如何在Spark提交中使用s3a和Apache spark 2.2（hadoop 2.8）？

Question

我试图使用使用hadoop 2.8版本构建的spark 2.2.0从spark访问S3数据，我在/jars/hadoop-aws-2.8.3.jar中使用/jars/aws-java-sdk-s3-1.10.6.jar，/jars/aws-java-sdk-core-1.10.6.jar和classpath

我得到以下异常

         java.lang.NoClassDefFoundError: org/apache/hadoop/fs/StorageStatistics
            at java.lang.Class.forName0(Native Method)
            at java.lang.Class.forName(Class.java:348)
            at org.apache.hadoop.conf.Configuration.getClassByNameOrNull(Configuration.java:2134)
            at org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:2099)
            at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2193)
            at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2654)
            at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2667)
            at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:94)
            at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2703)
            at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2685)
            at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373)
            at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295)
            at org.apache.spark.sql.execution.datasources.DataSource.hasMetadata(DataSource.scala:301)
            at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:344)
            at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
            at org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:441)
            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:498)
            at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
            at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
            at py4j.Gateway.invoke(Gateway.java:280)
            at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
            at py4j.commands.CallCommand.execute(CallCommand.java:79)
            at py4j.GatewayConnection.run(GatewayConnection.java:214)
            at java.lang.Thread.run(Thread.java:745)
        Caused by: java.lang.ClassNotFoundException: org.apache.hadoop.fs.StorageStatistics
            at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
            at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
            at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
            ... 27 more

然后我从火花安装目录classpath添加了hadoop-common jar到/sparkinstallation/jars/hadoop-common-2.8.3.jar，现在我收到以下错误：

        java.lang.IllegalAccessError: tried to access method org.apache.hadoop.metrics2.lib.MutableCounterLong.<init>(Lorg/apache/hadoop/metrics2/MetricsInfo;J)V from class org.apache.hadoop.fs.s3a.S3AInstrumentation
            at org.apache.hadoop.fs.s3a.S3AInstrumentation.streamCounter(S3AInstrumentation.java:194)
            at org.apache.hadoop.fs.s3a.S3AInstrumentation.streamCounter(S3AInstrumentation.java:216)
            at org.apache.hadoop.fs.s3a.S3AInstrumentation.<init>(S3AInstrumentation.java:139)
            at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:174)
            at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2669)
            at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:94)
            at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2703)
            at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2685)
            at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373)
            at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295)
            at org.apache.spark.sql.execution.datasources.DataSource.hasMetadata(DataSource.scala:301)
            at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:344)
            at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
            at org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:441)
            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:498)
            at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
            at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
            at py4j.Gateway.invoke(Gateway.java:280)
            at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
            at py4j.commands.CallCommand.execute(CallCommand.java:79)
            at py4j.GatewayConnection.run(GatewayConnection.java:214)
            at java.lang.Thread.run(Thread.java:745)

如果我错过了什么，有人可以帮忙吗？

我已经提到了链接 - How to use s3 with Apache spark 2.2 in the Spark shell，但没有帮助

Answer 1

我建议将依赖项添加到您的spark-submit命令，如下所示，这将下载所需的所有依赖项。如果您只是添加一个jar，您可能仍然缺少一些其他依赖项：

 spark-shell --packages "org.apache.hadoop:hadoop-aws:2.7.3"
 spark-submit --packages "org.apache.hadoop:hadoop-aws:2.7.3"

另一种方法是将依赖项捆绑到您的作业jar文件中，然后使用普通的spark-sbumit