[
https://issues.apache.org/jira/browse/SPARK-48155?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
angerszhu updated SPARK-48155:
------------------------------
Description:
{code:java}
24/05/07 09:48:55 ERROR [main] PlanChangeLogger:
=== Applying Rule
org.apache.spark.sql.execution.adaptive.AQEPropagateEmptyRelation ===
Project [date#124, station_name#0, shipment_id#14]
+- Filter (status#2L INSET 1, 149, 2, 36, 400, 417, 418, 419, 49, 5, 50, 581
AND station_type#1 IN (3,12))
+- Aggregate [date#124, shipment_id#14], [date#124, shipment_id#14, ... 3
more fields]
! +- Join LeftOuter, ((cast(date#124 as timestamp) >=
cast(from_unixtime((ctime#27L - 0), yyyy-MM-dd HH:mm:ss, Some(Asia/Singapore))
as timestamp)) AND (cast(date#124 as timestamp) + INTERVAL '-4' DAY <=
cast(from_unixtime((ctime#27L - 0), yyyy-MM-dd HH:mm:ss, Some(Asia/Singapore))
as timestamp)))
! :- LogicalQueryStage Generate
explode(org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@3a191e40),
false, [date#124], BroadcastQueryStage 0
! +- LocalRelation <empty>, [shipment_id#14, station_name#5, ... 3 more
fields]24/05/07 09:48:55 ERROR [main]
Project [date#124, station_name#0, shipment_id#14]
+- Filter (status#2L INSET 1, 149, 2, 36, 400, 417, 418, 419, 49, 5, 50, 581
AND station_type#1 IN (3,12))
+- Aggregate [date#124, shipment_id#14], [date#124, shipment_id#14, ... 3
more fields]
! +- Project [date#124, cast(null as string) AS shipment_id#14, ... 4 more
fields]
! +- LogicalQueryStage Generate
explode(org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@3a191e40),
false, [date#124], BroadcastQueryStage 0 {code}
{code:java}
java.util.concurrent.ExecutionException: java.lang.RuntimeException:
java.lang.UnsupportedOperationException: BroadcastExchange does not support the
execute() code path. at
org.apache.spark.sql.errors.QueryExecutionErrors$.executeCodePathUnsupportedError(QueryExecutionErrors.scala:1652)
at
org.apache.spark.sql.execution.exchange.BroadcastExchangeExec.doExecute(BroadcastExchangeExec.scala:203)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
at
org.apache.spark.sql.execution.adaptive.QueryStageExec.doExecute(QueryStageExec.scala:119)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
at
org.apache.spark.sql.execution.InputAdapter.inputRDD(WholeStageCodegenExec.scala:526)
at
org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs(WholeStageCodegenExec.scala:454)
at
org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs$(WholeStageCodegenExec.scala:453)
at
org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:497)
at
org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:50)
at org.apache.spark.sql.execution.SortExec.inputRDDs(SortExec.scala:132)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:750)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
at
org.apache.spark.sql.execution.aggregate.SortAggregateExec.doExecute(SortAggregateExec.scala:55)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.inputRDD$lzycompute(ShuffleExchangeExec.scala:144)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.inputRDD(ShuffleExchangeExec.scala:144)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.mapOutputStatisticsFuture$lzycompute(ShuffleExchangeExec.scala:149)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.mapOutputStatisticsFuture(ShuffleExchangeExec.scala:148)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeLike.$anonfun$submitShuffleJob$1(ShuffleExchangeExec.scala:70)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeLike.submitShuffleJob(ShuffleExchangeExec.scala:70)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeLike.submitShuffleJob$(ShuffleExchangeExec.scala:69)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.submitShuffleJob(ShuffleExchangeExec.scala:117)
at
org.apache.spark.sql.execution.adaptive.ShuffleQueryStageExec.shuffleFuture$lzycompute(QueryStageExec.scala:170)
at
org.apache.spark.sql.execution.adaptive.ShuffleQueryStageExec.shuffleFuture(QueryStageExec.scala:170)
at
org.apache.spark.sql.execution.adaptive.ShuffleQueryStageExec.doMaterialize(QueryStageExec.scala:172)
at
org.apache.spark.sql.execution.adaptive.QueryStageExec.materialize(QueryStageExec.scala:82)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$5(AdaptiveSparkPlanExec.scala:257)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$5$adapted(AdaptiveSparkPlanExec.scala:255)
