This fork provides some additional multicore support by favoring Parallelization w/ plyr
tm_mapany of plyr's options for
removeWords on a 10,000 document corpus with and without parallelization (2011 iMac 2.8 GHz Intel Core i5, 8 GB RAM, OS X 10.6.7, R version 2.13.0 Patched (2011-04-23 r55622), with 4 parallel workers). (Not necessarily representative of anything.)
system.time(tm::tm_map(inboundCorpus[1:10000], removeWords, myStopWords)) elapsed = 100.681
library(doMC) registerDoMC(cores=4) system.time(tmparallel::tm_map(inboundCorpus[1:10000], removeWords, myStopWords, .parallel=T, .progress='text')) elapsed = 53.809
With equivalent size
snow MPI cluster:
library(snow) makeCluster(4, type="MPI") system.time(tm::tm_map(inboundCorpus[1:10000], removeWords, myStopWords)) elapsed = 117.673
This adds an option to Option to use Rstem instead of SnowballStemmer
stemmer="Rstem"to use the implementation from Omegahat.org's Rstem package. This eliminates nasty dependencies on Rjava, etc. and has some performance advantages.
stemDocument on a 48,415 document corpus with Rstem vs. Snowball stemmer and with Rstem and parallelization (2011 iMac 2.8 GHz Intel Core i5, 8 GB RAM, OS X 10.6.7, R version 2.13.0 Patched (2011-04-23 r55622), with 4 parallel workers). (Not necessarily representative of anything.)
With SnowballStemmer, non parallel:
system.time(tm_map(inboundCorpus, stemDocument, .progress='text')) user system elapsed 731.575 4.220 730.456
With Rstem, non parallel:
system.time(tm_map(inboundCorpus, stemDocument, "english", stemmer="Rstem", .progress='text')) user system elapsed 180.282 0.626 181.013
With Rstem, parallel:
system.time(tm_map(inboundCorpus, stemDocument, "english", stemmer="Rstem", .progress='text', .parallel=T)) user system elapsed 240.981 3.216 152.029
R-Forge SVN README
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