AngersZhuuuu commented on a change in pull request #29085:
URL: https://github.com/apache/spark/pull/29085#discussion_r454941778
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File path:
sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveScriptTransformationExec.scala
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@@ -78,17 +78,25 @@ case class HiveScriptTransformationExec(
stderrBuffer,
"Thread-ScriptTransformation-STDERR-Consumer").start()
- val outputProjection = new InterpretedProjection(input, child.output)
-
// This nullability is a performance optimization in order to avoid an
Option.foreach() call
// inside of a loop
@Nullable val (inputSerde, inputSoi) =
ioschema.initInputSerDe(input).getOrElse((null, null))
+ // For HiveScriptTransformationExec, if inputSerde == null, but
outputSerde != null
+ // We will use StringBuffer to pass data, in this case, we should cast
data as string too.
+ val finalInput = if (inputSerde == null) {
+ input.map(Cast(_, StringType).withTimeZone(conf.sessionLocalTimeZone))
Review comment:
> Ur, ... what's an answer of my question? You meant we might get a
behaviour change, but that's not a problem? (what's a normal type?) At least, I
think we need to define supported an unsupported cases, clearly (& add tests
for all the cases).
As alfozan said, here we implement a limited data wrapper like row
formatted. tread all data as string.
https://github.com/apache/spark/pull/29085#discussion_r454298255
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