at scala.collection.Iterator.foreach(Iterator.scala:943) at
scala.collection.Iterator.foreach$(Iterator.scala:943) at
scala.collection.AbstractIterator.foreach(Iterator.scala:1431) at
scala.collection.IterableLike.foreach(IterableLike.scala:74) at
scala.collection.IterableLike.foreach$(IterableLike.scala:73) at
scala.collection.AbstractIterable.foreach(Iterable.scala:56) at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$1(AdaptiveSparkPlanExec.scala:255)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:782)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.getFinalPhysicalPlan(AdaptiveSparkPlanExec.scala:227)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.withFinalPlanUpdate(AdaptiveSparkPlanExec.scala:366)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.executeCollect(AdaptiveSparkPlanExec.scala:339)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715) at
org.apache.spark.sql.Dataset.$anonfun$collectAsList$1(Dataset.scala:2983) at
org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706) at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:104)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:170)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:91)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:782)
{code}
was:
{code:java}
24/05/07 09:48:55 ERROR [main] PlanChangeLogger:
=== Applying Rule
org.apache.spark.sql.execution.adaptive.AQEPropagateEmptyRelation ===
Project [date#124, station_name#0, shipment_id#14]
+- Filter (status#2L INSET 1, 149, 2, 36, 400, 417, 418, 419, 49, 5, 50, 581
AND station_type#1 IN (3,12))
+- Aggregate [date#124, shipment_id#14], [date#124, shipment_id#14, ... 3
more fields]
! +- Join LeftOuter, ((cast(date#124 as timestamp) >=
cast(from_unixtime((ctime#27L - 0), yyyy-MM-dd HH:mm:ss, Some(Asia/Singapore))
as timestamp)) AND (cast(date#124 as timestamp) + INTERVAL '-4' DAY <=
cast(from_unixtime((ctime#27L - 0), yyyy-MM-dd HH:mm:ss, Some(Asia/Singapore))
as timestamp)))
! :- LogicalQueryStage Generate
explode(org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@3a191e40),
false, [date#124], BroadcastQueryStage 0
! +- LocalRelation <empty>, [shipment_id#14, station_name#5, ... 3 more
fields]24/05/07 09:48:55 ERROR [main] PlanChangeLogger:
=== Applying Rule
org.apache.spark.sql.execution.adaptive.AQEPropagateEmptyRelation ===
Project [date#124, station_name#0, shipment_id#14]
+- Filter (status#2L INSET 1, 149, 2, 36, 400, 417, 418, 419, 49, 5, 50, 581
AND station_type#1 IN (3,12))
+- Aggregate [date#124, shipment_id#14], [date#124, shipment_id#14, ... 3
more fields]
! +- Project [date#124, cast(null as string) AS shipment_id#14, ... 4 more
fields]
! +- LogicalQueryStage Generate
explode(org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@3a191e40),
false, [date#124], BroadcastQueryStage 0 {code}
{code:java}
java.util.concurrent.ExecutionException: java.lang.RuntimeException:
java.lang.UnsupportedOperationException: BroadcastExchange does not support the
execute() code path. at
org.apache.spark.sql.errors.QueryExecutionErrors$.executeCodePathUnsupportedError(QueryExecutionErrors.scala:1652)
at
org.apache.spark.sql.execution.exchange.BroadcastExchangeExec.doExecute(BroadcastExchangeExec.scala:203)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
at
org.apache.spark.sql.execution.adaptive.QueryStageExec.doExecute(QueryStageExec.scala:119)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
at
org.apache.spark.sql.execution.InputAdapter.inputRDD(WholeStageCodegenExec.scala:526)
at
org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs(WholeStageCodegenExec.scala:454)
at
org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs$(WholeStageCodegenExec.scala:453)
at
org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:497)
at
org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:50)
at org.apache.spark.sql.execution.SortExec.inputRDDs(SortExec.scala:132)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:750)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
at
org.apache.spark.sql.execution.aggregate.SortAggregateExec.doExecute(SortAggregateExec.scala:55)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.inputRDD$lzycompute(ShuffleExchangeExec.scala:144)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.inputRDD(ShuffleExchangeExec.scala:144)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.mapOutputStatisticsFuture$lzycompute(ShuffleExchangeExec.scala:149)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.mapOutputStatisticsFuture(ShuffleExchangeExec.scala:148)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeLike.$anonfun$submitShuffleJob$1(ShuffleExchangeExec.scala:70)
