[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15815105#comment-15815105
]
Jacek Laskowski commented on SPARK-14165:
-
It can be closed but with FIXED resolution since it was indeed an issue that
was fixed in the meantime.
For the record, Spark 2.2.0-SNAPSHOT gives:
{code}
scala> val left = Seq((1,"a")).toDF("id", "abc")
left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
scala> val right = Seq((1,"a")).toDF("id", "ABC")
right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
scala> left.join(right, Seq("abc")).show
+---+---+---+
|abc| id| id|
+---+---+---+
| a| 1| 1|
+---+---+---+
scala> right.printSchema
root
|-- id: integer (nullable = false)
|-- ABC: string (nullable = true)
{code}
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:553)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:526)
> ... 51 elided
> {code}
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[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15814823#comment-15814823
]
Sean Owen commented on SPARK-14165:
---
Either the description needs to be edited to reflect the actual remaining
problem or else closed, sure.
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:553)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:526)
> ... 51 elided
> {code}
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[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15814312#comment-15814312
]
Hyukjin Kwon commented on SPARK-14165:
--
Hi all, should we resolve this JIRA as {{Cannot Reproduce}} and open another if
needed?
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:553)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:526)
> ... 51 elided
> {code}
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[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15420541#comment-15420541
]
Jacek Laskowski commented on SPARK-14165:
-
Thanks [~dongjoon] for looking into it. Yes, the more general join works fine.
I think the other example where the join expression is given should be fixed.
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:553)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:526)
> ... 51 elided
> {code}
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[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15420527#comment-15420527
]
Dongjoon Hyun commented on SPARK-14165:
---
I'm wondering if we need to fix the example in your comment. This is still the
same.
{code}
scala> left.join(right, $"abc" === $"ABC")
org.apache.spark.sql.AnalysisException: Reference 'abc' is ambiguous, could be:
abc#6, abc#16.;
{code}
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:553)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:526)
> ... 51 elided
> {code}
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[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15420525#comment-15420525
]
Dongjoon Hyun commented on SPARK-14165:
---
Hi, [~ja...@japila.pl].
Spark 2.0 seems to be released without this problem.
{code}
scala> val left = Seq((1,"a")).toDF("id", "abc")
scala> val right = Seq((1,"a")).toDF("id", "ABC")
scala> left.join(right, Seq("abc")).show
+---+---+---+
|abc| id| id|
+---+---+---+
| a| 1| 1|
+---+---+---+
scala> spark.version
res1: String = 2.0.0
{code}
Could you confirm this?
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:553)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:526)
> ... 51 elided
> {code}
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[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15216187#comment-15216187
]
Subhobrata Dey commented on SPARK-14165:
Hi [~jlaskowski],
I think the issue is already fixed in the latest 2.0.0-SNAPSHOT. The exception
message looks better now.
org.apache.spark.sql.AnalysisException: using columns ['abc] can not be
resolved given input columns: [id, abc, id, ABC] ;
Do you want any further changes?
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:553)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:526)
> ... 51 elided
> {code}
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[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15215477#comment-15215477
]
Jacek Laskowski commented on SPARK-14165:
-
Go ahead! Thanks!
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:553)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:526)
> ... 51 elided
> {code}
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[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15215333#comment-15215333
]
Subhobrata Dey commented on SPARK-14165:
Hi [~jlaskowski],
If nobody is working on this issue, I would like to work on this issue. Is it
possible to assign this to me?
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:553)
> at org.apache.spark.sql.Dataset.join(Dataset.scala:526)
> ... 51 elided
> {code}
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[jira] [Commented] (SPARK-14165) NoSuchElementException: None.get when joining DataFrames with Seq of fields of different case
[
https://issues.apache.org/jira/browse/SPARK-14165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15212365#comment-15212365
]
Jacek Laskowski commented on SPARK-14165:
-
Right, but:
{code}
scala> left.join(right, $"abc" === $"ABC")
org.apache.spark.sql.AnalysisException: Reference 'abc' is ambiguous, could be:
abc#378, abc#386.;
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolve(LogicalPlan.scala:261)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveChildren(LogicalPlan.scala:145)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$12$$anonfun$applyOrElse$6$$anonfun$24.apply(Analyzer.scala:572)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$12$$anonfun$applyOrElse$6$$anonfun$24.apply(Analyzer.scala:572)
at
org.apache.spark.sql.catalyst.analysis.package$.withPosition(package.scala:48)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$12$$anonfun$applyOrElse$6.applyOrElse(Analyzer.scala:572)
{code}
It sees the two columns as the same, doesn't it?
> NoSuchElementException: None.get when joining DataFrames with Seq of fields
> of different case
> -
>
> Key: SPARK-14165
> URL: https://issues.apache.org/jira/browse/SPARK-14165
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 2.0.0
>Reporter: Jacek Laskowski
>Priority: Minor
>
> {code}
> scala> val left = Seq((1,"a")).toDF("id", "abc")
> left: org.apache.spark.sql.DataFrame = [id: int, abc: string]
> scala> val right = Seq((1,"a")).toDF("id", "ABC")
> right: org.apache.spark.sql.DataFrame = [id: int, ABC: string]
> scala> left.join(right, Seq("abc"))
> java.util.NoSuchElementException: None.get
> at scala.None$.get(Option.scala:347)
> at scala.None$.get(Option.scala:345)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$$anonfun$62.apply(Analyzer.scala:1444)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$commonNaturalJoinProcessing(Analyzer.scala:1444)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1426)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$$anonfun$apply$29.applyOrElse(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:58)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:67)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:57)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1418)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveNaturalAndUsingJoin$.apply(Analyzer.scala:1417)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:41)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:58)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2299)
> at
