bogao007 commented on code in PR #41558:
URL: https://github.com/apache/spark/pull/41558#discussion_r1231423248
##########
connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala:
##########
@@ -462,6 +462,15 @@ abstract class KeyValueGroupedDataset[K, V] private[sql]
() extends Serializable
UdfUtils.coGroupFunctionToScalaFunc(f))(encoder)
}
+ protected def flatMapGroupsWithStateHelper[S: Encoder, U: Encoder](
+ outputMode: OutputMode,
+ timeoutConf: GroupStateTimeout,
+ initialState: KeyValueGroupedDataset[K, S],
Review Comment:
> But we could also just use an ultimate `flatMapGroupsWithState` that
achieves the same goal as @zhenlineo suggested and still delete this helper
method.
It would be hard to achieve this since the original `flatMapGroupsWithState`
methods doesn't contain a boolean to decide if it's `flatMapGroupsWithState` or
`mapGroupsWIthState`. If we add that boolean, then it's the same as the helper
function approach. Otherwise we have to maintain 2 different implementations
##########
connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala:
##########
@@ -462,6 +462,15 @@ abstract class KeyValueGroupedDataset[K, V] private[sql]
() extends Serializable
UdfUtils.coGroupFunctionToScalaFunc(f))(encoder)
}
+ protected def flatMapGroupsWithStateHelper[S: Encoder, U: Encoder](
+ outputMode: OutputMode,
+ timeoutConf: GroupStateTimeout,
+ initialState: KeyValueGroupedDataset[K, S],
Review Comment:
> But we could also just use an ultimate `flatMapGroupsWithState` that
achieves the same goal as @zhenlineo suggested and still delete this helper
method.
It would be hard to achieve this since the original `flatMapGroupsWithState`
methods doesn't contain a boolean to decide if it's `flatMapGroupsWithState` or
`mapGroupsWIthState`. If we add that boolean, then it's the same as the helper
function approach. Otherwise we have to maintain 2 different implementations
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