Given some data, dump its pdf into a MYSQL db for purposes of plotting a histogram ( db accessed via Ruby )

gistfile1.scala

import com.twitter.scalding._
import com.twitter.scalding.mathematics.Histogram
import util.Random

class HistogramTest(args : Args) extends Job(args) {

  def cdf2pdf(cdf:Map[Double,Double], keys:List[Double], size:Int):Map[Double,Double] = {
    var m = Map[Double,Double]()
    keys.foldLeft((m, 0.0d))((a,b) =>{
      val myval = cdf(b)*size
      val myactual = myval - a._2
      m += (b->myactual)
      (m,myval)
    })._1
  }

  def l2t11(x:List[Double]) = {
    Tuple11(x(0), x(1),x(2),x(3), x(4),x(5),x(6), x(7),x(8),x(9), x(10))
  }

  val tuples = (1 to 1000).map( x=> Random.nextGaussian + 5).filter(x=> x>2 && x< 8) // mean = 5, sigma = 1
  val bins = 11
  val bin_names = (1 to bins).map( i=> Symbol("b"+i))

  IterableSource(tuples, 'n)
  .read
  .groupAll{
    _.histogram('n -> 'h, (8-2)/(bins+0.0d))
  }.mapTo('h->bin_names){
    h:Histogram =>
    val size = h.size
    val cdf = h.cdf
    val keys = h.keys
    var pdf = cdf2pdf( cdf, keys, size )
    keys.foreach( p=> printf("%f, %f\n", p, pdf(p)))
    val values = h.keys.map( k => pdf(k))
    l2t11( values )
  }
  .write(Tsv("data/histo_test"))
}

gistfile2.txt

Results:
cat data/histo_test 
3.0  27.0	70.0	143.0	196.0	216.0	175.0	101.0	48.0	16.0	3.0