[jira] [Commented] (SPARK-7442) Spark 1.3.1 / Hadoop 2.6 prebuilt pacakge has a broken S3 filesystem API

["Nicholas Chammas (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-7442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14532961#comment-14532961 ] 

Nicholas Chammas commented on SPARK-7442:
-----------------------------------------

Changing the filesystem from {{s3n}} to {{s3a}} yields this:

{code}
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: java.lang.RuntimeException: java.lang.ClassNotFoundException: Class org.apache.hadoop.fs.s3a.S3AFileSystem not found
{code}

Same thing happens with the Scala shell.

> Spark 1.3.1 / Hadoop 2.6 prebuilt pacakge has a broken S3 filesystem API
> ------------------------------------------------------------------------
>
>                 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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