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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/03/25 21:38:25 UTC
[jira] [Updated] (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:all-tabpanel ]
Sean Owen updated SPARK-14165:
------------------------------
Issue Type: Improvement (was: Bug)
It's case sensitive right? your tables don't actually both have a column "abc" that your join condition claims. Are you just looking to improve the exception? that's fine.
> 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 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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