AngersZhuuuu commented on a change in pull request #30775:
URL: https://github.com/apache/spark/pull/30775#discussion_r554810061
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File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
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@@ -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. 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] = {
Review comment:
> can users work around it by calling untyped join and use `as[T]` to
get the typed dataset?
Logically, yes. But seems not not very convenient or direct.
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