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https://issues.apache.org/jira/browse/SPARK-15729?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15312541#comment-15312541
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Marco Capuccini edited comment on SPARK-15729 at 6/2/16 4:05 PM:
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[~sowen] I see! Thanks for the clarification. I'll open a PR, I think many
people think that a distributed FS is optional when using Spark in a
distributed environment. I did not mention that when I was running my
applications with 1.4.0 the data was written to NFS, and maybe that's the
reason why it was working fine.
I have another question. Let's assume I have copied the input data on each
node, in the exactly same path, and read it using sc.textFile. With such
assumption, let's say I perform some analysis on the dataset, reducing it to
something that can be collected on the driver node. Now if I collect the
reduced dataset, and I save it only on the machine where the driver is running,
using the Scala IO primitives, would this work? Or would there be some
corruption in the results?
was (Author: m.capucc...@gmail.com):
I see! Thanks for the clarification. I'll open a PR, I think many people think
that a distributed FS is optional when using Spark in a distributed
environment. I did not mention that when I was running my applications with
1.4.0 the data was written to NFS, and maybe that's the reason why it was
working fine.
I have another question. Let's assume I have copied the input data on each
node, in the exactly same path, and read it using sc.textFile. With such
assumption, let's say I perform some analysis on the dataset, reducing it to
something that can be collected on the driver node. Now if I collect the
reduced dataset, and I save it only on the machine where the driver is running,
using the Scala IO primitives, would this work? Or would there be some
corruption in the results?
> saveAsTextFile not working on regular filesystem
> ------------------------------------------------
>
> Key: SPARK-15729
> URL: https://issues.apache.org/jira/browse/SPARK-15729
> Project: Spark
> Issue Type: Bug
> Affects Versions: 1.6.1
> Reporter: Marco Capuccini
> Priority: Blocker
>
> I set up a standalone Spark cluster. I don't need HDFS, so I just want to
> save the files on the regular file system in a distributed manner. For
> testing purpose, I opened a Spark Shell, and I run the following code.
> sc.parallelize(1 to 100).saveAsTextFile("file:///mnt/volume/test.txt")
> I got no error from this, but if I go to inspect the /mnt/volume/test.txt
> folder on each node this is what I see:
> On the master (where I launched the spark shell):
> /mnt/volume/test.txt/_SUCCESS
> On the workers:
> /mnt/volume/test.txt/_temporary
> It seems like some failure occurred, but I didn't get any error. Is this a
> bug, or am I missing something?
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