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python-3.x - spark-shell 抛出异常

问题描述

尝试运行 spark-shell 时出错。Pyspark 运行完美。不确定是什么问题。

尝试更改 ~/.bash_profile 中的路径。没有任何效果。尝试卸载并再次安装软件包。

我列出了下面终端上显示的消息。Spark 和 Scala 的新手。因此，在设置系统时需要一些帮助。有人可以查看代码并让我知道出了什么问题。

MacBook-Pro:spark zoo$ bin/spark-shell
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.hadoop.security.authentication.util.KerberosUtil (file:/usr/local/spark/jars/hadoop-auth-2.7.3.jar) to method sun.security.krb5.Config.getInstance()
WARNING: Please consider reporting this to the maintainers of org.apache.hadoop.security.authentication.util.KerberosUtil
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
2019-01-26 11:32:29 WARN  NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).

Failed to initialize compiler: object java.lang.Object in compiler mirror not found.
** Note that as of 2.8 scala does not assume use of the java classpath.
** For the old behavior pass -usejavacp to scala, or if using a Settings
** object programmatically, settings.usejavacp.value = true.

Failed to initialize compiler: object java.lang.Object in compiler mirror not found.
** Note that as of 2.8 scala does not assume use of the java classpath.
** For the old behavior pass -usejavacp to scala, or if using a Settings
** object programmatically, settings.usejavacp.value = true.
Exception in thread "main" java.lang.NullPointerException
    at scala.reflect.internal.SymbolTable.exitingPhase(SymbolTable.scala:256)
    at scala.tools.nsc.interpreter.IMain$Request.x$20$lzycompute(IMain.scala:896)
    at scala.tools.nsc.interpreter.IMain$Request.x$20(IMain.scala:895)
    at scala.tools.nsc.interpreter.IMain$Request.headerPreamble$lzycompute(IMain.scala:895)
    at scala.tools.nsc.interpreter.IMain$Request.headerPreamble(IMain.scala:895)
    at scala.tools.nsc.interpreter.IMain$Request$Wrapper.preamble(IMain.scala:918)
    at scala.tools.nsc.interpreter.IMain$CodeAssembler$$anonfun$apply$23.apply(IMain.scala:1337)
    at scala.tools.nsc.interpreter.IMain$CodeAssembler$$anonfun$apply$23.apply(IMain.scala:1336)
    at scala.tools.nsc.util.package$.stringFromWriter(package.scala:64)
    at scala.tools.nsc.interpreter.IMain$CodeAssembler$class.apply(IMain.scala:1336)
    at scala.tools.nsc.interpreter.IMain$Request$Wrapper.apply(IMain.scala:908)
    at scala.tools.nsc.interpreter.IMain$Request.compile$lzycompute(IMain.scala:1002)
    at scala.tools.nsc.interpreter.IMain$Request.compile(IMain.scala:997)
    at scala.tools.nsc.interpreter.IMain.compile(IMain.scala:579)
    at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:567)
    at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565)
    at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:807)
    at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:681)
    at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:395)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$mcV$sp$2.apply(SparkILoop.scala:79)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$mcV$sp$2.apply(SparkILoop.scala:79)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SparkILoop.scala:79)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1.apply(SparkILoop.scala:79)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1.apply(SparkILoop.scala:79)
    at scala.tools.nsc.interpreter.ILoop.savingReplayStack(ILoop.scala:91)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply$mcV$sp(SparkILoop.scala:78)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:78)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:78)
    at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:214)
    at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:77)
    at org.apache.spark.repl.SparkILoop.loadFiles(SparkILoop.scala:110)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:920)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
    at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97)
    at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909)
    at org.apache.spark.repl.Main$.doMain(Main.scala:76)
    at org.apache.spark.repl.Main$.main(Main.scala:56)
    at org.apache.spark.repl.Main.main(Main.scala)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.base/java.lang.reflect.Method.invoke(Method.java:566)
    at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:894)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:198)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:228)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
# 
MacBook-Pro:spark zoo$ cat ~/.bash_profile

# Setting PATH for Python 3.7
# The original version is saved in .bash_profile.pysave
PATH="/Library/Frameworks/Python.framework/Versions/3.7/bin:${PATH}"
export PATH

export JAVA_HOME=/Library/Java/JavaVirtualMachines/jdk-11.0.2.jdk/Contents/Home
export PATH="$JAVA_HOME/bin:$PATH"

export SPARK_HOME=/usr/local/spark
export SBT_HOME=/usr/local/sbt
export SCALA_HOME=/usr/local/scala

export PATH="$PATH:$SCALA_HOME/bin"
export PYTHONPATH="$SPARK_HOME/python:$PYTHONPATH"
export PATH=$JAVA_HOME/bin:$SBT_HOME/bin:$SBT_HOME/lib:$SCALA_HOME/bin:$SCALA_HOME/lib:$PATH
export PATH=$JAVA_HOME/bin:$SPARK_HOME:$SPARK_HOME/bin:$SPARK_HOME/sbin:$PATH

export PYSPARK_PYTHON=python3
export PYSPARK_DRIVER_PYTHON=ipython
export PYSPARK_DRIVER_PYTHON_OPTS='notebook'

标签： python-3.xscalaapache-spark

解决方案

java 类路径设置不正确。幸运的是，错误消息准确地解释了如何修复它。

** 请注意，从 2.8 开始，scala 不假定使用 java 类路径。
** 对于旧行为，将 -usejavacp 传递给 scala，或者如果以
编程方式使用 Settings ** 对象，settings.usejavacp.value = true。

-usejavacp在声明 spark-shell 时添加参数是最简单的解决方法。所以你会运行它作为spark-shell -usejavacp.

看起来您使用的 Java 版本比 Java 8 更新，这是不受支持的。关于非法反射访问的警告就是这种情况的迹象。您可能还需要安装 Java8 并在运行 spark-shell 时使用它。

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