亚马逊s3a使用Spark返回400 Bad Request

Question

出于结帐目的,我尝试将Amazon S3存储桶设置为检查点文件.

val checkpointDir = "s3a://bucket-name/checkpoint.txt"
val sc = new SparkContext(conf)
sc.setLocalProperty("spark.default.parallelism", "30")
sc.hadoopConfiguration.set("fs.s3a.access.key", "xxxxx")
sc.hadoopConfiguration.set("fs.s3a.secret.key", "xxxxx")
sc.hadoopConfiguration.set("fs.s3a.endpoint", "bucket-name.s3-website.eu-central-1.amazonaws.com")
val ssc = new StreamingContext(sc, Seconds(10))
ssc.checkpoint(checkpointDir)

但它会因此异常而停止

Exception in thread "main" com.amazonaws.services.s3.model.AmazonS3Exception: Status Code: 400, AWS Service: Amazon S3, AWS Request ID: 9D8E8002H3BBDDC7, AWS Error Code: null, AWS Error Message: Bad Request, S3 Extended Request ID: Qme5E3KAr/KX0djiq9poGXPJkmr0vuXAduZujwGlvaAl+oc6vlUpq7LIh70IF3LNgoewjP+HnXA=
at com.amazonaws.http.AmazonHttpClient.handleErrorResponse(AmazonHttpClient.java:798)
at com.amazonaws.http.AmazonHttpClient.executeHelper(AmazonHttpClient.java:421)
at com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:232)
at com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:3528)
at com.amazonaws.services.s3.AmazonS3Client.headBucket(AmazonS3Client.java:1031)
at com.amazonaws.services.s3.AmazonS3Client.doesBucketExist(AmazonS3Client.java:994)
at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:154)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2596)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
at org.apache.spark.streaming.StreamingContext.checkpoint(StreamingContext.scala:232)
at com.misterbell.shiva.StreamingApp$.main(StreamingApp.scala:89)
at com.misterbell.shiva.StreamingApp.main(StreamingApp.scala)
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:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:664)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:169)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:192)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:111)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

我不明白为什么我得到这个错误,我找不到任何例子.

Answer 1

此消息对应于"错误端点"或错误的签名版本支持.

在这里看到法兰克福是唯一一个不支持签名版本2的人.我是我选择的那个.

当然,毕竟我的研究不能说什么是签名版本,但在文档中并不明显.但V2似乎与s3a一起使用.

在S3界面中看到的端点不是真正的端点,它只是Web端点.

你有一次用论文端点像 sc.hadoopConfiguration.set("fs.s3a.endpoint", "s3-eu-west-1.amazonaws.com")

但默认情况下它与US端点一起工作

Answer 2

如果您无论如何都想在 spark 中使用支持 Signature V4 的区域，您可以-Dcom.amazonaws.services.s3.enableV4在运行时将标志传递给驱动程序选项和执行程序选项。例如：

spark-submit --conf spark.driver.extraJavaOptions='-Dcom.amazonaws.services.s3.enableV4' \
    --conf spark.executor.extraJavaOptions='-Dcom.amazonaws.services.s3.enableV4' \
    ... (other spark options)

使用此设置，即使 AWS sdk 版本不那么新鲜（com.amazonaws:aws-java-sdk:1.7.4在我的情况下），Spark 也能够写入法兰克福（和其他仅适用于 V4 的区域）