java - PySpark 吞下 JVM “OOM heapspace”异常

Question

问题

我有一个 PySpark 作业，偶尔会以java.lang.OutOfMemoryError: Java heap space. 我的脚本中止，但退出代码报告为成功。此错误未包含在任何 Python 异常中，因此我不知道如何捕获它并重新引发它，因此我的脚本不会报告成功。

这是我公司的核心脚本之一。不幸的是，代码是垃圾，因此很难在不影响生产的情况下对其进行测试。

我制作了一个示例脚本来复制此错误，但生成的 Java 异常包含在 Python 错误Py4JJavaError中，因此这不会复制我的问题。

问题

• 是否可以从 Python 中捕获 JVM 异常？
• 或者至少冒泡这个异常，所以我的脚本失败了？

这是一个例外：

ERROR:weekly_update:An error occurred while calling o2980.count.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 68 in stage 648.0 failed 1 times, most recent failure: Lost task 68.0 in stage 648.0 (TID 32330, dagobah, executor driver): java.lang.OutOfMemoryError: Java heap space

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2059)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2008)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2007)
    at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
    at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2007)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:973)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:973)
    at scala.Option.foreach(Option.scala:407)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:973)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2239)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2188)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2177)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2120)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2139)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2164)
    at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:388)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
    at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:385)
    at org.apache.spark.sql.Dataset.$anonfun$count$1(Dataset.scala:2981)
    at org.apache.spark.sql.Dataset.$anonfun$count$1$adapted(Dataset.scala:2980)
    at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3618)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
    at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3616)
    at org.apache.spark.sql.Dataset.count(Dataset.scala:2980)
    at jdk.internal.reflect.GeneratedMethodAccessor288.invoke(Unknown Source)
    at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.base/java.lang.reflect.Method.invoke(Method.java:566)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:238)
    at java.base/java.lang.Thread.run(Thread.java:834)
Caused by: java.lang.OutOfMemoryError: Java heap space

标签： javapythonapache-sparkpyspark