Github user mike0sv commented on a diff in the pull request:
https://github.com/apache/spark/pull/18488#discussion_r125358120
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/JavaTypeInference.scala
---
@@ -127,19 +128,24 @@ object JavaTypeInference {
// TODO: we should only collect properties that have getter and
setter. However, some tests
// pass in scala case class as java bean class which doesn't have
getter and setter.
- val properties = getJavaBeanReadableProperties(other)
- val fields = properties.map { property =>
- val returnType =
typeToken.method(property.getReadMethod).getReturnType
- val (dataType, nullable) = inferDataType(returnType, seenTypeSet
+ other)
- new StructField(property.getName, dataType, nullable)
+ if (typeToken.getRawType.isEnum) {
--- End diff --
Probably, but int is cheaper. However, if we use string, there will be a
possibility for meaningful queries. Also, there are strange cases with complex
enums with different fields, even with complex types. I'd say string with
constant name is enough, thou
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