JacksonKjar commented on code in PR #59215:
URL: https://github.com/apache/spark/pull/59215#discussion_r4343098167
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sql/api/src/main/scala/org/apache/spark/sql/catalyst/JavaTypeInference.scala:
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@@ -186,6 +188,45 @@ object JavaTypeInference {
throw ExecutionErrors.cannotFindEncoderForTypeError(t.toString)
}
+ /**
+ * Infer an [[AgnosticEncoder]] for a Java record (`java.lang.Record`).
Fields follow component
+ * declaration order and are read through the component accessors. Like the
JavaBean case,
+ * components are resolved through `encoderFor`, which carries `seenTypeSet`
and `typeVariables`
+ * into nested components.
+ */
+ private def encoderForJavaRecord[T](
+ recordClass: Class[T],
+ seenTypeSet: Set[Class[_]],
+ typeVariables: Map[TypeVariable[_], Type]): JavaRecordEncoder[T] = {
+ if (seenTypeSet.contains(recordClass)) {
+ throw
ExecutionErrors.cannotHaveCircularReferencesInBeanClassError(recordClass)
+ }
+
+ // Type parameters are erased, so they can only be resolved when the
enclosing type binds
+ // them (e.g. a `Box<String>` component), which puts them in
`typeVariables`.
+ val unboundTypeParams =
recordClass.getTypeParameters.filterNot(typeVariables.contains)
+ if (unboundTypeParams.nonEmpty) {
+ throw ExecutionErrors.genericRecordNotSupportedError(recordClass)
+ }
+
+ val fields = recordClass.getRecordComponents.map { component =>
+ val accessor = component.getAccessor
+ val encoder = encoderFor(component.getGenericType, seenTypeSet +
recordClass, typeVariables)
+ // The existence of `javax.annotation.Nonnull` means this component is
not nullable.
+ val hasNonNull = accessor.isAnnotationPresent(classOf[Nonnull])
Review Comment:
Good catch, thanks. I applied the suggested fix in ad5bdeb and added unit
tests covering components with explicit accessors both with and without
`@Nonnull`
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