【发布时间】：2019-12-07 15:11:39
【问题描述】：
已成功启动 aws EMR 集群，但任何提交都失败了：
19/07/30 08:37:42 ERROR UserData: Error encountered while try to get user data
java.io.IOException: File '/var/aws/emr/userData.json' cannot be read
at com.amazon.ws.emr.hadoop.fs.shaded.org.apache.commons.io.FileUtils.openInputStream(FileUtils.java:296)
at com.amazon.ws.emr.hadoop.fs.shaded.org.apache.commons.io.FileUtils.readFileToString(FileUtils.java:1711)
at com.amazon.ws.emr.hadoop.fs.shaded.org.apache.commons.io.FileUtils.readFileToString(FileUtils.java:1748)
at com.amazon.ws.emr.hadoop.fs.util.UserData.getUserData(UserData.java:62)
at com.amazon.ws.emr.hadoop.fs.util.UserData.<init>(UserData.java:39)
at com.amazon.ws.emr.hadoop.fs.util.UserData.ofDefaultResourceLocations(UserData.java:52)
at com.amazon.ws.emr.hadoop.fs.util.AWSSessionCredentialsProviderFactory.buildSTSClient(AWSSessionCredentialsProviderFactory.java:52)
at com.amazon.ws.emr.hadoop.fs.util.AWSSessionCredentialsProviderFactory.<clinit>(AWSSessionCredentialsProviderFactory.java:17)
at com.amazon.ws.emr.hadoop.fs.rolemapping.DefaultS3CredentialsResolver.resolve(DefaultS3CredentialsResolver.java:22)
at com.amazon.ws.emr.hadoop.fs.guice.CredentialsProviderOverrider.override(CredentialsProviderOverrider.java:25)
at com.amazon.ws.emr.hadoop.fs.s3.lite.executor.GlobalS3Executor.executeOverriders(GlobalS3Executor.java:130)
at com.amazon.ws.emr.hadoop.fs.s3.lite.executor.GlobalS3Executor.execute(GlobalS3Executor.java:86)
at com.amazon.ws.emr.hadoop.fs.s3.lite.AmazonS3LiteClient.invoke(AmazonS3LiteClient.java:184)
at com.amazon.ws.emr.hadoop.fs.s3.lite.AmazonS3LiteClient.doesBucketExist(AmazonS3LiteClient.java:90)
at com.amazon.ws.emr.hadoop.fs.s3n.Jets3tNativeFileSystemStore.ensureBucketExists(Jets3tNativeFileSystemStore.java:139)
at com.amazon.ws.emr.hadoop.fs.s3n.Jets3tNativeFileSystemStore.initialize(Jets3tNativeFileSystemStore.java:116)
at com.amazon.ws.emr.hadoop.fs.s3n.S3NativeFileSystem.initialize(S3NativeFileSystem.java:508)
at com.amazon.ws.emr.hadoop.fs.EmrFileSystem.initialize(EmrFileSystem.java:111)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2859)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:99)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2896)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2878)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:392)
at org.apache.spark.deploy.DependencyUtils$.org$apache$spark$deploy$DependencyUtils$$resolveGlobPath(DependencyUtils.scala:190)
at org.apache.spark.deploy.DependencyUtils$$anonfun$resolveGlobPaths$2.apply(DependencyUtils.scala:146)
at org.apache.spark.deploy.DependencyUtils$$anonfun$resolveGlobPaths$2.apply(DependencyUtils.scala:144)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
at org.apache.spark.deploy.DependencyUtils$.resolveGlobPaths(DependencyUtils.scala:144)
at org.apache.spark.deploy.SparkSubmit$$anonfun$prepareSubmitEnvironment$3.apply(SparkSubmit.scala:354)
at org.apache.spark.deploy.SparkSubmit$$anonfun$prepareSubmitEnvironment$3.apply(SparkSubmit.scala:354)
at scala.Option.map(Option.scala:146)
at org.apache.spark.deploy.SparkSubmit.prepareSubmitEnvironment(SparkSubmit.scala:354)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:143)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
userData.json 不是我的应用程序的一部分，看起来它是 emr 内部的。
任何想法有什么问题吗？我通过 livy requests 提交工作。 集群设置： 2 个核心节点 m4.large 7 个任务节点 m5.4xlarge 1 个主节点 m5.xlarge
【问题讨论】：
-
可能dupe
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我不认为这是相关的，除非这是亚马逊做错的事情。此 SO 中的目录是 EMR 的内部目录，而不是 spark 作业的目标目录。
标签： amazon-web-services apache-spark amazon-emr