admin管理员组

文章数量:1608810

错误信息如下所示:

[hadoop@admin01 spark-2.1.1-bin-hadoop2.7]$ bin/spark-shell \
> --master spark://admin01:7077 \
> --executor-memory 2g \
> --total-executor-cores 2
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
18/12/01 19:38:06 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/12/01 19:39:06 ERROR SparkContext: Error initializing SparkContext.
java.io.FileNotFoundException: File does not exist: hdfs://admin01:8020/directory
	at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1309)
	at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1301)
	at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
	at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1317)
	at org.apache.spark.scheduler.EventLoggingListener.start(EventLoggingListener.scala:93)
	at org.apache.spark.SparkContext.<init>(SparkContext.scala:531)
	at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2320)
	at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:868)
	at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:860)
	at scala.Option.getOrElse(Option.scala:121)
	at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:860)
	at org.apache.spark.repl.Main$.createSparkSession(Main.scala:96)
	at $line3.$read$$iw$$iw.<init>(<console>:15)
	at $line3.$read$$iw.<init>(<console>:42)
	at $line3.$read.<init>(<console>:44)
	at $line3.$read$.<init>(<console>:48)
	at $line3.$read$.<clinit>(<console>)
	at $line3.$eval$.$print$lzycompute(<console>:7)
	at $line3.$eval$.$print(<console>:6)
	at $line3.$eval.$print(<console>)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:497)
	at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786)
	at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047)
	at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:638)
	at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:637)
	at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31)
	at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:19)
	at scala.tools.nsc.interpreter.IMain$WrappedRequest.loadAndRunReq(IMain.scala:637)
	at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:569)
	at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565)
	at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:807)
	at scala.tools.nsc.interpreter.ILoopmand(ILoop.scala:681)
	at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:395)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply$mcV$sp(SparkILoop.scala:38)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37)
	at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37)
	at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:214)
	at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:37)
	at org.apache.spark.repl.SparkILoop.loadFiles(SparkILoop.scala:105)
	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$$anonfun$process$1.apply(ILoop.scala:909)
	at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97)
	at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909)
	at org.apache.spark.repl.Main$.doMain(Main.scala:69)
	at org.apache.spark.repl.Main$.main(Main.scala:52)
	at org.apache.spark.repl.Main.main(Main.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:497)
	at org.apache.spark.deploy.SparkSubmit$$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:743)
	at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
	at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
java.io.FileNotFoundException: File does not exist: hdfs://admin01:8020/directory
  at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1309)
  at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1301)
  at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
  at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1317)
  at org.apache.spark.scheduler.EventLoggingListener.start(EventLoggingListener.scala:93)
  at org.apache.spark.SparkContext.<init>(SparkContext.scala:531)
  at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2320)
  at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:868)
  at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:860)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:860)
  at org.apache.spark.repl.Main$.createSparkSession(Main.scala:96)
  ... 47 elided

解决方案:

1、先telnet 192.168.1.88:7077是否能连通?
2、检查在master主机检查7077端口属于什么IP,eg.
如下的7077端口则属于127.0.0.1,需要将其修改成其他主机能访问的ip;

3.修改/etc/hosts文件即可,如下:
127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4 中去掉127.0.0.1与主机名的关联;如图所示:

相信很多人都很期待看待排除错误之后,运行的结果会是怎么样子的?接下来我们就来看一下运行的结果如下图所示:

本文标签: MasterSparkConnectioninformationrefused