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https://issues.apache.org/jira/browse/SPARK-7442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14533029#comment-14533029
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Nicholas Chammas commented on SPARK-7442:
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Apparently this is an issue with Hadoop 2.6 upstream:
*
http://mail-archives.apache.org/mod_mbox/hadoop-user/201504.mbox/%3CCA+XUwYxPxLkfhOxn1jNkoUKEQQMcPWFzvXJ=u+kp28kdejo...@mail.gmail.com%3E
* https://issues.apache.org/jira/browse/HADOOP-11863
Jars for S3 access now need to be added manually.
Dunno if that means we need to do anything Spark-side, since this kind of a
breaking change.
> Spark 1.3.1 / Hadoop 2.6 prebuilt pacakge has broken S3 filesystem access
> -------------------------------------------------------------------------
>
> Key: SPARK-7442
> URL: https://issues.apache.org/jira/browse/SPARK-7442
> Project: Spark
> Issue Type: Bug
> Components: Build
> Affects Versions: 1.3.1
> Environment: OS X
> Reporter: Nicholas Chammas
>
> # Download Spark 1.3.1 pre-built for Hadoop 2.6 from the [Spark downloads
> page|http://spark.apache.org/downloads.html].
> # Add {{localhost}} to your {{slaves}} file and {{start-all.sh}}
> # Fire up PySpark and try reading from S3 with something like this:
> {code}sc.textFile('s3n://bucket/file_*').count(){code}
> # You will get an error like this:
> {code}py4j.protocol.Py4JJavaError: An error occurred while calling
> z:org.apache.spark.api.python.PythonRDD.collectAndServe.
> : java.io.IOException: No FileSystem for scheme: s3n{code}
> {{file:///...}} works. Spark 1.3.1 prebuilt for Hadoop 2.4 works. Spark 1.3.0
> works.
> It's just the combination of Spark 1.3.1 prebuilt for Hadoop 2.6 accessing S3
> that doesn't work.
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