Per https://spark.apache.org/docs/latest/building-spark.html, spark 2.3.1 is built with hadoop 2.6.X by default. This is why I see my fat jar includes hadoop 2.6.5 (instead of 3.1.0) jars. HftpFileSystem has been removed in hadoop 3.
On https://spark.apache.org/downloads.html, I only see spark 2.3.1 built with hadoop 2.7. Where can I get spark 2.3.1 built with hadoop 3? Does spark 2.3.1 support hadoop 3? Appreciate your help. On Thu, Aug 30, 2018 at 8:59 AM Lian Jiang <jiangok2...@gmail.com> wrote: > Hi, > > I am using HDP3.0 which uses HADOOP3.1.0 and Spark 2.3.1. My spark > streaming jobs running fine in HDP2.6.4 (HADOOP2.7.3, spark 2.2.0) fails in > HDP3: > > java.lang.IllegalAccessError: class > org.apache.hadoop.hdfs.web.HftpFileSystem cannot access its superinterface > org.apache.hadoop.hdfs.web.TokenAspect$TokenManagementDelegator > > at java.lang.ClassLoader.defineClass1(Native Method) > > at java.lang.ClassLoader.defineClass(ClassLoader.java:763) > > at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142) > > at java.net.URLClassLoader.defineClass(URLClassLoader.java:467) > > at java.net.URLClassLoader.access$100(URLClassLoader.java:73) > > at java.net.URLClassLoader$1.run(URLClassLoader.java:368) > > at java.net.URLClassLoader$1.run(URLClassLoader.java:362) > > at java.security.AccessController.doPrivileged(Native Method) > > at java.net.URLClassLoader.findClass(URLClassLoader.java:361) > > at java.lang.ClassLoader.loadClass(ClassLoader.java:424) > > at java.lang.ClassLoader.loadClass(ClassLoader.java:357) > > at java.lang.Class.forName0(Native Method) > > at java.lang.Class.forName(Class.java:348) > > at java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:370) > > at java.util.ServiceLoader$LazyIterator.next(ServiceLoader.java:404) > > at java.util.ServiceLoader$1.next(ServiceLoader.java:480) > > at org.apache.hadoop.fs.FileSystem.loadFileSystems(FileSystem.java:3268) > > at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:3313) > > at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3352) > > at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:124) > > at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3403) > > at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3371) > > at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:477) > > at org.apache.hadoop.fs.Path.getFileSystem(Path.java:361) > > at > org.apache.hadoop.mapreduce.lib.input.LineRecordReader.initialize(LineRecordReader.java:85) > > at > org.apache.spark.sql.execution.datasources.HadoopFileLinesReader.<init>(HadoopFileLinesReader.scala:46) > > at > org.apache.spark.sql.execution.datasources.json.TextInputJsonDataSource$.readFile(JsonDataSource.scala:125) > > at > org.apache.spark.sql.execution.datasources.json.JsonFileFormat$$anonfun$buildReader$2.apply(JsonFileFormat.scala:132) > > at > org.apache.spark.sql.execution.datasources.json.JsonFileFormat$$anonfun$buildReader$2.apply(JsonFileFormat.scala:130) > > at > org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:148) > > at > org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:132) > > at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org > $apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:128) > > at > org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:182) > > at > org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:109) > > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown > Source) > > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614) > > at > org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:216) > > at > org.apache.spark.sql.execution.SortExec$$anonfun$1.apply(SortExec.scala:108) > > at > org.apache.spark.sql.execution.SortExec$$anonfun$1.apply(SortExec.scala:101) > > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830) > > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830) > > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) > > at org.apache.spark.scheduler.Task.run(Task.scala:109) > > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345) > > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > > at java.lang.Thread.run(Thread.java:745) > > > > Any idea? Thanks. > >
