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Posted to issues@spark.apache.org by "Peng Cheng (JIRA)" <ji...@apache.org> on 2015/05/24 20:55:17 UTC
[jira] [Comment Edited] (SPARK-7442) Spark 1.3.1 / Hadoop 2.6
prebuilt pacakge has broken S3 filesystem access
[ https://issues.apache.org/jira/browse/SPARK-7442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14557820#comment-14557820 ]
Peng Cheng edited comment on SPARK-7442 at 5/24/15 6:55 PM:
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Adding jar won't solve the problem:
you need to set the following parameters:
--conf spark.hadoop.fs.s3n.impl=org.apache.hadoop.fs.s3native.NativeS3FileSystem
--conf spark.hadoop.fs.s3.impl=org.apache.hadoop.fs.s3.S3FileSystem
But in my 2.6 environment the fs implementation in the added jar is ignored by worker's classloader for unknow reason, see http://stackoverflow.com/questions/30426245/apache-spark-classloader-cannot-find-classdef-in-the-jar
was (Author: peng):
Adding jar won't solve the problem:
you need to set the following parameters:
--conf spark.hadoop.fs.s3n.impl=org.apache.hadoop.fs.s3native.NativeS3FileSystem
--conf spark.hadoop.fs.s3.impl=org.apache.hadoop.fs.s3.S3FileSystem
But in my 2.6 environment the added jar is ignored by worker's classloader for unknow reason, see http://stackoverflow.com/questions/30426245/apache-spark-classloader-cannot-find-classdef-in-the-jar
> 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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