HeartSaVioR commented on code in PR #40561:
URL: https://github.com/apache/spark/pull/40561#discussion_r1153935588
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/statefulOperators.scala:
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@@ -980,3 +1022,65 @@ object StreamingDeduplicateExec {
private val EMPTY_ROW =
UnsafeProjection.create(Array[DataType](NullType)).apply(InternalRow.apply(null))
}
+
+case class StreamingDeduplicateWithinWatermarkExec(
+ keyExpressions: Seq[Attribute],
+ child: SparkPlan,
+ stateInfo: Option[StatefulOperatorStateInfo] = None,
+ eventTimeWatermarkForLateEvents: Option[Long] = None,
+ eventTimeWatermarkForEviction: Option[Long] = None)
+ extends BaseStreamingDeduplicateExec {
+
+ protected val schemaForValueRow: StructType = StructType(
+ Array(StructField("expiresAt", LongType, nullable = false)))
Review Comment:
Let's consolidate this to below comment thread. I pinged Gengliang in below
comment to understand what is the use case story for TimestampType vs
TimestampNTZType, is the type somehow interchangeable, etc. Before that, I'll
just roll back the change to match with flatMapGroupsWithState.
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