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https://issues.apache.org/jira/browse/MAHOUT-542?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13070018#comment-13070018
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pragati meena commented on MAHOUT-542:
--------------------------------------
hi sebastian,
i am trying to run the example in windows using hadoop on cygwin , but i keep
getting the following error ,even though history file exists at
same directory location
Exception in thread "main" java.lang.IllegalStateException:
java.io.FileNotFoundException: File does not exist:
/user/hadoop/temp/errors/_logs
at
org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterator$1.apply(SequenceFileDirIterator.java:73)
at
org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterator$1.apply(SequenceFileDirIterator.java:67)
at com.google.common.collect.Iterators$8.next(Iterators.java:730)
at com.google.common.collect.Iterators$5.hasNext(Iterators.java:508)
at
com.google.common.collect.ForwardingIterator.hasNext(ForwardingIterator.java:40)
at
org.apache.mahout.utils.eval.ParallelFactorizationEvaluator.computeRmse(ParallelFactorizationEvaluator.java:111)
Any ideas on how to fix this
regards
Pragati Meena
> MapReduce implementation of ALS-WR
> ----------------------------------
>
> Key: MAHOUT-542
> URL: https://issues.apache.org/jira/browse/MAHOUT-542
> Project: Mahout
> Issue Type: New Feature
> Components: Collaborative Filtering
> Affects Versions: 0.5
> Reporter: Sebastian Schelter
> Assignee: Sebastian Schelter
> Fix For: 0.5
>
> Attachments: MAHOUT-452.patch, MAHOUT-542-2.patch,
> MAHOUT-542-3.patch, MAHOUT-542-4.patch, MAHOUT-542-5.patch,
> MAHOUT-542-6.patch, logs.zip
>
>
> As Mahout is currently lacking a distributed collaborative filtering
> algorithm that uses matrix factorization, I spent some time reading through a
> couple of the Netflix papers and stumbled upon the "Large-scale Parallel
> Collaborative Filtering for the Netflix Prize" available at
> http://www.hpl.hp.com/personal/Robert_Schreiber/papers/2008%20AAIM%20Netflix/netflix_aaim08(submitted).pdf.
> It describes a parallel algorithm that uses "Alternating-Least-Squares with
> Weighted-λ-Regularization" to factorize the preference-matrix and gives some
> insights on how the authors distributed the computation using Matlab.
> It seemed to me that this approach could also easily be parallelized using
> Map/Reduce, so I sat down and created a prototype version. I'm not really
> sure I got the mathematical details correct (they need some optimization
> anyway), but I wanna put up my prototype implementation here per Yonik's law
> of patches.
> Maybe someone has the time and motivation to work a little on this with me.
> It would be great if someone could validate the approach taken (I'm willing
> to help as the code might not be intuitive to read) and could try to
> factorize some test data and give feedback then.
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