpression(Analyzer.scala:1812)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.resolveExpressionByPlanChildren(Analyzer.scala:1863)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$17.$anonfun$applyOrElse$94(Analyzer.scala:1577)
> at
> org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$mapExpressions$1(QueryPlan.scala:193)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:82)
> at
> org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:193)
> at
> org.apache.spark.sql.catalyst.plans.QueryPlan.recursiveTransform$1(QueryPlan.scala:204)
> at
> org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$mapExpressions$3(QueryPlan.scala:209)
> at
> scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
> at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
> at scala.collection.TraversableLike.map(TraversableLike.scala:286)
> at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
> at scala.collection.AbstractTraversable.map(Traversable.scala:108)
> at
> org.apache.spark.sql.catalyst.plans.QueryPlan.recursiveTransform$1(QueryPlan.scala:209)
>
> Since, Spark is case insensitive, it should work for second case also when we
> have upper and lower case column names in the column list.
> It also works fine in Spark 2.3.
>
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[jira] [Updated] (SPARK-42655) Incorrect ambiguous column reference error
[
https://issues.apache.org/jira/browse/SPARK-42655?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Shrikant Prasad updated SPARK-42655:
Description:
val df1 =
sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
"col5")
val op_cols_same_case = List("id","col2","col3","col4", "col5", "id")
val df2 = df1.select(op_cols_same_case.head, op_cols_same_case.tail: _*)
df2.select("id").show()
This query runs fine.
But when we change the casing of the op_cols to have mix of upper & lower case
("id" & "ID") it throws an ambiguous col ref error:
val df1 =
sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
"col5")
val op_cols_mixed_case = List("id","col2","col3","col4", "col5", "ID")
val df3 = df1.select(op_cols_mixed_case.head, op_cols_mixed_case.tail: _*)
df3.select("id").show()
org.apache.spark.sql.AnalysisException: Reference 'id' is ambiguous, could be:
id, id.
at
org.apache.spark.sql.catalyst.expressions.package$AttributeSeq.resolve(package.scala:363)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveChildren(LogicalPlan.scala:112)
at
org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$resolveExpressionByPlanChildren$1(Analyzer.scala:1857)
at
org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$resolveExpression$2(Analyzer.scala:1787)
at
org.apache.spark.sql.catalyst.analysis.package$.withPosition(package.scala:60)
at
org.apache.spark.sql.catalyst.analysis.Analyzer.innerResolve$1(Analyzer.scala:1794)
at
org.apache.spark.sql.catalyst.analysis.Analyzer.resolveExpression(Analyzer.scala:1812)
at
org.apache.spark.sql.catalyst.analysis.Analyzer.resolveExpressionByPlanChildren(Analyzer.scala:1863)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$17.$anonfun$applyOrElse$94(Analyzer.scala:1577)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$mapExpressions$1(QueryPlan.scala:193)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:82)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:193)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.recursiveTransform$1(QueryPlan.scala:204)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$mapExpressions$3(QueryPlan.scala:209)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at scala.collection.TraversableLike.map(TraversableLike.scala:286)
at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
at scala.collection.AbstractTraversable.map(Traversable.scala:108)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.recursiveTransform$1(QueryPlan.scala:209)
Since, Spark is case insensitive, it should work for second case also when we
have upper and lower case column names in the column list.
It also works fine in Spark 2.3.
was:
val df1 =
sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
"col5")
val op_cols_same_case = List("id","col2","col3","col4", "col5", "id")
val df2 = df1.select(op_cols_same_case .head, op_cols_same_case .tail: _*)
df2.select("id").show()
This query runs fine.
But when we change the casing of the op_cols to have mix of upper & lower case
("id" & "ID") it throws an ambiguous col ref error:
val df1 =
sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
"col5")
val op_cols_same_case = List("id","col2","col3","col4", "col5", "ID")
val df2 = df1.select(op_cols_same_case .head, op_cols_same_case .tail: _*)
df2.select("id").show()
Since, Spark is case insensitive, it should work for second case also when we
have upper and lower case column names in the column list.
It also works fine in Spark 2.3.
> Incorrect ambiguous column reference error
> --
>
> Key: SPARK-42655
> URL: https://issues.apache.org/jira/browse/SPARK-42655
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
>Affects Versions: 3.2.0
>Reporter: Shrikant Prasad
>Priority: Major
>
> val df1 =
> sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
> "col5")
> val op_cols_same_case = List("id","col2","col3","col4", "col5", "id")
> val df2 = df1.select(op_cols_same_case.head, op_cols_same_case.tail: _*)
> df2.select("id").show()
>
> This query runs fine.
>
> But when we change the casing of the op_cols to have mix of upper & lower
> case ("id" & "ID") it throws an ambiguous col ref error:
>
> val df1 =
>
[jira] [Updated] (SPARK-42655) Incorrect ambiguous column reference error
[
https://issues.apache.org/jira/browse/SPARK-42655?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Shrikant Prasad updated SPARK-42655:
Description:
val df1 =
sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
"col5")
val op_cols_same_case = List("id","col2","col3","col4", "col5", "id")
val df2 = df1.select(op_cols_same_case .head, op_cols_same_case .tail: _*)
df2.select("id").show()
This query runs fine.
But when we change the casing of the op_cols to have mix of upper & lower case
("id" & "ID") it throws an ambiguous col ref error:
val df1 =
sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
"col5")
val op_cols_same_case = List("id","col2","col3","col4", "col5", "ID")
val df2 = df1.select(op_cols_same_case .head, op_cols_same_case .tail: _*)
df2.select("id").show()
Since, Spark is case insensitive, it should work for second case also when we
have upper and lower case column names in the column list.
It also works fine in Spark 2.3.
was:
val df1 =
sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
"col5")
val op_cols_same_case = List("id","col2","col3","col4", "col5", "id")
val df2 = df1.select(op_cols_same_case .head, op_cols_same_case .tail: _*)
df2.select("id").show()
This query runs fine.
But when we change the casing of the op_cols to have mix of upper & lower case
("id" & "ID") it throws an ambiguous col ref error:
val df1 =
sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
"col5")
val op_cols_same_case = List("id","col2","col3","col4", "col5", "ID")
val df2 = df1.select(op_cols_same_case .head, op_cols_same_case .tail: _*)
df2.select("id").show()
Since, Spark is case insensitive, it should work for second case also when we
have upper and lower case column names in the column list.
> Incorrect ambiguous column reference error
> --
>
> Key: SPARK-42655
> URL: https://issues.apache.org/jira/browse/SPARK-42655
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
>Affects Versions: 3.2.0
>Reporter: Shrikant Prasad
>Priority: Major
>
> val df1 =
> sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
> "col5")
> val op_cols_same_case = List("id","col2","col3","col4", "col5", "id")
> val df2 = df1.select(op_cols_same_case .head, op_cols_same_case .tail: _*)
> df2.select("id").show()
>
> This query runs fine.
>
> But when we change the casing of the op_cols to have mix of upper & lower
> case ("id" & "ID") it throws an ambiguous col ref error:
>
> val df1 =
> sc.parallelize(List((1,2,3,4,5),(1,2,3,4,5))).toDF("id","col2","col3","col4",
> "col5")
> val op_cols_same_case = List("id","col2","col3","col4", "col5", "ID")
> val df2 = df1.select(op_cols_same_case .head, op_cols_same_case .tail: _*)
> df2.select("id").show()
>
> Since, Spark is case insensitive, it should work for second case also when we
> have upper and lower case column names in the column list.
> It also works fine in Spark 2.3.
>
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