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Posted to dev@mahout.apache.org by "Andrew Palumbo (JIRA)" <ji...@apache.org> on 2014/09/14 16:53:34 UTC
[jira] [Issue Comment Deleted] (MAHOUT-1615) SparkEngine
drmFromHDFS returning the same Key for all Key,Vec Pairs for Text-Keyed
SequenceFiles
[ https://issues.apache.org/jira/browse/MAHOUT-1615?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Andrew Palumbo updated MAHOUT-1615:
-----------------------------------
Comment: was deleted
(was: Possibly a spark bug?)
> SparkEngine drmFromHDFS returning the same Key for all Key,Vec Pairs for Text-Keyed SequenceFiles
> -------------------------------------------------------------------------------------------------
>
> Key: MAHOUT-1615
> URL: https://issues.apache.org/jira/browse/MAHOUT-1615
> Project: Mahout
> Issue Type: Bug
> Reporter: Andrew Palumbo
> Fix For: 1.0
>
>
> When reading in seq2sparse output from HDFS in the spark-shell of form <Text,VectorWriteable> SparkEngine's drmFromHDFS method is creating rdds with the same Key for all Pairs:
> {code}
> mahout> val drmTFIDF= drmFromHDFS( path = "/tmp/mahout-work-andy/20news-test-vectors/part-r-00000")
> {code}
> Has keys:
> {...}
> key: /talk.religion.misc/84570
> key: /talk.religion.misc/84570
> key: /talk.religion.misc/84570
> {...}
> for the entire set. This is the last Key in the set.
> The problem can be traced to the first line of drmFromHDFS(...) in SparkEngine.scala:
> {code}
> val rdd = sc.sequenceFile(path, classOf[Writable], classOf[VectorWritable], minPartitions = parMin)
> // Get rid of VectorWritable
> .map(t => (t._1, t._2.get()))
> {code}
> which gives the same key for all t._1.
>
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