anishshri-db commented on code in PR #43961:
URL: https://github.com/apache/spark/pull/43961#discussion_r1430640516
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/object.scala:
##########
@@ -569,6 +569,41 @@ case class FlatMapGroupsWithState(
copy(child = newLeft, initialState = newRight)
}
+object TransformWithState {
+ def apply[K: Encoder, V: Encoder, U: Encoder](
+ groupingAttributes: Seq[Attribute],
Review Comment:
Done
##########
sql/core/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala:
##########
@@ -642,6 +642,37 @@ class KeyValueGroupedDataset[K, V] private[sql](
outputMode, timeoutConf, initialState)(f)(stateEncoder, outputEncoder)
}
+ /**
+ * (Scala-specific)
+ * Invokes methods defined in the stateful processor used in arbitrary state
API v2.
+ * We allow the user to act on per-group set of input rows along with keyed
state and the
+ * user can choose to output/return 0 or more rows.
+ * For a static/batch dataset, this operator is not supported and will throw
an exception.
+ * For a streaming dataframe, we will repeatedly invoke the interface
methods for new rows
+ * in each trigger and the user's state/state variables will be stored
persistently across
+ * invocations.
+ *
+ * @tparam U The type of the output objects. Must be encodable to Spark SQL
types.
+ * @param statefulProcessor Instance of statefulProcessor whose functions
will be invoked by the
+ * operator.
+ * @param outputMode The output mode of the stateful processor. Defaults to
APPEND mode.
+ *
+ */
+ def transformWithState[U: Encoder]
+ (statefulProcessor: StatefulProcessor[K, V, U],
Review Comment:
Done
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