火花壳抛出异常

时间：2019-01-26 19:48:01

标签： python-3.x scala apache-spark

尝试运行spark-shell时出错。 Pyspark运行完美。不知道是什么问题。

尝试更改〜/ .bash_profile中的路径。没事。 尝试卸载并再次安装软件包。

我已经列出了以下终端上显示的消息。 Spark和Scala的新手。因此，需要一些帮助来建立系统。有人可以看一下代码，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'

1 个答案:

答案 0 :(得分：0)

The java classpath is not correctly set. Luckily the error message explains exactly how to fix it.

** 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.

Just adding the -usejavacp parameter when stating spark-shell is the simplest fix. So you would run it as spark-shell -usejavacp.

It also looks like you are using a version of Java newer than Java 8, which is not supported. The warnings about illegal reflective access are signs of this. You may need to install Java8 as well and use that when running spark-shell.

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