[SPARK-19758] Casting string to timestamp in inline table definition fails with AnalysisException

• Type: Bug
• Status: Resolved
• Priority: Blocker
• Resolution: Fixed
• Affects Version/s: 2.2.0
• Fix Version/s: 2.2.0
• Component/s: SQL
• Target Version/s: 2.2.0
• Assignee: L. C. Hsieh
• Reporter: Josh Rosen
• Created: 28/Feb/17 01:04
• Updated: 03/Mar/17 15:15
• Resolved: 03/Mar/17 15:15

Description

The following query runs succesfully on Spark 2.1.x but fails in the current master:

sql("""CREATE TEMPORARY VIEW table_4(timestamp_col_3) AS VALUES TIMESTAMP('1991-12-06 00:00:00.0')""")

Here's the error:

scala> sql("""CREATE TEMPORARY VIEW table_4(timestamp_col_3) AS VALUES TIMESTAMP('1991-12-06 00:00:00.0')""")
org.apache.spark.sql.AnalysisException: failed to evaluate expression CAST('1991-12-06 00:00:00.0' AS TIMESTAMP): None.get; line 1 pos 50
  at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
  at org.apache.spark.sql.catalyst.analysis.ResolveInlineTables$$anonfun$4$$anonfun$apply$4.apply(ResolveInlineTables.scala:105)
  at org.apache.spark.sql.catalyst.analysis.ResolveInlineTables$$anonfun$4$$anonfun$apply$4.apply(ResolveInlineTables.scala:95)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
  at scala.collection.immutable.List.foreach(List.scala:381)
  at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
  at scala.collection.immutable.List.map(List.scala:285)
  at org.apache.spark.sql.catalyst.analysis.ResolveInlineTables$$anonfun$4.apply(ResolveInlineTables.scala:95)
  at org.apache.spark.sql.catalyst.analysis.ResolveInlineTables$$anonfun$4.apply(ResolveInlineTables.scala:94)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
  at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
  at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
  at scala.collection.AbstractTraversable.map(Traversable.scala:104)
  at org.apache.spark.sql.catalyst.analysis.ResolveInlineTables$.convert(ResolveInlineTables.scala:94)
  at org.apache.spark.sql.catalyst.analysis.ResolveInlineTables$$anonfun$apply$1.applyOrElse(ResolveInlineTables.scala:36)
  at org.apache.spark.sql.catalyst.analysis.ResolveInlineTables$$anonfun$apply$1.applyOrElse(ResolveInlineTables.scala:32)
  at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
  at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
  at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
  at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:288)
  at org.apache.spark.sql.catalyst.analysis.ResolveInlineTables$.apply(ResolveInlineTables.scala:32)
  at org.apache.spark.sql.catalyst.analysis.ResolveInlineTables$.apply(ResolveInlineTables.scala:31)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
  at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
  at scala.collection.immutable.List.foldLeft(List.scala:84)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
  at scala.collection.immutable.List.foreach(List.scala:381)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
  at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:65)
  at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:63)
  at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:51)
  at org.apache.spark.sql.execution.command.CreateViewCommand.run(views.scala:128)
  at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)
  at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)
  at org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:67)
  at org.apache.spark.sql.Dataset.<init>(Dataset.scala:182)
  at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:67)
  at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:588)
  ... 48 elided

It appears that this bug was introduced by SPARK-18936. /cc ueshin

Issue Links

• relates to: SPARK-18936 Infrastructure for session local timezone support
• links to: [Github] Pull Request #17114 (viirya)