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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2017/06/25 10:45:01 UTC
[jira] [Assigned] (SPARK-21204) RuntimeException with Set and Case
Class in Spark 2.1.1
[ https://issues.apache.org/jira/browse/SPARK-21204?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-21204:
------------------------------------
Assignee: (was: Apache Spark)
> RuntimeException with Set and Case Class in Spark 2.1.1
> -------------------------------------------------------
>
> Key: SPARK-21204
> URL: https://issues.apache.org/jira/browse/SPARK-21204
> Project: Spark
> Issue Type: Bug
> Components: Optimizer, SQL
> Affects Versions: 2.1.1
> Reporter: Leo Romanovsky
>
> When attempting to produce a Dataset containing a Set, such as with:
> {code:java}
> dbData
> .groupBy("userId")
> .agg(functions.collect_set("friendId") as "friendIds")
> .as[(Int, Set[Int])]
> {code}
> An exception occurs. This can be avoided by casting to a Seq, but sometimes it makes more logical sense have a Set, especially when using the collect_set aggregation operation. Additionally, I am unable to write this Dataset to a Cassandra table containing a Set column without first converting to an RDD.
> {code:java}
> [error] Exception in thread "main" java.lang.UnsupportedOperationException: No Encoder found for Set[Int]
> [error] - field (class: "scala.collection.immutable.Set", name: "_2")
> [error] - root class: "scala.Tuple2"
> [error] at org.apache.spark.sql.catalyst.ScalaReflection$.org$apache$spark$sql$catalyst$ScalaReflection$$serializerFor(ScalaReflection.scala:602)
> [error] at org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$9.apply(ScalaReflection.scala:596)
> [error] at org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$9.apply(ScalaReflection.scala:587)
> [error] at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:252)
> [error] at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:252)
> [error] at scala.collection.immutable.List.foreach(List.scala:381)
> [error] at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:252)
> [error] at scala.collection.immutable.List.flatMap(List.scala:344)
> [error] at org.apache.spark.sql.catalyst.ScalaReflection$.org$apache$spark$sql$catalyst$ScalaReflection$$serializerFor(ScalaReflection.scala:587)
> [error] at org.apache.spark.sql.catalyst.ScalaReflection$.serializerFor(ScalaReflection.scala:425)
> [error] at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$.apply(ExpressionEncoder.scala:71)
> [error] at org.apache.spark.sql.Encoders$.product(Encoders.scala:275)
> [error] at org.apache.spark.sql.SQLImplicits.newProductEncoder(SQLImplicits.scala:49)
> {code}
> I think the resolution to this might be similar to adding the Map type - https://github.com/apache/spark/pull/16986
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