>From the stacktrace:
FAILEDjava.lang.NumberFormatException: For input string: "A1234567"
at
java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
Obviously, the input's incorrect.
On Wednesday, November 20, 2013 6:02 PM, Sameer Tilak <ssti...@live.com> wrote:
Dear Sebastian,I tried using ItemSimilarityJob.My data has the following format
Each line contains data in the format:userid itemid (I also tried userid,
itemcode). Itemcode is a string. However, I am getting the following error. May
be my input format is incorrect.
./mahout org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob
--input testdata/similarityinput -o testdata/similarityoutput
--similarityClassname SIMILARITY_COOCCURRENCE --maxSimilaritiesPerItem 10
13/11/20 14:46:39 WARN driver.MahoutDriver: No
org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob.props found
on classpath, will use command-line arguments only13/11/20 14:46:39 INFO
common.AbstractJob: Command line arguments: {--booleanData=[false],
--endPhase=[2147483647], --input=[testdata/similarityinput], --maxPrefs=[500],
--maxSimilaritiesPerItem=[10], --minPrefsPerUser=[1],
--output=[testdata/similarityoutput],
--similarityClassname=[SIMILARITY_COOCCURRENCE], --startPhase=[0],
--tempDir=[temp]}13/11/20 14:46:39 INFO common.AbstractJob: Command line
arguments: {--booleanData=[false], --endPhase=[2147483647],
--input=[testdata/similarityinput], --minPrefsPerUser=[1],
--output=[temp/prepareRatingMatrix],
--ratingShift=[0.0], --startPhase=[0], --tempDir=[temp]}13/11/20 14:46:41 INFO
input.FileInputFormat: Total input paths to process : 113/11/20 14:46:41 INFO
util.NativeCodeLoader: Loaded the native-hadoop library13/11/20 14:46:41 WARN
snappy.LoadSnappy: Snappy native library not loaded13/11/20 14:46:41 INFO
mapred.JobClient: Running job: job_201311111627_011513/11/20 14:46:42 INFO
mapred.JobClient: map 0% reduce 0%13/11/20 14:47:00 INFO mapred.JobClient:
Task Id : attempt_201311111627_0115_m_000000_0, Status :
FAILEDjava.lang.NumberFormatException: For input string: "A1234567" at
java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Long.parseLong(Long.java:441) at
java.lang.Long.parseLong(Long.java:483) at
org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper.map(ItemIDIndexMapper.java:50)
at
org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper.map(ItemIDIndexMapper.java:31)
at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:144) at
org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:764) at
org.apache.hadoop.mapred.MapTask.run(MapTask.java:370) at
org.apache.hadoop.mapred.Child$4.run(Child.java:255) at
java.security.AccessController.doPrivileged(Native Method) at
javax.security.auth.Subject.doAs(Subject.java:415) at
org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1121)
at org.apache.hadoop.mapred.Child.main(Child.java:249)
13/11/20 14:47:11 INFO mapred.JobClient: Task Id :
attempt_201311111627_0115_m_000000_1, Status :
FAILEDjava.lang.NumberFormatException: For input string: "A1234567" at
java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Long.parseLong(Long.java:441) at
java.lang.Long.parseLong(Long.java:483) at
org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper.map(ItemIDIndexMapper.java:50)
at
org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper.map(ItemIDIndexMapper.java:31)
at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:144) at
org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:764) at
org.apache.hadoop.mapred.MapTask.run(MapTask.java:370) at
org.apache.hadoop.mapred.Child$4.run(Child.java:255) at
java.security.AccessController.doPrivileged(Native Method) at
javax.security.auth.Subject.doAs(Subject.java:415) at
org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1121)
at org.apache.hadoop.mapred.Child.main(Child.java:249)
> Date: Wed, 20 Nov 2013 08:22:07 +0100
> From: ssc.o...@googlemail.com
> To: user@mahout.apache.org
> Subject: Re: Mahout fpg
>
> You can use ItemSimilarityJob to find sets of items that cooccur
> together in your users interactions.
>
> --sebastian
>
>
> On 20.11.2013 08:11, Sameer Tilak wrote:
> >
> >
> >
> > Hi Sunil,
> > Thanks for your reply. We can benefit a lot from the parallel frequent
> > pattern matching functionality. Will there be any alternative in future
> > releases? I guess, we can use older versions of Mahout if we need that.
> >
> >> Date: Tue, 19 Nov 2013 19:25:54 -0800
> >> From: suneel_mar...@yahoo.com
> >> Subject: Re: Mahout fpg
> >> To: user@mahout.apache.org
> >>
> >> Fpg has been removed from the codebase as it will not be supported.
