Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/15072#discussion_r82728292
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala ---
@@ -53,7 +53,15 @@ import org.apache.spark.util.Utils
private[sql] object Dataset {
def apply[T: Encoder](sparkSession: SparkSession, logicalPlan:
LogicalPlan): Dataset[T] = {
- new Dataset(sparkSession, logicalPlan, implicitly[Encoder[T]])
+ val encoder = implicitly[Encoder[T]]
+ if (encoder.clsTag.runtimeClass == classOf[Row]) {
+ // We should use the encoder generated from the executed plan rather
than the existing
+ // encoder for DataFrame because the types of columns can be varied
due to widening types.
+ // See SPARK-17123. This is a bit hacky. Maybe we should find a
better way to do this.
+ ofRows(sparkSession, logicalPlan).asInstanceOf[Dataset[T]]
+ } else {
+ new Dataset(sparkSession, logicalPlan, encoder)
+ }
--- End diff --
Hm, I manually tested. It seems `except` is failed too. It seems fine with
`intersect`.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
