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https://issues.apache.org/jira/browse/MAHOUT-1833?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Edmond Luo updated MAHOUT-1833:
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Summary: Enhance svec function to accepting cardinality as parameter
(was: One more svec function accepting cardinality as parameter )
> Enhance svec function to accepting cardinality as parameter
> ------------------------------------------------------------
>
> Key: MAHOUT-1833
> URL: https://issues.apache.org/jira/browse/MAHOUT-1833
> Project: Mahout
> Issue Type: Improvement
> Affects Versions: 0.12.0
> Environment: Mahout Spark Shell 0.12.0,
> Spark 1.6.0 Cluster on Hadoop Yarn 2.7.1,
> Centos7 64bit
> Reporter: Edmond Luo
>
> It will be nice to add one more wrapper function like below to
> org.apache.mahout.math.scalabindings
> {code}
> /**
> * create a sparse vector out of list of tuple2's with specific
> cardinality(size),
> * throws IllegalArgumentException if cardinality is not bigger than required
> cardinality of sdata
> * @param cardinality sdata
> * @return
> */
> def svec(cardinality: Int, sdata: TraversableOnce[(Int, AnyVal)]) = {
> val required = if (sdata.nonEmpty) sdata.map(_._1).max + 1 else 0
> if (cardinality < required) {
> throw new IllegalArgumentException(s"Cardinality[%cardinality] must be
> bigger than required[%required]!")
> }
> val initialCapacity = sdata.size
> val sv = new RandomAccessSparseVector(cardinality, initialCapacity)
> sdata.foreach(t ⇒ sv.setQuick(t._1,
> t._2.asInstanceOf[Number].doubleValue()))
> sv
> }
> {code}
> So user can specify the cardinality for the created sparse vector.
> This is very useful and convenient if user wants to create a DRM with many
> sparse vectors and the vectors are not with the same actual size(but with the
> same logical size, e.g. rows of a sparse matrix).
> Below code should demonstrate the case:
> {code}
> var cardinality = 20
> val rdd = sc.textFile("/some/file.txt").map(_.split(",")).map(line =>
> (line(0).toInt, Array((line(1).toInt,1)))).reduceByKey((v1, v2) => v1 ++
> v2).map(row => (row._1, svec(cardinality, row._2)))
> val drm = drmWrap(rdd.map(row => (row._1, row._2.asInstanceOf[Vector])))
> // All element wise opperation will fail for those DRM with not
> cardinality-consistent SparseVector
> val drm2 = drm + drm
> val drm3 = drm - drm
> val drm4 = drm * drm
> val drm5 = drm / drm
> {code}
> Notice that in the last map, the svec acceptted one more cardinality
> parameter, so the cardinality of those created SparseVector can be consistent.
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