stefankandic commented on code in PR #46280:
URL: https://github.com/apache/spark/pull/46280#discussion_r1595221619
##########
sql/api/src/main/scala/org/apache/spark/sql/types/StructField.scala:
##########
@@ -63,7 +66,60 @@ case class StructField(
("name" -> name) ~
("type" -> dataType.jsonValue) ~
("nullable" -> nullable) ~
- ("metadata" -> metadata.jsonValue)
+ ("metadata" -> metadataJson)
+ }
+
+ private def metadataJson: JValue = {
+ val metadataJsonValue = metadata.jsonValue
+ metadataJsonValue match {
+ case JObject(fields) if collationMetadata.nonEmpty =>
+ val collationFields = collationMetadata.map(kv => kv._1 ->
JString(kv._2)).toList
+ JObject(fields :+ (DataType.COLLATIONS_METADATA_KEY ->
JObject(collationFields)))
+
+ case _ => metadataJsonValue
+ }
+ }
+
+ /** Map of field path to collation name. */
+ private lazy val collationMetadata: mutable.Map[String, String] = {
+ val fieldToCollationMap = mutable.Map[String, String]()
+
+ def visitRecursively(dt: DataType, path: String): Unit = dt match {
+ case at: ArrayType =>
+ processDataType(at.elementType, path + ".element")
+
+ case mt: MapType =>
+ processDataType(mt.keyType, path + ".key")
+ processDataType(mt.valueType, path + ".value")
+
+ case st: StringType if isCollatedString(st) =>
+ fieldToCollationMap(path) = collationName(st)
+
+ case _ =>
+ }
+
+ def processDataType(dt: DataType, path: String): Unit = {
+ if (isCollatedString(dt)) {
+ fieldToCollationMap(path) = collationName(dt)
+ } else {
+ visitRecursively(dt, path)
+ }
+ }
+
+ visitRecursively(dataType, name)
Review Comment:
I added a test to be sure this works, but I don't see why we would need any
special logic for this case.
Even if we have a column name.key this will never be ambiguous in the
metadata as the struct field could be a string or a map but never both, so
parsing will just work regardless - we could never have a case of adding the
collation two times.
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