at
org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeLike.submitShuffleJob(ShuffleExchangeExec.scala:70)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeLike.submitShuffleJob$(ShuffleExchangeExec.scala:69)
at
org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.submitShuffleJob(ShuffleExchangeExec.scala:117)
at
org.apache.spark.sql.execution.adaptive.ShuffleQueryStageExec.shuffleFuture$lzycompute(QueryStageExec.scala:170)
at
org.apache.spark.sql.execution.adaptive.ShuffleQueryStageExec.shuffleFuture(QueryStageExec.scala:170)
at
org.apache.spark.sql.execution.adaptive.ShuffleQueryStageExec.doMaterialize(QueryStageExec.scala:172)
at
org.apache.spark.sql.execution.adaptive.QueryStageExec.materialize(QueryStageExec.scala:82)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$5(AdaptiveSparkPlanExec.scala:257)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$5$adapted(AdaptiveSparkPlanExec.scala:255)
at scala.collection.Iterator.foreach(Iterator.scala:943) at
scala.collection.Iterator.foreach$(Iterator.scala:943) at
scala.collection.AbstractIterator.foreach(Iterator.scala:1431) at
scala.collection.IterableLike.foreach(IterableLike.scala:74) at
scala.collection.IterableLike.foreach$(IterableLike.scala:73) at
scala.collection.AbstractIterable.foreach(Iterable.scala:56) at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$1(AdaptiveSparkPlanExec.scala:255)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:782)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.getFinalPhysicalPlan(AdaptiveSparkPlanExec.scala:227)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.withFinalPlanUpdate(AdaptiveSparkPlanExec.scala:366)
at
org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.executeCollect(AdaptiveSparkPlanExec.scala:339)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715) at
org.apache.spark.sql.Dataset.$anonfun$collectAsList$1(Dataset.scala:2983) at
org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706) at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:104)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:170)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:91)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:782)
{code}
> PropagateEmpty relation cause LogicalQueryStage only with broadcast without
> join then execute failed
> ----------------------------------------------------------------------------------------------------
>
> Key: SPARK-48155
> URL: https://issues.apache.org/jira/browse/SPARK-48155
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.2.1, 3.5.1, 3.3.4
> Reporter: angerszhu
> Priority: Major
>
> {code:java}
> 24/05/07 09:48:55 ERROR [main] PlanChangeLogger:
> === Applying Rule
> org.apache.spark.sql.execution.adaptive.AQEPropagateEmptyRelation ===
> Project [date#124, station_name#0, shipment_id#14]
> +- Filter (status#2L INSET 1, 149, 2, 36, 400, 417, 418, 419, 49, 5, 50, 581
> AND station_type#1 IN (3,12))
> +- Aggregate [date#124, shipment_id#14], [date#124, shipment_id#14, ... 3
> more fields]
> ! +- Join LeftOuter, ((cast(date#124 as timestamp) >=
> cast(from_unixtime((ctime#27L - 0), yyyy-MM-dd HH:mm:ss,
> Some(Asia/Singapore)) as timestamp)) AND (cast(date#124 as timestamp) +
> INTERVAL '-4' DAY <= cast(from_unixtime((ctime#27L - 0), yyyy-MM-dd HH:mm:ss,
> Some(Asia/Singapore)) as timestamp)))
> ! :- LogicalQueryStage Generate
> explode(org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@3a191e40),
> false, [date#124], BroadcastQueryStage 0
> ! +- LocalRelation <empty>, [shipment_id#14, station_name#5, ... 3
> more fields]24/05/07 09:48:55 ERROR [main]
> Project [date#124, station_name#0, shipment_id#14]
> +- Filter (status#2L INSET 1, 149, 2, 36, 400, 417, 418, 419, 49, 5, 50, 581
> AND station_type#1 IN (3,12))
> +- Aggregate [date#124, shipment_id#14], [date#124, shipment_id#14, ... 3
> more fields]
> ! +- Project [date#124, cast(null as string) AS shipment_id#14, ... 4
> more fields]
> ! +- LogicalQueryStage Generate
> explode(org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@3a191e40),
