grundprinzip commented on code in PR #38970:
URL: https://github.com/apache/spark/pull/38970#discussion_r1042952381
##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala:
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@@ -518,9 +518,16 @@ class SparkConnectPlanner(session: SparkSession) {
}
private def transformCast(cast: proto.Expression.Cast): Expression = {
- Cast(
- transformExpression(cast.getExpr),
- DataTypeProtoConverter.toCatalystType(cast.getCastToType))
+ cast.getCastToTypeCase match {
+ case proto.Expression.Cast.CastToTypeCase.TYPE =>
+ Cast(
+ transformExpression(cast.getExpr),
+ DataTypeProtoConverter.toCatalystType(cast.getType))
+ case _ =>
+ Cast(
+ transformExpression(cast.getExpr),
+ session.sessionState.sqlParser.parseDataType(cast.getTypeStr))
Review Comment:
When I looked at cast as a unicorn in the context of expressions, it's one
of the few where not all argument types resolve to expressions. I was wondering
if we could simplify the approach to make the type argument of cast an
expression that can resolve as a string then we can do the matching of the
expression in the analyzer.
This is very similar to why you added the oneof to the proto message.
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