beliefer commented on a change in pull request #32513:
URL: https://github.com/apache/spark/pull/32513#discussion_r645379831
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/HiveResult.scala
##########
@@ -67,12 +67,38 @@ object HiveResult {
command.executeCollect().map(_.getString(1))
case other =>
val timeFormatters = getTimeFormatters
- val result: Seq[Seq[Any]] =
other.executeCollectPublic().map(_.toSeq).toSeq
- // We need the types so we can output struct field names
- val types = executedPlan.output.map(_.dataType)
- // Reformat to match hive tab delimited output.
- result.map(_.zip(types).map(e => toHiveString(e, false, timeFormatters)))
- .map(_.mkString("\t"))
+ val commandPhysicalPlans = other collect {
Review comment:
OK
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/QueryExecution.scala
##########
@@ -73,12 +76,33 @@ class QueryExecution(
sparkSession.sessionState.analyzer.executeAndCheck(logical, tracker)
}
+ // SPARK-35378: Commands should be executed eagerly so that `sql("INSERT
...")` can trigger the
+ // table insertion immediately without a `.collect()`. We also need to
eagerly execute non-root
+ // commands, because many commands return `GenericInternalRow` and can't be
put in a query plan
+ // directly, otherwise the query engine may cast `GenericInternalRow` to
`UnsafeRow` and fail.
+ lazy val commandExecuted: LogicalPlan = if (isExecutingCommand) {
+ analyzed.mapChildren(eagerlyExecuteCommands)
+ } else {
+ eagerlyExecuteCommands(analyzed)
+ }
+
+ private def eagerlyExecuteCommands(p: LogicalPlan) = p transformDown {
+ case c: Command =>
+ val qe = sparkSession.sessionState.executePlan(c, true)
+ CommandResult(
+ qe.analyzed.output,
+ qe.commandExecuted,
+ qe.executedPlan,
+ SQLExecution.withNewExecutionId(qe,
name)(qe.executedPlan.executeCollect()))
+ case other => other
+ }
+
lazy val withCachedData: LogicalPlan = sparkSession.withActive {
assertAnalyzed()
assertSupported()
// clone the plan to avoid sharing the plan instance between different
stages like analyzing,
// optimizing and planning.
- sparkSession.sharedState.cacheManager.useCachedData(analyzed.clone())
+
sparkSession.sharedState.cacheManager.useCachedData(commandExecuted.clone())
}
lazy val optimizedPlan: LogicalPlan =
executePhase(QueryPlanningTracker.OPTIMIZATION) {
Review comment:
OK
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