Hello everyone,
I'm having some difficulty reading from my company's private S3 buckets.
I've got an S3 access key and secret key, and I can read the files fine from
a non-Spark Scala routine via AWScala. But trying to read them with the
SparkContext.textFiles([comma separated s3n://bucket/key uris]) leads to the
following stack trace (where I've changed the object key to use terms
'subbucket' and 'datafile-' for privacy reasons:
[error] (run-main-0) org.apache.hadoop.fs.s3.S3Exception:
org.jets3t.service.S3ServiceException: S3 HEAD request failed for
'/subbucket%2F2014%2F01%2Fdatafile-01.gz' - ResponseCode=403,
ResponseMessage=Forbidden
org.apache.hadoop.fs.s3.S3Exception: org.jets3t.service.S3ServiceException:
S3 HEAD request failed for '/subbucket%2F2014%2F01%2Fdatafile-01.gz' -
ResponseCode=403, ResponseMessage=Forbidden
at
org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.retrieveMetadata(Jets3tNativeFileSystemStore.java:122)
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:483)
at
org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryI
[... etc ...]
I'm handing off the credentials themselves via the following method:
def cleanKey(s: String): String = s.replace("/", "%2F")
val sc = new SparkContext("local[8]", "SparkS3Test")
sc.hadoopConfiguration.set("fs.s3n.awsAccessKeyId",
cleanKey(creds.accessKeyId))
sc.hadoopConfiguration.set("fs.s3n.awsSecretAccessKey",
cleanKey(creds.secretAccessKey))
The comma-separated URIs themselves look each look like:
s3n://odesk-bucket-name/subbucket/2014/01/datafile-01.gz
The actual string that I've replaced with 'subbucket' includes underscores
but otherwise is just straight ASCII; the term 'datafile' is substituting is
also just straight ASCII.
This is using Spark 1.0.0, via a library dependency to sbt of:
"org.apache.spark" % "spark-core_2.10" % "1.0.0"
Any tips appeciated!
Thanks much,
-Brian
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