[
https://issues.apache.org/jira/browse/SPARK-12777?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15097327#comment-15097327
]
Jakob Odersky commented on SPARK-12777:
---------------------------------------
I get the same error in SparkShell, however everything works in a plain
application (as shown in the listing)
{code}
import org.apache.spark._
import org.apache.spark.sql._
case class Test(v: (Int, Int))
object Main {
val conf = new SparkConf().setMaster("local").setAppName("testbench")
val sc = new SparkContext(conf)
val sqlContext = new SQLContext(sc)
def main(args: Array[String]): Unit = {
import sqlContext.implicits._
val rdd = sc.parallelize(
Seq(
Test((1,2)),
Test((3,4))))
val ds = sqlContext.createDataset(rdd).toDS
ds.show
}
}
{code}
> Dataset fields can't be Scala tuples
> ------------------------------------
>
> Key: SPARK-12777
> URL: https://issues.apache.org/jira/browse/SPARK-12777
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.0, 1.6.1, 2.0.0
> Reporter: Chris Jansen
>
> Datasets can't seem to handle scala tuples as fields of case classes in
> datasets.
> {code}
> Seq((1,2), (3,4)).toDS().show() //works
> {code}
> When including a tuple as a field, the code fails:
> {code}
> case class Test(v: (Int, Int))
> Seq(Test((1,2)), Test((3,4)).toDS().show //fails
> {code}
> {code}
> UnresolvedException: : Invalid call to dataType on unresolved object, tree:
> 'name (unresolved.scala:59)
>
> org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute.dataType(unresolved.scala:59)
>
> org.apache.spark.sql.catalyst.expressions.GetStructField.org$apache$spark$sql$catalyst$expressions$GetStructField$$field$lzycompute(complexTypeExtractors.scala:107)
>
> org.apache.spark.sql.catalyst.expressions.GetStructField.org$apache$spark$sql$catalyst$expressions$GetStructField$$field(complexTypeExtractors.scala:107)
>
> org.apache.spark.sql.catalyst.expressions.GetStructField$$anonfun$toString$1.apply(complexTypeExtractors.scala:111)
>
> org.apache.spark.sql.catalyst.expressions.GetStructField$$anonfun$toString$1.apply(complexTypeExtractors.scala:111)
>
> org.apache.spark.sql.catalyst.expressions.GetStructField.toString(complexTypeExtractors.scala:111)
>
> org.apache.spark.sql.catalyst.expressions.Expression.toString(Expression.scala:217)
>
> org.apache.spark.sql.catalyst.expressions.Expression.toString(Expression.scala:217)
>
> org.apache.spark.sql.catalyst.expressions.If.toString(conditionalExpressions.scala:76)
>
> org.apache.spark.sql.catalyst.expressions.Expression.toString(Expression.scala:217)
>
> org.apache.spark.sql.catalyst.expressions.Alias.toString(namedExpressions.scala:155)
>
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$argString$1.apply(TreeNode.scala:385)
>
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$argString$1.apply(TreeNode.scala:381)
> org.apache.spark.sql.catalyst.trees.TreeNode.argString(TreeNode.scala:388)
> org.apache.spark.sql.catalyst.trees.TreeNode.simpleString(TreeNode.scala:391)
>
> org.apache.spark.sql.catalyst.plans.QueryPlan.simpleString(QueryPlan.scala:172)
>
> org.apache.spark.sql.catalyst.trees.TreeNode.generateTreeString(TreeNode.scala:441)
> org.apache.spark.sql.catalyst.trees.TreeNode.treeString(TreeNode.scala:396)
>
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$5.apply(RuleExecutor.scala:118)
>
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$5.apply(RuleExecutor.scala:119)
> org.apache.spark.Logging$class.logDebug(Logging.scala:62)
>
> org.apache.spark.sql.catalyst.rules.RuleExecutor.logDebug(RuleExecutor.scala:44)
>
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:115)
>
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72)
>
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72)
>
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.resolve(ExpressionEncoder.scala:253)
> org.apache.spark.sql.Dataset.<init>(Dataset.scala:78)
> org.apache.spark.sql.Dataset.<init>(Dataset.scala:89)
> org.apache.spark.sql.SQLContext.createDataset(SQLContext.scala:507)
>
> org.apache.spark.sql.SQLImplicits.localSeqToDatasetHolder(SQLImplicits.scala:80)
> {code}
> When providing a type alias, the code fails in a different way:
> {code}
> type TwoInt = (Int, Int)
> case class Test(v: TwoInt)
> Seq(Test((1,2)), Test((3,4)).toDS().show //fails
> {code}
> {code}
> NoSuchElementException: : head of empty list (ScalaReflection.scala:504)
>
> org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$extractorFor$1.apply(ScalaReflection.scala:504)
>
> org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$extractorFor$1.apply(ScalaReflection.scala:502)
>
> org.apache.spark.sql.catalyst.ScalaReflection$.org$apache$spark$sql$catalyst$ScalaReflection$$extractorFor(ScalaReflection.scala:502)
>
> org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$extractorFor$1.apply(ScalaReflection.scala:509)
>
> org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$extractorFor$1.apply(ScalaReflection.scala:502)
>
> org.apache.spark.sql.catalyst.ScalaReflection$.org$apache$spark$sql$catalyst$ScalaReflection$$extractorFor(ScalaReflection.scala:502)
>
> org.apache.spark.sql.catalyst.ScalaReflection$.extractorsFor(ScalaReflection.scala:394)
>
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$.apply(ExpressionEncoder.scala:54)
> org.apache.spark.sql.SQLImplicits.newProductEncoder(SQLImplicits.scala:41)
>
> com.intenthq.pipeline.actions.ActionsJobIntegrationSpec.enrich(ActionsJobIntegrationSpec.scala:63)
>
> com.intenthq.pipeline.actions.ActionsJobIntegrationSpec$$anonfun$is$2.apply(ActionsJobIntegrationSpec.scala:45)
>
> com.intenthq.pipeline.actions.ActionsJobIntegrationSpec$$anonfun$is$2.apply(ActionsJobIntegrationSpec.scala:45)
> {code}
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