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From nfantone <nfant...@gmail.com>
Subject Re: Clustering from DB
Date Mon, 06 Jul 2009 20:39:31 GMT
I was using Canopy to create input clusters, but the error appeared
while running kMeans (if I run kMeans' job only with previously
created clusters from Canopy placed in output/canopies as initial
clusters, it still fails). I noticed no other problems. I was using
revision 790979 before updating.  Strangely, there were no changes in
the job and drivers class from that revision. svn diff shows that the
only classes that changed in org.apache.mahout.clustering.kmeans
package were KMeansInfo.java and RandomSeedGenerator.java

On Mon, Jul 6, 2009 at 3:55 PM, Jeff Eastman<jdog@windwardsolutions.com> wrote:
> Hum, no, it's looking for the output of the first iteration. Were there
> other errors? What was the last revision you were running? It does look like
> something got horked, as it should be looking for output/clusters-0/*. Can
> you diff the job and driver class to see what changed?
>
> Jeff
>
> nfantone wrote:
>>
>> Fellows, today I updated to revision 791558 and while running kMeans I
>> got the following exception:
>>
>> WARNING: java.io.FileNotFoundException: File
>> output/clusters-0/part-00000/* does not exist.
>> java.io.FileNotFoundException: File output/clusters-0/part-00000/*
>> does not exist.
>>
>> The algorithm isn't interrupted, though. But this exception wasn't
>> thrown before the update and, to me, its message is not quite clear.
>> It seems as it's looking for any file inside a "part-00000" directory,
>> which doesn't exist; and, as far as I know, "part-xxxxx" are default
>> names for output files.
>>
>> I could show the entire stack trace, if needed. Any pointers?
>>
>>
>> On Thu, Jul 2, 2009 at 3:16 PM, nfantone<nfantone@gmail.com> wrote:
>>
>>>
>>> Thanks for the feedback, Jeff.
>>>
>>>
>>>>
>>>> The logical format of input to KMeans is <Key, Vector> as it is in
>>>> sequence
>>>> file format, but the Key is never used. To my knowledge, there is no
>>>> requirement to assign identifiers to the input points*. Users are free
>>>> to
>>>> associate an arbitrary name field with each vector - also label mappings
>>>> may
>>>> be assigned - but these are not manipulated by KMeans or any of the
>>>> other
>>>> clustering applications. The name field is now used as a vector
>>>> identifier
>>>> by the KMeansClusterMapper - if it is non-null - in the output step
>>>> only.
>>>>
>>>
>>> The key may not be used internally, but externally they can prove to
>>> be pretty useful. For me, keys are userIDs and each Vector represents
>>> his/her historical behavior. Being able to collect the output
>>> information as <UserID, ClusterID> is quite neat as it allows me to,
>>> for instance, retrieve user information using data directly from a
>>> HDFS file's field.
>>>
>>>
>>
>>
>>
>
>

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