Apache spark Spark sql在纱线集群模式下抛出java.lang.OutOfMemoryError，但在纱线客户机模式下工作

我有一个简单的配置单元查询，它在使用pyspark shell的纱线客户机模式下运行良好，当我在纱线集群模式下运行它时，它会抛出以下错误

Exception in thread "Thread-6" 
Exception: java.lang.OutOfMemoryError thrown from the UncaughtExceptionHandler in thread "Thread-6"
Exception in thread "Reporter" 
Exception: java.lang.OutOfMemoryError thrown from the UncaughtExceptionHandler in thread "Reporter" 
Exception: java.lang.OutOfMemoryError thrown from the UncaughtExceptionHandler in thread "sparkDriver-scheduler-1"

集群信息：hadoop2.4、Spark 1.4.0-hadoop2.4、Hive0.13.1 该脚本从配置单元表中获取10列，进行一些转换并将其写入文件

> num-executors 200 executor-memory 8G driver-memory 16G executor-cores 3

完整堆栈跟踪：

py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o62.javaToPython.
: java.lang.OutOfMemoryError: PermGen space at java.lang.ClassLoader.defineClass1(Native Method)
    at java.lang.ClassLoader.defineClass(ClassLoader.java:800)
    at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
    at java.net.URLClassLoader.defineClass(URLClassLoader.java:449)
    at java.net.URLClassLoader.access$100(URLClassLoader.java:71)
    at java.net.URLClassLoader$1.run(URLClassLoader.java:361)
    at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
    at java.security.AccessController.doPrivileged(Native Method)
    at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
    at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
    at java.lang.Class.getDeclaredMethods0(Native Method)
    at java.lang.Class.privateGetDeclaredMethods(Class.java:2570)
    at java.lang.Class.getDeclaredMethods(Class.java:1855)
    at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:206)
    at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:132)
    at org.apache.spark.SparkContext.clean(SparkContext.scala:1891)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:683)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:682)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
    at org.apache.spark.rdd.RDD.mapPartitions(RDD.scala:682)
    at org.apache.spark.api.python.SerDeUtil$.javaToPython(SerDeUtil.scala:140)
    at org.apache.spark.sql.DataFrame.javaToPython(DataFrame.scala:1435)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)

java.lang.OutOfMemoryError:java.lang.ClassLoader.defineClass1（

驱动程序JVM中的“永久生成”堆空间可能已用完。此区域用于存储类。当我们在群集模式下运行时，JVM需要加载更多类（我认为这是因为应用程序管理器与驱动程序在同一JVM中运行）。要增加永久生成区域，请添加以下选项：

--driver-java-options -XX:MaxPermSize=256M

另见

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在Python程序中使用HiveContext时，我发现还需要以下选项：

--files /usr/hdp/current/spark-client/conf/hive-site.xml

另见

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我还想指定要使用的Python的特定版本，这需要另一个选项：

--conf spark.yarn.appMasterEnv.PYSPARK_PYTHON=/usr/local/bin/python2.7

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另请参见

对Mark的答案稍加补充-有时Spark with HiveContext会抱怨OutOfMemoryError，但未提及PermGen，但是仅-XX:MaxPermSize有帮助

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因此，如果您在使用Spark+HiveContext时处理OOM，也可以尝试-XX:MaxPermSize

一些有关群集/本地配置以及脚本中的内容的信息。将群集信息添加到问题中我面临相同的问题。您是如何解决的？