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https://issues.apache.org/jira/browse/MAHOUT-524?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13132810#comment-13132810
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Jeff Eastman commented on MAHOUT-524:
-------------------------------------
All of this is buried inside of DistributedLanczosSolver. Either the problem
resides in there and should impact all users of DLS or it is in the
SpectralKMeansDriver setup which invokes the DLS. Turns out the DLS.runJob(...)
method employed (line 65) is only called by spectral clustering (KMeans and
Eigencuts). The one other caller, DLS.runJob(...) (line 80) is itself never
called.
Just looking at the invocation site (SpectralKMeansDriver.run() line 155, I see
two file paths being passed into DLS.runJob(...): the lanczosSeqFiles path is
output/calculations/eigenvectors-17, the desired output path, and the
LanczosState is constructed with L, a DRM with inputPath
examples/output/calculations/laplacian-89. This is the input path which is
failing in getFileStatus and causing the exception. Both of these look
reasonable to me.
There are; however, several different Configuration objects being manipulated
by SKMD. I'm suspicious there is something horked in one of them which is
causing the DLS file not found.
> DisplaySpectralKMeans example fails
> -----------------------------------
>
> Key: MAHOUT-524
> URL: https://issues.apache.org/jira/browse/MAHOUT-524
> Project: Mahout
> Issue Type: Bug
> Components: Clustering
> Affects Versions: 0.4, 0.5
> Reporter: Jeff Eastman
> Assignee: Shannon Quinn
> Labels: clustering, k-means, visualization
> Fix For: 0.6
>
> Attachments: EclipseLog_20110918.txt,
> SpectralKMeans_fail_20110919.txt, aff.txt, raw.txt, spectralkmeans.png
>
>
> I've committed a new display example that attempts to push the standard
> mixture of models data set through spectral k-means. After some tweaking of
> configuration arguments and a bug fix in EigenCleanupJob it runs spectral
> k-means to completion. The display example is expecting 2-d clustered points
> and the example is producing 5-d points. Additional I/O work is needed before
> this will play with the rest of the clustering algorithms.
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