Hadoop 2.9.2，Spark 2.4.0访问AWS s3a存储桶

Question

已经过了几天，但我无法使用Spark从公共Amazon Bucket下载：(

这是spark-shell命令：

spark-shell  --master yarn
              -v
              --jars file:/usr/local/hadoop/share/hadoop/tools/lib/hadoop-aws-2.9.2.jar,file:/usr/local/hadoop/share/hadoop/tools/lib/aws-java-sdk-bundle-1.11.199.jar
              --driver-class-path=/usr/local/hadoop/share/hadoop/tools/lib/hadoop-aws-2.9.2.jar:/usr/local/hadoop/share/hadoop/tools/lib/aws-java-sdk-bundle-1.11.199.jar

应用程序启动，shell等待提示：

   ____              __
  / __/__  ___ _____/ /__
 _\ \/ _ \/ _ `/ __/  '_/
/___/ .__/\_,_/_/ /_/\_\   version 2.4.0
   /_/

Using Scala version 2.11.12 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_191)
Type in expressions to have them evaluated.
Type :help for more information.

scala> val data1 = sc.textFile("s3a://my-bucket-name/README.md")

18/12/25 13:06:40 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 242.1 KB, free 246.7 MB)
18/12/25 13:06:40 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 24.2 KB, free 246.6 MB)
18/12/25 13:06:40 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hadoop-edge01:3545 (size: 24.2 KB, free: 246.9 MB)
18/12/25 13:06:40 INFO SparkContext: Created broadcast 0 from textFile at <console>:24
data1: org.apache.spark.rdd.RDD[String] = s3a://my-bucket-name/README.md MapPartitionsRDD[1] at textFile at <console>:24

scala> data1.count()

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.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodesInternal(TokenCache.java:97)
at org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodes(TokenCache.java:80)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:206)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2126)
at org.apache.spark.rdd.RDD.count(RDD.scala:1168)
... 49 elided
Caused by: java.lang.ClassNotFoundException: 
org.apache.hadoop.fs.StorageStatistics
  at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
  at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
  at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
  at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
  ... 77 more

scala>

1. 如下所述，在hadoop / core-site.xml中设置了所有AWS密钥，秘密密钥：Hadoop-AWS模块：与Amazon Web Services集成
2. 该存储桶是公共的-任何人都可以下载（已通过curl -O测试）
3. 如您所见，所有.jars由Hadoop本身从/usr/local/hadoop/share/hadoop/tools/lib/文件夹提供
4. 没有其他设置spark-defaults.conf-只有命令行中发送的设置

5. 这两个罐子都不提供此类：

   jar tf /usr/local/hadoop/share/hadoop/tools/lib/hadoop-aws-2.9.2.jar | grep org/apache/hadoop/fs/StorageStatistics
   (no result)
   
   jar tf /usr/local/hadoop/share/hadoop/tools/lib/aws-java-sdk-bundle-1.11.199.jar | grep org/apache/hadoop/fs/StorageStatistics
   (no result)
   

我该怎么办 ？我忘了加另一个罐子吗？什么确切的配置hadoop-aws和aws-java-sdk-bundle？版本？

Answer 1

嗯....终于找到问题了..

主要问题是我已经为Hadoop预安装了Spark。它是“针对Hadoop 2.7及更高版本的v2.4.0预先构建”。正如您在上面看到的我为之奋斗时所说的那样，这有点误导标题。实际上Spark附带了不同版本的hadoop jar。/ usr / local / spark / jars /中的清单显示它具有：

hadoop-common-2.7.3.jar
hadoop-client-2.7.3.jar
....

它只是丢失了：hadoop-aws和aws-java-sdk。我在Maven仓库中进行了一点挖掘：hadoop-aws-v2.7.3及其依赖项：aws-java-sdk-v1.7.4和voila！下载了这些jar并将其作为参数发送到Spark。像这样：

spark-shell
--master yarn
-v
--jars文件：/home/aws-java-sdk-1.7.4.jar，文件：/home/hadoop-aws-2.7.3.jar
--driver-class-path = / home / aws-java-sdk-1.7.4.jar：/home/hadoop-aws-2.7.3.jar

做了工作！

我只是想知道为什么Hadoop中的所有jar（以及将它们作为参数发送到--jar和--driver-class-path）都没有赶上。Spark会以某种方式自动选择罐子，而不是我发送的罐子

Answer 2

我劝你不要做你做过的事。您正在运行带有hadoop 2.7.2jar 的预构建 spark，hadoop 2.9.2并且您向类路径中添加了更多 jar 以使用hadoop 2.7.3版本中的s3来解决问题。

您应该做的是使用“hadoop free” spark 版本 - 并通过配置提供 hadoop 文件，如您在以下链接中所见 - https://spark.apache.org/docs/2.4.0/hadoop-提供的.html

主要部分：

在 conf/spark-env.sh

如果hadoop二进制文件在您的 PATH 中

export SPARK_DIST_CLASSPATH=$(hadoop classpath)

使用明确的hadoop二进制路径

export SPARK_DIST_CLASSPATH=$(/path/to/hadoop/bin/hadoop classpath)

传递 Hadoop 配置目录

export SPARK_DIST_CLASSPATH=$(hadoop --config /path/to/configs classpath)