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import org.slf4j.LoggerFactory

import scala.collection.mutable.HashSet

import org.apache.spark.SparkConf

import org.apache.spark.SparkContext

object Canopy {

def main(args: Array[String]): Unit = {

val input="/usr/data_test.csv"

val output="data.csv"

val slices = 8

val t1 = 8.0

val t2 = 4.0

val log = LoggerFactory.getLogger("Canopy")

val conf = new SparkConf().setAppName("Canopy").setMaster("local")

val sc = new SparkContext(conf)

try {

val oldpairs=sc.textFile(input)

val pairs = oldpairs.map { line =>

val pair = line.split(",")

(pair(0), pair(1).split(",").map(_.toDouble))

}

pairs.foreach(println)

val map_centers = new HashSet[(String, Array[Double])]

val raw_center_pairs = pairs.map(v =>

(v._1, canopy_(v, map_centers, t2))).filter(a => a._2 != null).collect().toList

val center_pairs = new HashSet[(String, Array[Double])]

for (i

canopy_(raw_center_pairs(i)._2, center_pairs, t2)

}

sc.makeRDD(center_pairs.toList, 1).map { pair =>

pair._1 + pair._2.mkString(",")

}.saveAsTextFile(output)

} catch {

case e: Exception =>

log.info(e.getStackTrace.mkString("\n"))

}

sc.stop()

}

def measure(v1: Array[Double], v2: Array[Double]): Double = {

var distance = 0.0

val aa = if (v1.length < v2.length)

v1.length

else

v2.length

for (i

distance += scala.math.pow(v1(i) - v2(i), 2)

}

distance

}

def canopy_(p0: (String, Array[Double]), pair: HashSet[(String, Array[Double])], t2: Double): (String, Array[Double]) = {

if (!pair.exists(p => measure(p._2, p0._2) < t2)) {

pair += p0

p0

} else {

null

}

}

}

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