rahulsmahadev commented on a change in pull request #33336:
URL: https://github.com/apache/spark/pull/33336#discussion_r670821139
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FlatMapGroupsWithStateExec.scala
##########
@@ -404,3 +402,72 @@ case class FlatMapGroupsWithStateExec(
copy(child = newLeft, initialState = newRight)
}
+object FlatMapGroupsWithStateExec {
+
+ def foundDuplicateInitialKeyException(): Exception = {
+ throw new IllegalArgumentException("The initial state provided contained "
+
+ "multiple rows(state) with the same key. Make sure to de-duplicate the "
+
+ "initial state before passing it.")
+ }
+
+ /**
+ * Special handling for when the child relation is a batch relation.
+ * If the initial state is provided, we create an instance of the
CoGroupExec, if the initial
+ * state is not provided we create an instance of the MapGroupsExec
+ */
+ // scalastyle:off argcount
+ def forBatch(
+ userFunc: (Any, Iterator[Any], LogicalGroupState[Any]) => Iterator[Any],
+ keyDeserializer: Expression,
+ valueDeserializer: Expression,
+ initialStateDeserializer: Expression,
+ groupingAttributes: Seq[Attribute],
+ initialStateGroupAttrs: Seq[Attribute],
+ dataAttributes: Seq[Attribute],
+ initialStateDataAttrs: Seq[Attribute],
+ outputObjAttr: Attribute,
+ timeoutConf: GroupStateTimeout,
+ hasInitialState: Boolean,
+ initialState: SparkPlan,
+ child: SparkPlan): SparkPlan = {
+ if (hasInitialState) {
+ val watermarkPresent = child.output.exists {
+ case a: Attribute if a.metadata.contains(EventTimeWatermark.delayKey)
=> true
+ case _ => false
+ }
+ val func = (keyRow: Any, values: Iterator[Any], states: Iterator[Any])
=> {
+ // Check if there is only one state for every key.
+ var foundInitialStateForKey = false
+ val optionalState = states.map { initialState =>
+ if (foundInitialStateForKey) {
+ foundDuplicateInitialKeyException()
+ }
+ foundInitialStateForKey = true
+ initialState
+ }.toSeq
+
+ // Create group state object
+ val groupState = GroupStateImpl.createForStreaming(
Review comment:
createForStreaming is a misnomer actually. it is just create a
groupStateImpl object using the parameters
https://livegrep.dev.databricks.com/view/databricks/runtime/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/GroupStateImpl.scala#L202
createForbatch is infact creating groupStateImpl without the state
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