[SPARK-13326] Dataset in spark 2.0.0-SNAPSHOT missing columns

• Type: Bug
• Status: Resolved
• Priority: Minor
• Resolution: Later
• Affects Version/s: 2.0.0
• Component/s: SQL
• Assignee: Unassigned
• Reporter: koert kuipers
• Created: 15/Feb/16 21:53
• Updated: 04/Apr/16 23:58
• Resolved: 04/Apr/16 23:58

Description

i noticed some things stopped working on datasets in spark 2.0.0-SNAPSHOT, and with a confusing error message (cannot resolved some column with input columns []).

for example in 1.6.0-SNAPSHOT:

scala> val ds = sc.parallelize(1 to 10).toDS
ds: org.apache.spark.sql.Dataset[Int] = [value: int]

scala> ds.map(x => Option(x))
res0: org.apache.spark.sql.Dataset[Option[Int]] = [value: int]

and same commands in 2.0.0-SNAPSHOT:

scala> val ds = sc.parallelize(1 to 10).toDS
ds: org.apache.spark.sql.Dataset[Int] = [value: int]

scala> ds.map(x => Option(x))
org.apache.spark.sql.AnalysisException: cannot resolve 'value' given input columns: [];
  at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:60)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:57)
  at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:284)
  at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:284)
  at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
  at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:283)
  at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionUp$1(QueryPlan.scala:162)
  at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2(QueryPlan.scala:172)
  at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2$1.apply(QueryPlan.scala:176)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
  at scala.collection.immutable.List.foreach(List.scala:381)
  at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
  at scala.collection.immutable.List.map(List.scala:285)
  at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2(QueryPlan.scala:176)
  at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$2.apply(QueryPlan.scala:181)
  at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
  at scala.collection.Iterator$class.foreach(Iterator.scala:742)
  at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
  at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
  at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
  at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
  at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:308)
  at scala.collection.AbstractIterator.to(Iterator.scala:1194)
  at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:300)
  at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1194)
  at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:287)
  at scala.collection.AbstractIterator.toArray(Iterator.scala:1194)
  at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:181)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:57)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:50)
  at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:122)
  at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:121)
  at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:121)
  at scala.collection.immutable.List.foreach(List.scala:381)
  at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:121)
  at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:50)
  at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:46)
  at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.resolve(ExpressionEncoder.scala:322)
  at org.apache.spark.sql.Dataset.<init>(Dataset.scala:81)
  at org.apache.spark.sql.Dataset.<init>(Dataset.scala:92)
  at org.apache.spark.sql.Dataset.mapPartitions(Dataset.scala:339)
  at org.apache.spark.sql.Dataset.map(Dataset.scala:323)
  ... 43 elided

i observed similar issues with user defined types (org.apache.spark.sql.types.UserDefinedType) in Dataset. trying to insert a UserDefinedType in Dataset[Row] fails with input columns [].

Issue Links

• relates to: SPARK-14155 Hide UserDefinedType in Spark 2.0