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https://issues.apache.org/jira/browse/MAHOUT-1615?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Andrew Palumbo updated MAHOUT-1615:
-----------------------------------
Description:
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 SparkEngine.scala
drmFromHDFS(...):
{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.
was:
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:
`mahout> val drmTFIDF= drmFromHDFS( path =
"/tmp/mahout-work-andy/20news-test-vectors/part-r-00000")`
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 SparkEngine.scala drmFromHDFS:
`val rdd = sc.sequenceFile(path, classOf[Writable],
classOf[VectorWritable], minPartitions = parMin)
// Get rid of VectorWritable
.map(t => (t._1, t._2.get()))`
which gives the same key for all t._1.
> SparkEngine drmFromHDFS returning the same Key for all Key,VecPairs for
> Text-Keyed Files
> ----------------------------------------------------------------------------------------
>
> 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 SparkEngine.scala
> drmFromHDFS(...):
> {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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