> false, [date#124], BroadcastQueryStage 0 {code}
> {code:java}
> java.util.concurrent.ExecutionException: java.lang.RuntimeException:
> java.lang.UnsupportedOperationException: BroadcastExchange does not support
> the execute() code path. at
> org.apache.spark.sql.errors.QueryExecutionErrors$.executeCodePathUnsupportedError(QueryExecutionErrors.scala:1652)
> at
> org.apache.spark.sql.execution.exchange.BroadcastExchangeExec.doExecute(BroadcastExchangeExec.scala:203)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
> at
> org.apache.spark.sql.execution.adaptive.QueryStageExec.doExecute(QueryStageExec.scala:119)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDD(WholeStageCodegenExec.scala:526)
> at
> org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs(WholeStageCodegenExec.scala:454)
> at
> org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs$(WholeStageCodegenExec.scala:453)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:497)
> at
> org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:50)
> at org.apache.spark.sql.execution.SortExec.inputRDDs(SortExec.scala:132)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:750)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
> at
> org.apache.spark.sql.execution.aggregate.SortAggregateExec.doExecute(SortAggregateExec.scala:55)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:184)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:180)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.inputRDD$lzycompute(ShuffleExchangeExec.scala:144)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.inputRDD(ShuffleExchangeExec.scala:144)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.mapOutputStatisticsFuture$lzycompute(ShuffleExchangeExec.scala:149)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.mapOutputStatisticsFuture(ShuffleExchangeExec.scala:148)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeLike.$anonfun$submitShuffleJob$1(ShuffleExchangeExec.scala:70)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:222)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:219)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeLike.submitShuffleJob(ShuffleExchangeExec.scala:70)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeLike.submitShuffleJob$(ShuffleExchangeExec.scala:69)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.submitShuffleJob(ShuffleExchangeExec.scala:117)
> at
> org.apache.spark.sql.execution.adaptive.ShuffleQueryStageExec.shuffleFuture$lzycompute(QueryStageExec.scala:170)
> at
> org.apache.spark.sql.execution.adaptive.ShuffleQueryStageExec.shuffleFuture(QueryStageExec.scala:170)
> at
> org.apache.spark.sql.execution.adaptive.ShuffleQueryStageExec.doMaterialize(QueryStageExec.scala:172)
> at
> org.apache.spark.sql.execution.adaptive.QueryStageExec.materialize(QueryStageExec.scala:82)
> at
> org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$5(AdaptiveSparkPlanExec.scala:257)
> at
> org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$5$adapted(AdaptiveSparkPlanExec.scala:255)
> at scala.collection.Iterator.foreach(Iterator.scala:943) at
> scala.collection.Iterator.foreach$(Iterator.scala:943) at
> scala.collection.AbstractIterator.foreach(Iterator.scala:1431) at
> scala.collection.IterableLike.foreach(IterableLike.scala:74) at
> scala.collection.IterableLike.foreach$(IterableLike.scala:73) at
> scala.collection.AbstractIterable.foreach(Iterable.scala:56) at
> org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$1(AdaptiveSparkPlanExec.scala:255)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:782)
> at
> org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.getFinalPhysicalPlan(AdaptiveSparkPlanExec.scala:227)
> at
> org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.withFinalPlanUpdate(AdaptiveSparkPlanExec.scala:366)
> at
> org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.executeCollect(AdaptiveSparkPlanExec.scala:339)
> at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715) at
> org.apache.spark.sql.Dataset.$anonfun$collectAsList$1(Dataset.scala:2983)
> at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:104)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:170)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:91)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:782)
> {code}
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