[jira] [Updated] (MAHOUT-1615) SparkEngine drmFromHDFS returning the same Key for all Key,Vec Pairs for Text-Keyed SequenceFiles

["Andrew Palumbo (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MAHOUT-1615?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Andrew Palumbo updated MAHOUT-1615:
-----------------------------------
    Summary: SparkEngine drmFromHDFS returning the same Key for all Key,Vec Pairs for Text-Keyed SequenceFiles  (was: SparkEngine drmFromHDFS returning the same Key for all Key,VecPairs for Text-Keyed sequenceFiles)

> 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.
>   



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)