imback82 commented on a change in pull request #27391: [SPARK-30612][SQL]
Resolve qualified column name with v2 tables
URL: https://github.com/apache/spark/pull/27391#discussion_r374471639
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/package.scala
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@@ -204,13 +209,85 @@ package object expressions {
// If none of attributes match database.table.column pattern or
// `table.column` pattern, we try to resolve it as a column.
- val (candidates, nestedFields) = matches match {
+ matches match {
case (Seq(), _) =>
val name = nameParts.head
val attributes = collectMatches(name,
direct.get(name.toLowerCase(Locale.ROOT)))
(attributes, nameParts.tail)
case _ => matches
}
+ }
+
+ /**
+ * Match attributes for the case where at least one qualifier in `attrs`
has more than 2 parts.
+ */
+ private def matchWithThreeOrMorePartQualifiers(
+ nameParts: Seq[String],
+ resolver: Resolver): (Seq[Attribute], Seq[String]) = {
+ // Returns true if the `short` qualifier is a subset of the last
elements of
+ // `long` qualifier. For example, Seq("a", "b") is a subset of Seq("a",
"a", "b"),
+ // but not a subset of Seq("a", "b", "b").
+ def matchQualifier(short: Seq[String], long: Seq[String]): Boolean = {
+ (long.length >= short.length) &&
+ long.takeRight(short.length)
+ .zip(short)
+ .forall(x => resolver(x._1, x._2))
+ }
+
+ // Collect attributes that match the given name and qualifier.
+ // A match occurs if
+ // 1) the given name matches the attribute's name according to the
resolver.
+ // 2) the given qualifier is a subset of the attribute's qualifier.
+ def collectMatches(
+ name: String,
+ qualifier: Seq[String],
+ candidates: Option[Seq[Attribute]]): Seq[Attribute] = {
+ candidates.toSeq.flatMap(_.collect {
Review comment:
Yes, that's simpler. I will make changes to both places.
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