[
https://issues.apache.org/jira/browse/SPARK-49689?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
harikishore updated SPARK-49689:
--------------------------------
Description:
Spark added TimestampNTZType support since 3.4.0.
[https://spark.apache.org/docs/3.4.0/api/java/org/apache/spark/sql/types/TimestampNTZType.html]
However, EventTimeWatermark with TimestampNTZType fails analysis check.
{code:java}
case etw: EventTimeWatermark =>
etw.eventTime.dataType match {
case s: StructType
if s.find(_.name == "end").map(_.dataType) ==
Some(TimestampType) =>
case _: TimestampType =>
case _ =>
etw.failAnalysis(
errorClass = "EVENT_TIME_IS_NOT_ON_TIMESTAMP_TYPE",
messageParameters = Map(
"eventName" -> toSQLId(etw.eventTime.name),
"eventType" -> toSQLType(etw.eventTime.dataType)))
} {code}
Both *FilterPushdownSuite.scala* and *AnalysisSuite.scala* don't explicitly
avoid timestampNTZ. Moreover, from *StatefulAggregationStrategy* -->
{*}EventTimeWatermarkExec{*}, even if the eventTime is of type
TimestampNTZType, it should be handled as per
{*}datetimeExpressions{*}.{*}scala{*}. It is also supported in Window
Expressions {*}WindowSpecDefinition -> isValidFrameType{*}.
was:
Spark added TimestampNTZType support since 3.4.0.
[https://spark.apache.org/docs/3.4.0/api/java/org/apache/spark/sql/types/TimestampNTZType.html]
However, EventTimeWatermark with TimestampNTZType fails analysis check.
{quote}case etw: EventTimeWatermark =>
etw.eventTime.dataType match {
case s: StructType
if s.find(_.name == "end").map(_.dataType) ==
Some(TimestampType) =>
case _: TimestampType =>
case _ =>
etw.failAnalysis(
errorClass = "EVENT_TIME_IS_NOT_ON_TIMESTAMP_TYPE",
messageParameters = Map(
"eventName" -> toSQLId(etw.eventTime.name),
"eventType" -> toSQLType(etw.eventTime.dataType)))
}{quote}
Both *FilterPushdownSuite.scala* and *AnalysisSuite.scala* don't explicitly
avoid timestampNTZ. Moreover, from *StatefulAggregationStrategy* -->
{*}EventTimeWatermarkExec{*}, even if the eventTime is of type
TimestampNTZType, it should be handled as per
{*}datetimeExpressions{*}.{*}scala{*}. It is also supported in Window
Expressions {*}WindowSpecDefinition -> isValidFrameType{*}.
> EventTimeWatermark to support TimestampNTZType
> ----------------------------------------------
>
> Key: SPARK-49689
> URL: https://issues.apache.org/jira/browse/SPARK-49689
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
> Affects Versions: 3.4.0, 3.4.1, 3.5.0, 3.5.1, 3.5.2, 3.4.3
> Reporter: harikishore
> Priority: Major
> Fix For: 3.5.2
>
>
> Spark added TimestampNTZType support since 3.4.0.
> [https://spark.apache.org/docs/3.4.0/api/java/org/apache/spark/sql/types/TimestampNTZType.html]
> However, EventTimeWatermark with TimestampNTZType fails analysis check.
>
> {code:java}
> case etw: EventTimeWatermark =>
> etw.eventTime.dataType match {
> case s: StructType
> if s.find(_.name == "end").map(_.dataType) ==
> Some(TimestampType) =>
> case _: TimestampType =>
> case _ =>
> etw.failAnalysis(
> errorClass = "EVENT_TIME_IS_NOT_ON_TIMESTAMP_TYPE",
> messageParameters = Map(
> "eventName" -> toSQLId(etw.eventTime.name),
> "eventType" -> toSQLType(etw.eventTime.dataType)))
> } {code}
> Both *FilterPushdownSuite.scala* and *AnalysisSuite.scala* don't explicitly
> avoid timestampNTZ. Moreover, from *StatefulAggregationStrategy* -->
> {*}EventTimeWatermarkExec{*}, even if the eventTime is of type
> TimestampNTZType, it should be handled as per
> {*}datetimeExpressions{*}.{*}scala{*}. It is also supported in Window
> Expressions {*}WindowSpecDefinition -> isValidFrameType{*}.
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