anishshri-db commented on code in PR #45674:
URL: https://github.com/apache/spark/pull/45674#discussion_r1547185002
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sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StatefulProcessorHandleImpl.scala:
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@@ -77,14 +78,23 @@ class StatefulProcessorHandleImpl(
store: StateStore,
runId: UUID,
keyEncoder: ExpressionEncoder[Any],
+ ttlMode: TTLMode,
timeoutMode: TimeoutMode,
- isStreaming: Boolean = true)
+ isStreaming: Boolean = true,
+ batchTimestampMs: Option[Long] = None,
+ eventTimeWatermarkMs: Option[Long] = None)
extends StatefulProcessorHandle with Logging {
import StatefulProcessorHandleState._
+ /**
+ * Stores all the active ttl states, and is used to cleanup expired values
+ * in [[doTtlCleanup()]] function.
+ */
+ private val ttlStates: util.List[TTLState] = new util.ArrayList[TTLState]()
Review Comment:
Is there any reason to store this as Java list vs Scala seq (or other
equivalent data structures) ?
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