Spark/Hadoop在AWS S3上不支持SSE-KMS加密 [英] Doesn't Spark/Hadoop support SSE-KMS encryption on AWS S3

问题描述

我正在尝试使用KMS密钥(SSE-KMS)通过服务器端加密在S3上保存rdd，但是出现以下异常:

线程主"中的异常 com.amazonaws.services.s3.model.AmazonS3Exception:状态码:400， AWS服务:Amazon S3，AWS请求ID:695E32175EBA568A，AWS错误 代码:InvalidArgument，AWS错误消息:加密方法 不支持指定的，S3扩展请求ID: Pi + HFLg0WsAWtkdI2S/xViOcRPMCi7zdHiaO5n1f7tiwpJe2z0lPY1C2Cr53PnnUCj3358Gx3AQ =

以下是我的测试代码中的一部分，该代码通过使用SSE-KMS进行加密在S3上编写rdd:

val sparkConf = new SparkConf().
  setMaster("local[*]").
  setAppName("aws-encryption")
val sc = new SparkContext(sparkConf)

sc.hadoopConfiguration.set("fs.s3a.access.key", AWS_ACCESS_KEY)
sc.hadoopConfiguration.set("fs.s3a.secret.key", AWS_SECRET_KEY)
sc.hadoopConfiguration.setBoolean("fs.s3a.sse.enabled", true)
sc.hadoopConfiguration.set("fs.s3a.server-side-encryption-algorithm", "SSE-KMS")
sc.hadoopConfiguration.set("fs.s3a.sse.kms.keyId", KMS_ID)

val s3a = new org.apache.hadoop.fs.s3a.S3AFileSystem
val s3aName = s3a.getClass.getName
sc.hadoopConfiguration.set("fs.s3a.impl", s3aName)

val rdd = sc.parallelize(Seq("one", "two", "three", "four"))
println("rdd is: " + rdd.collect())
rdd.saveAsTextFile(s"s3a://$bucket/$objKey")

尽管如此，我仍可以使用AES256加密在s3上写rdd.

spark/hadoop的KMS密钥加密值是否不同于"SSE-KMS"?

任何人都可以建议我在这里缺少什么或做错什么吗.

环境详细信息如下:

• 火花:1.6.1
• Hadoop:2.6.0
• Aws-Java-Sdk:1.7.4

谢谢.

解决方案

不幸的是，似乎Hadoop的现有版本(即2.8)不支持SSE-KMS:(

以下是观察结果:

1. 直到Hadoop 2.8.1才支持SSE-KMS
2. 应该在Hadoop 2.9中引入的SSE-KMS
3. 在Hadoop 3.0.0alpha版本中，支持SSE-KMS.

相同的观察结果适用于Java的AWS开发工具包

1. SSE-KMS是在aws-java-sdk 1.9.5中引入的

I am trying to save an rdd on S3 with server side encryption using KMS key (SSE-KMS), But I am getting the following exception:

Exception in thread "main" com.amazonaws.services.s3.model.AmazonS3Exception: Status Code: 400, AWS Service: Amazon S3, AWS Request ID: 695E32175EBA568A, AWS Error Code: InvalidArgument, AWS Error Message: The encryption method specified is not supported, S3 Extended Request ID: Pi+HFLg0WsAWtkdI2S/xViOcRPMCi7zdHiaO5n1f7tiwpJe2z0lPY1C2Cr53PnnUCj3358Gx3AQ=

Following is the piece of my test code to write an rdd on S3 by using SSE-KMS for encryption:

val sparkConf = new SparkConf().
  setMaster("local[*]").
  setAppName("aws-encryption")
val sc = new SparkContext(sparkConf)

sc.hadoopConfiguration.set("fs.s3a.access.key", AWS_ACCESS_KEY)
sc.hadoopConfiguration.set("fs.s3a.secret.key", AWS_SECRET_KEY)
sc.hadoopConfiguration.setBoolean("fs.s3a.sse.enabled", true)
sc.hadoopConfiguration.set("fs.s3a.server-side-encryption-algorithm", "SSE-KMS")
sc.hadoopConfiguration.set("fs.s3a.sse.kms.keyId", KMS_ID)

val s3a = new org.apache.hadoop.fs.s3a.S3AFileSystem
val s3aName = s3a.getClass.getName
sc.hadoopConfiguration.set("fs.s3a.impl", s3aName)

val rdd = sc.parallelize(Seq("one", "two", "three", "four"))
println("rdd is: " + rdd.collect())
rdd.saveAsTextFile(s"s3a://$bucket/$objKey")

Although, I am able to write rdd on s3 with AES256 encryption.

Does spark/hadoop have a different value for KMS key encryption instead of "SSE-KMS"?

Can anyone please suggest what I am missing here or doing wrong.

Environment details as follow:

• Spark: 1.6.1
• Hadoop: 2.6.0
• Aws-Java-Sdk: 1.7.4

Thank you in advance.

解决方案

Unfortunately, It seems like existing version of Hadoop i.e. 2.8 does not support SSE-KMS :(

Following is the observation:

1. SSE-KMS is not supported till Hadoop 2.8.1
2. SSE-KMS supposed to be introduced in Hadoop 2.9
3. In Hadoop 3.0.0alpha version, SSE-KMS is supported.

Same observation w.r.t. AWS SDK for Java

1. SSE-KMS was introduced in aws-java-sdk 1.9.5

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