spark.driver.maxResultSize限制 Spark 驱动程序（driver）在向客户端返回结果时的最大大小

冷不防 2024-03-02 09:40 28阅读 0赞

![在这里插入图片描述][1e4a310eb0ba4d2396dc997c7b76e8dc.jpeg]

org.apache.kyuubi.KyuubiSQLException: org.apache.kyuubi.KyuubiSQLException: Error operating ExecuteStatement: org.apache.spark.SparkException: Job aborted due to stage failure: Total size of serialized results of 3 tasks (1290.4 MiB) is bigger than spark.driver.maxResultSize (1024.0 MiB) at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2454) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2403) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2402) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2402) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1160) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1160) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1160) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2642) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2584) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2573) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2235) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2254) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2279) at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1030) 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:414) at org.apache.spark.rdd.RDD.collect(RDD.scala:1029) at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:410) at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715) at org.apache.spark.sql.Dataset.$anonfun$collect$1(Dataset.scala:2971) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3704) at org.apache.spark.sql.Dataset.collect(Dataset.scala:2971) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement.fullCollectResult(ExecuteStatement.scala:70) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement.collectAsIterator(ExecuteStatement.scala:161) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement.$anonfun$executeStatement$1(ExecuteStatement.scala:84) at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23) at org.apache.kyuubi.engine.spark.operation.SparkOperation.$anonfun$withLocalProperties$1(SparkOperation.scala:155) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) at org.apache.kyuubi.engine.spark.operation.SparkOperation.withLocalProperties(SparkOperation.scala:139) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement.executeStatement(ExecuteStatement.scala:78) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement$$anon$1.run(ExecuteStatement.scala:100) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) at org.apache.kyuubi.KyuubiSQLException$.apply(KyuubiSQLException.scala:69) at org.apache.kyuubi.engine.spark.operation.SparkOperation$$anonfun$onError$1.$anonfun$applyOrElse$1(SparkOperation.scala:189) at org.apache.kyuubi.Utils$.withLockRequired(Utils.scala:395) at org.apache.kyuubi.operation.AbstractOperation.withLockRequired(AbstractOperation.scala:51) at org.apache.kyuubi.engine.spark.operation.SparkOperation$$anonfun$onError$1.applyOrElse(SparkOperation.scala:177) at org.apache.kyuubi.engine.spark.operation.SparkOperation$$anonfun$onError$1.applyOrElse(SparkOperation.scala:172) at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement.$anonfun$executeStatement$1(ExecuteStatement.scala:88) at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23) at org.apache.kyuubi.engine.spark.operation.SparkOperation.$anonfun$withLocalProperties$1(SparkOperation.scala:155) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) at org.apache.kyuubi.engine.spark.operation.SparkOperation.withLocalProperties(SparkOperation.scala:139) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement.executeStatement(ExecuteStatement.scala:78) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement$$anon$1.run(ExecuteStatement.scala:100) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Total size of serialized results of 3 tasks (1290.4 MiB) is bigger than spark.driver.maxResultSize (1024.0 MiB) at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2454) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2403) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2402) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2402) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1160) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1160) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1160) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2642) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2584) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2573) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2235) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2254) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2279) at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1030) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:414) at org.apache.spark.rdd.RDD.collect(RDD.scala:1029) at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:410) at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715) at org.apache.spark.sql.Dataset.$anonfun$collect$1(Dataset.scala:2971) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3704) at org.apache.spark.sql.Dataset.collect(Dataset.scala:2971) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement.fullCollectResult(ExecuteStatement.scala:70) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement.collectAsIterator(ExecuteStatement.scala:161) at org.apache.kyuubi.engine.spark.operation.ExecuteStatement.$anonfun$executeStatement$1(ExecuteStatement.scala:84) ... 11 more at org.apache.kyuubi.KyuubiSQLException$.apply(KyuubiSQLException.scala:69) at org.apache.kyuubi.operation.ExecuteStatement.waitStatementComplete(ExecuteStatement.scala:129) at org.apache.kyuubi.operation.ExecuteStatement.$anonfun$runInternal$1(ExecuteStatement.scala:161) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)

### spark.driver.maxResultSize ###

Limit of total size of serialized results of all partitions for each Spark action (e.g. collect). Should be at least 1M, or 0 for unlimited. Jobs will be aborted if the total size is above this limit. Having a high limit may cause out-of-memory errors in driver (depends on spark.driver.memory and memory overhead of objects in JVM). Setting a proper limit can protect the driver from out-of-memory errors.

每个Spark　action的所有分区的序列化结果的总大小限制（例如，collect行动算子）。 应该至少为1M，或者为无限制。 如果超过1g，job将被中止。 如果driver.maxResultSize设置过大可能会超出内存（取决于spark.driver.memory和JVM中对象的内存开销）。 设置适当的参数限制可以防止内存不足。

默认值:1024M  
设置为0则为无限制，但是有OOM的风险

**您可以通过以下方式修改 spark.driver.maxResultSize 的值：**

在 Spark 配置文件（如 spark-defaults.conf）中添加以下行：

spark.driver.maxResultSize 2g

这会将最大结果大小设置为 2GB。

或者，在启动 Spark 作业时，可以通过命令行参数来覆盖该属性的值，例如：

spark-submit --conf spark.driver.maxResultSize=2g ...

saprk-sql --conf spark.driver.maxResultSize=2g

[1e4a310eb0ba4d2396dc997c7b76e8dc.jpeg]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/02/1e025ab5e31847e19ce1ea3cf04f41cd.png