sahnib commented on code in PR #45674:
URL: https://github.com/apache/spark/pull/45674#discussion_r1543444350
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sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StateTypesEncoderUtils.scala:
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@@ -23,11 +23,19 @@ import
org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.Serializer
import org.apache.spark.sql.catalyst.encoders.encoderFor
import org.apache.spark.sql.catalyst.expressions.{UnsafeProjection, UnsafeRow}
import org.apache.spark.sql.execution.streaming.state.StateStoreErrors
-import org.apache.spark.sql.types.{BinaryType, StructType}
+import org.apache.spark.sql.types.{BinaryType, LongType, StructType}
object StateKeyValueRowSchema {
val KEY_ROW_SCHEMA: StructType = new StructType().add("key", BinaryType)
- val VALUE_ROW_SCHEMA: StructType = new StructType().add("value", BinaryType)
+ val VALUE_ROW_SCHEMA: StructType = new StructType()
+ .add("value", BinaryType)
+ .add("ttlExpirationMs", LongType)
Review Comment:
Removed logging for ttlExpiration if ttl is disabled. In order to support
this functionality, I have split ValueState into ValueStateImpl and
ValueStateImplWithTTL - to prevent un-necessary ttlMode checks for each
function.
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StateTypesEncoderUtils.scala:
##########
@@ -62,33 +70,79 @@ class StateTypesEncoder[GK, V](
private val rowToObjDeserializer =
valExpressionEnc.resolveAndBind().createDeserializer()
private val reusedValRow = new UnsafeRow(valEncoder.schema.fields.length)
+ private val NO_TTL_ENCODED_VALUE: Long = -1L
Review Comment:
Done.
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