[GitHub] [spark] zsxwing commented on a diff in pull request #40561: [SPARK-42931][SS] Introduce dropDuplicatesWithinWatermark

["zsxwing (via GitHub)" <gi...@apache.org>]

zsxwing commented on code in PR #40561:
URL: https://github.com/apache/spark/pull/40561#discussion_r1152772092


##########
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/statefulOperators.scala:
##########
@@ -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)))
+
+  protected val extraOptionOnStateStore: Map[String, String] = Map.empty
+
+  private val eventTimeCol: Attribute = WatermarkSupport.findEventTimeColumn(child.output,
+    allowMultipleEventTimeColumns = false).get
+  private val delayThresholdMs = eventTimeCol.metadata.getLong(EventTimeWatermark.delayKey)
+  private val eventTimeColOrdinal: Int = child.output.indexOf(eventTimeCol)
+
+  protected def initializeReusedDupInfoRow(): Option[UnsafeRow] = {
+    val timeoutToUnsafeRow = UnsafeProjection.create(schemaForValueRow)
+    val timeoutRow = timeoutToUnsafeRow(new SpecificInternalRow(schemaForValueRow))
+    Some(timeoutRow)
+  }
+
+  protected def putDupInfoIntoState(
+      store: StateStore,
+      data: UnsafeRow,
+      key: UnsafeRow,
+      reusedDupInfoRow: Option[UnsafeRow]): Unit = {
+    assert(reusedDupInfoRow.isDefined, "This should have reused row.")
+    val timeoutRow = reusedDupInfoRow.get
+
+    val timestamp = data.getLong(eventTimeColOrdinal)
+    // The unit of timestamp in Spark is microseconds, convert the delay threshold to micros.
+    val expiresAt = timestamp + delayThresholdMs * 1000

Review Comment:
   nit: Should we use `org.apache.spark.sql.catalyst.util.DateTimeUtils#millisToMicros` to handle overflow (e.g., the user sets a very large `delayThresholdMs`)? We can fix this later since you are just following the current `watermarkExpression` code.



##########
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/statefulOperators.scala:
##########
@@ -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:
   QQ: why use LongType rather than `TimestampType`?



##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala:
##########
@@ -679,6 +679,8 @@ object RemoveNoopUnion extends Rule[LogicalPlan] {
       d.withNewChildren(Seq(simplifyUnion(u)))
     case d @ Deduplicate(_, u: Union) =>
       d.withNewChildren(Seq(simplifyUnion(u)))
+    case d @ DeduplicateWithinWatermark(_, u: Union) =>

Review Comment:
   > I don't think semantic deferences require disabling batch.
   
   +1. I don't see why this should be different than the existing `dropDuplicates`.



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