Question

我正在使用以下命令启动pyspark

./bin/pyspark --master yarn --deploy-mode client --executor-memory 5g

我收到以下错误

15/10/14 17:19:15 INFO spark.SparkContext: SparkContext already stopped.
Traceback (most recent call last):
  File "/opt/spark-1.5.1/python/pyspark/shell.py", line 43, in <module>
    sc = SparkContext(pyFiles=add_files)
  File "/opt/spark-1.5.1/python/pyspark/context.py", line 113, in __init__
    conf, jsc, profiler_cls)
  File "/opt/spark-1.5.1/python/pyspark/context.py", line 178, in _do_init
    self._jvm.PythonAccumulatorParam(host, port))
  File "/opt/spark-1.5.1/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 701, in __call__
  File "/opt/spark-1.5.1/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling None.org.apache.spark.api.python.PythonAccumulatorParam.
: java.lang.NullPointerException
        at org.apache.spark.api.python.PythonAccumulatorParam.<init>(PythonRDD.scala:825)
        at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
        at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
        at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
        at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
        at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:234)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
        at py4j.Gateway.invoke(Gateway.java:214)
        at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:79)
        at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:68)
        at py4j.GatewayConnection.run(GatewayConnection.java:207)
        at java.lang.Thread.run(Thread.java:745)

出于某种原因，我也收到了这条消息

 ERROR cluster.YarnClientSchedulerBackend: Yarn application has already exited with state FINISHED!

和

WARN remote.ReliableDeliverySupervisor: Association with remote system [akka.tcp://sparkYarnAM@192.168.1.112:48644] has failed, address is now gated for [5000] ms. Reason: [Disassociated]

这可能就是我SparkSetext停止的原因。

我使用Spark 1.5.1和Hadoop 2.7.1和Yarn 2.7。

有没有人知道为什么Yarn应用程序会在发生任何事情之前退出？

有关其他信息，请参阅我的yarn-site.xml

        <property>
                <name>yarn.nodemanager.resource.memory-mb</name>
                <value>26624</value>
        </property>
        <property>
                <name>yarn.scheduler.minimum-allocation-mb</name>
                <value>1024</value>
        </property>
        <property>
                <name>yarn.scheduler.maximum-allocation-mb</name>
                <value>26624</value>
        </property>
        <property>
                <name>yarn.nodemanager.vmem-pmem-ratio</name>
                <value>2.1</value>
        </property>

这是我的mapred-site.xml

    <property>
            <name>mapreduce.map.memory.mb</name>
            <value>2048</value>
    </property>
    <property>
            <name>mapreduce.map.java.opts</name>
            <value>-Xmx1640M</value>
            <description>Heap size for map jobs.</description>
    </property>
    <property>
            <name>mapreduce.reduce.memory.mb</name>
            <value>16384</value>
    </property>
    <property>
            <name>mapreduce.reduce.java.opts</name>
            <value>-Xmx13107M</value>
            <description>Heap size for reduce jobs.</description>
    </property>

Answer 1

我能够通过添加

来解决这个问题

spark.yarn.am.memory 5g

到spark-default.conf文件。

我认为这是一个与记忆相关的问题。

此参数的默认值为512米

Answer 2

我有一个类似的问题，当我查看端口8088上的Hadoop GUI并点击我的PySpark作业的ID列中的应用程序链接时，我看到以下错误：

未捕获的异常：org.apache ... InvalidResourceRequestException无效的资源请求，请求的虚拟核心＆lt; 0，或请求的虚拟核＆gt; max configured，requestedVirtualCores = 8，maxVirtualCores = 1

如果我将脚本更改为使用--executor-cores 1而不是默认值（--executor-cores 8），那么它就可以了。现在我只需让管理员更改一些Yarn设置以允许更多内核，例如yarn.scheduler.maximum-allocation-vcores，请参阅https://stackoverflow.com/a/29789568/215945

在我尝试启动PySpark时获取Null指针异常

2 个答案: