Github user allwefantasy commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55089256
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The cluster resource 60 executors(60 cores, 220g memory)
The corpus size 240000 document
The number of iterations 100
The number of term 80000
The number of topics 500
alpha 0.1
beta 0.01
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val data =
sc.textFile(s"/output/william/spark-lda-data/trainings").sample(false,0.1)
val parsedData = data.map { line =>
val parts = line.split(',')
val values = parts(1).split(' ').map{k=>
val Array(pos,v) = k.split(":")
(pos.toInt,v.toInt)
}.toMap[Int,Int]
Document(parts(0).toInt,(0 until wordInfo.value.size).map(k=>
values.getOrElse(k,0)).toArray)
}
val (topicModel,documents) =
org.apache.spark.mllib.clustering.LDA.train(parsedData,wordInfo.value.size,500,30,(0.7*30).toInt,0.1,0.01)
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