[ https://issues.apache.org/jira/browse/SPARK-40367?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
jacky updated SPARK-40367: -------------------------- Description: I use this code:spark.sql("xx").selectExpr(spark.table(target).columns:_*).write.mode("overwrite").insertInto(target),I get an error Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Total size of serialized results of 3730 tasks (64.0 GB) is bigger than spark.driver.maxResultSize (64.0 GB) at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1609) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1597) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1596) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1596) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1830) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1779) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1768) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099) at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) at org.apache.spark.rdd.RDD.collect(RDD.scala:938) at org.apache.spark.sql.execution.SparkPlan.executeCollectIterator(SparkPlan.scala:304) at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:76) at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:73) at org.apache.spark.sql.execution.SQLExecution$.withExecutionId(SQLExecution.scala:97) at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:72) at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:72) at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24) at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) --conf spark.driver.maxResultSize=64g --{-}conf spark.sql.broadcastTimeout=36000{-} {-}-{-}-conf spark.sql.autoBroadcastJoinThreshold=204857600 --conf spark.memory.offHeap.enabled=true --conf spark.memory.offHeap.size=4g --num-executors 500 --executor-memory 16g --executor-cores 2 --driver-memory 80G --conf spark.sql.shuffle.partitions=4000 --conf spark.sql.adaptive.enabled=true When I increase the spark.driver.maxResultSize,it also does not work was: I use this code:spark.sql("xx").selectExpr(spark.table(target).columns:_*).write.mode("overwrite").insertInto(target),I get an error Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Total size of serialized results of 3730 tasks (64.0 GB) is bigger than spark.driver.maxResultSize (64.0 GB) at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1609) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1597) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1596) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1596) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1830) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1779) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1768) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099) at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) at org.apache.spark.rdd.RDD.collect(RDD.scala:938) at org.apache.spark.sql.execution.SparkPlan.executeCollectIterator(SparkPlan.scala:304) at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:76) at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:73) at org.apache.spark.sql.execution.SQLExecution$.withExecutionId(SQLExecution.scala:97) at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:72) at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:72) at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24) at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) -{-}conf spark.driver.maxResultSize=64g --conf spark.sql.broadcastTimeout=36000 -{-} -conf spark.sql.autoBroadcastJoinThreshold=204857600 --conf spark.memory.offHeap.enabled=true --conf spark.memory.offHeap.size=4g --num-executors 500 --executor-memory 16g --executor-cores 2 --driver-memory 80G --conf spark.sql.shuffle.partitions=4000 --conf spark.sql.adaptive.enabled=true When I increase the spark.driver.maxResultSize,it also does not work > Total size of serialized results of 3730 tasks (64.0 GB) is bigger than > spark.driver.maxResultSize (64.0 GB) > ------------------------------------------------------------------------------------------------------------- > > Key: SPARK-40367 > URL: https://issues.apache.org/jira/browse/SPARK-40367 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.3.2 > Reporter: jacky > Priority: Blocker > > I use this > code:spark.sql("xx").selectExpr(spark.table(target).columns:_*).write.mode("overwrite").insertInto(target),I > get an error > > Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: > Total size of serialized results of 3730 tasks (64.0 GB) is bigger than > spark.driver.maxResultSize (64.0 GB) > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1609) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1597) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1596) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1596) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) > at scala.Option.foreach(Option.scala:257) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1830) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1779) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1768) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099) > at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) > at org.apache.spark.rdd.RDD.collect(RDD.scala:938) > at > org.apache.spark.sql.execution.SparkPlan.executeCollectIterator(SparkPlan.scala:304) > at > org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:76) > at > org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:73) > at > org.apache.spark.sql.execution.SQLExecution$.withExecutionId(SQLExecution.scala:97) > at > org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:72) > at > org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:72) > at > scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24) > at > scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > > --conf spark.driver.maxResultSize=64g > --{-}conf spark.sql.broadcastTimeout=36000{-} > {-}-{-}-conf spark.sql.autoBroadcastJoinThreshold=204857600 > --conf spark.memory.offHeap.enabled=true > --conf spark.memory.offHeap.size=4g > --num-executors 500 > --executor-memory 16g > --executor-cores 2 --driver-memory 80G > --conf spark.sql.shuffle.partitions=4000 > --conf spark.sql.adaptive.enabled=true > > When I increase the spark.driver.maxResultSize,it also does not work -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org