python Spark安装问题，java异常
当我尝试在安装后立即运行pyspark、sparkshell和任何其他spark命令时，它会抛出此异常
请建议一种解决方法，它一直悬而未决，我也尝试过通过Brew安装spark，但没有成功
log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.lib.MutableMetricsFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.hadoop.security.authentication.util.KerberosUtil (file:/opt/spark/lib/spark-assembly-1.6.3-hadoop2.6.0.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
Exception in thread "main" java.lang.ExceptionInInitializerError
at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:79)
at org.apache.hadoop.security.Groups.parseStaticMapping(Groups.java:104)
at org.apache.hadoop.security.Groups.<init>(Groups.java:86)
at org.apache.hadoop.security.Groups.<init>(Groups.java:66)
at org.apache.hadoop.security.Groups.getUserToGroupsMappingService(Groups.java:280)
at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:271)
at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:248)
at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:763)
at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:748)
at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:621)
at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2214)
at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2214)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2214)
at org.apache.spark.SecurityManager.<init>(SecurityManager.scala:214)
at org.apache.spark.repl.SparkIMain.<init>(SparkIMain.scala:118)
at org.apache.spark.repl.SparkILoop$SparkILoopInterpreter.<init>(SparkILoop.scala:187)
at org.apache.spark.repl.SparkILoop.createInterpreter(SparkILoop.scala:217)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:949)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.StringIndexOutOfBoundsException: begin 0, end 3, length 2
at java.base/java.lang.String.checkBoundsBeginEnd(String.java:3319)
at java.base/java.lang.String.substring(String.java:1874)
at org.apache.hadoop.util.Shell.<clinit>(Shell.java:49)
... 35 more
Using Spark's repl log4j profile: org/apache/spark/log4j-defaults-repl.properties
To adjust logging level use sc.setLogLevel("INFO")## Heading ##
# 1 楼答案
您可能需要安装Java8版本，最好是8u-151版本https://www.oracle.com/technetwork/java/javase/downloads/java-archive-javase8-2177648.html
此外，您还必须设置HOME和PATH