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https://issues.apache.org/jira/browse/SPARK-20799?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16022807#comment-16022807
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Steve Loughran commented on SPARK-20799:
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If what I think is happening is, then it's the security tightening of 
HADOOP-3733 which has stopped this. It is sort-of-a-regression, but as it has a 
security benefit "stops leaking your secrets through logs" Its not something we 
want to revert. Anyway, it *never* worked if you had a "/" in your secret key, 
so the sole reason it worked for you in the past is that you don't (see: I know 
something about your secret credentials:)

Hadoop 2.8 is way better for S3A support all round, so I'd encourage you to 
stay and play. In particular,
# switch from s3n:// to s3a:// for your URLs, to get the new high-performance 
client
# try setting {{fs.s3a.experimental.fadvise=random}} in your settings and you 
should expect to see a significant speedup in ORC input.

If the use case here is that you want to use separate credentials for a 
specific bucket, you can use per-bucket config now
{code}
fs.s3a.bucket.site-2.access.key=my access key
fs.s3a.bucket.site-2.access.secret=my access secret
{code}

then when you refer to {{s3a://site-2/path}} ,  the specific key & secret for 
that bucket are picked up. This is why you shouldn't need to use inline secrets 
at all


> Unable to infer schema for ORC on reading ORC from S3
> -----------------------------------------------------
>
>                 Key: SPARK-20799
>                 URL: https://issues.apache.org/jira/browse/SPARK-20799
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.1.1
>            Reporter: Jork Zijlstra
>
> We are getting the following exception: 
> {code}org.apache.spark.sql.AnalysisException: Unable to infer schema for ORC. 
> It must be specified manually.{code}
> Combining following factors will cause it:
> - Use S3
> - Use format ORC
> - Don't apply a partitioning on de data
> - Embed AWS credentials in the path
> The problem is in the PartitioningAwareFileIndex def allFiles()
> {code}
> leafDirToChildrenFiles.get(qualifiedPath)
>           .orElse { leafFiles.get(qualifiedPath).map(Array(_)) }
>           .getOrElse(Array.empty)
> {code}
> leafDirToChildrenFiles uses the path WITHOUT credentials as its key while the 
> qualifiedPath contains the path WITH credentials.
> So leafDirToChildrenFiles.get(qualifiedPath) doesn't find any files, so no 
> data is read and the schema cannot be defined.
> Spark does output the S3xLoginHelper:90 - The Filesystem URI contains login 
> details. This is insecure and may be unsupported in future., but this should 
> not mean that it shouldn't work anymore.
> Workaround:
> Move the AWS credentials from the path to the SparkSession
> {code}
> SparkSession.builder
>       .config("spark.hadoop.fs.s3n.awsAccessKeyId", {awsAccessKeyId})
>       .config("spark.hadoop.fs.s3n.awsSecretAccessKey", {awsSecretAccessKey})
> {code}



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