AngersZhuuuu commented on a change in pull request #30775:
URL: https://github.com/apache/spark/pull/30775#discussion_r543843221
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
##########
@@ -1240,6 +1240,40 @@ class Dataset[T] private[sql](
joinWith(other, condition, "inner")
}
+ /**
+ * Joins this Dataset returning value of left where `condition` evaluates to
true.
+ *
+ * This is similar to the relation `join` function with one important
difference in the
+ * result schema. Since `joinPartial` preserves objects present on left side
of the join, the
+ * result schema is similarly nested into one column names `_1`.
+ *
+ * This type of join can be useful both for preserving type-safety with the
original object
+ * types as well as working with relational data where either side of the
join has column
+ * names in common.
+ *
+ * @param other Right side of the join.
+ * @param condition Join expression.
+ * @param joinType Type of join to perform. Default `inner`. Must be one of:
+ * `left_semi`, `left_anti`.
+ *
+ * @group typedrel
+ * @since 3.1.0
+ */
+ def joinPartial[U](other: Dataset[U], condition: Column, joinType: String):
Dataset[T] = {
+ val joinedType = JoinType(joinType)
+
+ if (joinedType != LeftSemi && joinedType != LeftAnti) {
+ throw new AnalysisException("Invalid join type in joinPartial: " +
joinedType.sql)
Review comment:
> Better to have an actionable message like in the case of other join
types, use `joinWith or join` API.
Nice suggestion.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