> >>
> >>
> >>
> >>
> >>
> >> On Tuesday, November 19, 2013 8:56 PM, Sameer Tilak <ssti...@live.com>
> >> wrote:
> >>
> >> Hi everyone,I downloaded the latest version of Mahout and did mvn install.
> >> When I try to run fog, I get the following errors. Do I need to download
> >> and compile FPG separately? Looks like somehow it has not been included in
> >> the list of valid programs.
> >> 13/11/19 17:49:19 WARN driver.MahoutDriver: Unable to add class:
> >> fpg13/11/19 17:49:19 WARN driver.MahoutDriver: No fpg.props found on
> >> classpath, will use command-line arguments onlyUnknown program 'fpg'
> >> chosen.Valid program names are: arff.vector: : Generate Vectors from an
> >> ARFF file or directory baumwelch: : Baum-Welch algorithm for unsupervised
> >> HMM training canopy: : Canopy clustering cat: : Print a file or resource
> >> as the logistic regression models would see it cleansvd: : Cleanup and
> >> verification of SVD output clusterdump: : Dump cluster output to text
> >> clusterpp: : Groups Clustering Output In Clusters cmdump: : Dump
> >> confusion matrix in HTML or text formats concatmatrices: : Concatenates 2
> >> matrices of same cardinality into a single matrix cvb: : LDA via
> >> Collapsed Variation Bayes (0th deriv. approx) cvb0_local: : LDA via
> >> Collapsed Variation Bayes, in memory locally. evaluateFactorization: :
> >> compute RMSE and MAE of a rating
> >> matrix factorization against probes fkmeans: : Fuzzy K-means clustering
> >>hmmpredict: : Generate random sequence of observations by given HMM
> >>itemsimilarity: : Compute the item-item-similarities for item-based
> >>collaborative filtering kmeans: : K-means clustering lucene.vector: :
> >>Generate Vectors from a Lucene index lucene2seq: : Generate Text
> >>SequenceFiles from a Lucene index matrixdump: : Dump matrix in CSV format
> >>matrixmult: : Take the product of two matrices parallelALS: : ALS-WR
> >>factorization of a rating matrix qualcluster: : Runs clustering
> >>experiments and summarizes results in a CSV recommendfactorized: : Compute
> >>recommendations using the factorization of a rating matrix
> >>recommenditembased: : Compute recommendations using item-based
> >>collaborative filtering regexconverter: : Convert text files on a per line
> >>basis based on regular expressions resplit: : Splits a set of
> >>SequenceFiles into a number of equal splits
rowid: :
> >> Map SequenceFile<Text,VectorWritable> to
> >>{SequenceFile<IntWritable,VectorWritable>, SequenceFile<IntWritable,Text>}
> >>rowsimilarity: : Compute the pairwise similarities of the rows of a matrix
> >>runAdaptiveLogistic: : Score new production data using a probably trained
> >>and validated AdaptivelogisticRegression model runlogistic: : Run a
> >>logistic regression model against CSV data seq2encoded: : Encoded Sparse
> >>Vector generation from Text sequence files seq2sparse: : Sparse Vector
> >>generation from Text sequence files seqdirectory: : Generate sequence
> >>files (of Text) from a directory seqdumper: : Generic Sequence File dumper
> >> seqmailarchives: : Creates SequenceFile from a directory containing
> >>gzipped mail archives seqwiki: : Wikipedia xml dump to sequence file
> >>spectralkmeans: : Spectral k-means clustering split: : Split Input data
> >>into test and train sets splitDataset: : split a rating dataset into
> >>training and probe parts ssvd: :
> >> Stochastic SVD streamingkmeans: : Streaming k-means clustering svd: :
> >>Lanczos Singular Value Decomposition testnb: : Test the Vector-based Bayes
> >>classifier trainAdaptiveLogistic: : Train an AdaptivelogisticRegression
> >>model trainlogistic: : Train a logistic regression using stochastic
> >>gradient descent trainnb: : Train the Vector-based Bayes classifier
> >>transpose: : Take the transpose of a matrix validateAdaptiveLogistic: :
> >>Validate an AdaptivelogisticRegression model against hold-out data set
> >>vecdist: : Compute the distances between a set of Vectors (or Cluster or
> >>Canopy, they must fit in memory) and a list of Vectors vectordump: : Dump
> >>vectors from a sequence file to text viterbi: : Viterbi decoding of hidden
> >>states from given output states sequence
> >
> >
> >
>
