/ParaBond/src/scaly/parabond/test/Mr05.scala

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package scaly.parabond.test



import org.scalatest.junit.JUnitSuite
import org.junit.Assert._
import org.junit.Test
import scaly.parabond.mr.MapReduce
import com.mongodb.casbah.MongoConnection
import com.mongodb.casbah.commons.MongoDBObject
import com.mongodb.casbah.MongoCursor
import scaly.parabond.util.MongoHelper
import scaly.parabond.value.SimpleBondValuator
import scala.util.Random

import scaly.parabond.util.Helper


/**

 * This class runs a map-reduce unit test for n portfolios in the

 * parabond database. It alternates between parallel and serial methods.

 * @author Ron Coleman, Ph.D.

 */

class Mr05 {

  /** Number of bond portfolios to analyze */

  val PORTF_NUM = 100

        

  /** Connects to the parabond DB */

  val mongo = MongoConnection("127.0.0.1")("parabond")

  

  /** Record captured with each result */

  case class Result(id : Int, price: Double, bondCount: Int, t0: Long, t1: Long)

  

  /** Initialize the random number generator */

  val ran = new Random(0)   

  

  /** Write a detailed report */

  val details = true

  

  /** Unit test entry point */

  @Test

  def test {

    // Set the number of portfolios to analyze

    val arg = System.getProperty("n")

    

    val n = if(arg == null) PORTF_NUM else arg.toInt

    

    print("\n"+this.getClass()+" "+ "N: "+n +" ")

    

    val details = if(System.getProperty("details") != null) true else false

        

    (1 to n).foreach { p =>

      // Choose a random portfolio

      val lottery = ran.nextInt(100000)+1 



      val results = new Array[Result](2)

      

      // Evaluate the portfolios in random order

      if(lottery %2 == 0) {

        results(0) = priceParallel(lottery)

        results(1) = priceSerially(lottery)

      }

      else {

        results(1) = priceSerially(lottery)         

        results(0) = priceParallel(lottery)

      }

      

      val dt0 = (results(0).t1 - results(0).t0) / 1000000000.0

      

      val dt1 = (results(1).t1 - results(1).t0) / 1000000000.0      

        

      println("%6d %10.2f %10.2f %6.4f %6.4f".format(results(0).id, results(0).price, results(1).price, dt0, dt1))

      

    }

  }

  

  def priceParallel(portfId : Int) : Result = {

    val t0 = System.nanoTime

    

    val list = List((portfId,Helper.curveCoeffs))

    

    val result = MapReduce.mapreduceBasic(list, mapping, reducing)  

    

    val t1 = System.nanoTime

    

    val rsult = result(portfId)(0)

    

    Result(portfId,rsult.price,rsult.bondCount,t0,t1)

  }

  

  def priceSerially(portfId : Int) : Result = {

      // Connect to the portfolio collection

      val t0 = System.nanoTime

      

      val portfsCollecton = mongo("Portfolios")

      

      val portfsQuery = MongoDBObject("id" -> portfId)



      val portfsCursor: MongoCursor = portfsCollecton.find(portfsQuery)



      // Get the bonds in the portfolio

      val bondIds = MongoHelper.asList(portfsCursor, "instruments")



      // Connect to the bonds collection

      val bondsCollection = mongo("Bonds")



      val value = bondIds.foldLeft(0.0) { (sum, id) =>

        

        // Get the bond from the bond collection

        val bondQuery = MongoDBObject("id" -> id)



        val bondCursor: MongoCursor = bondsCollection.find(bondQuery)



        val bond = MongoHelper.asBond(bondCursor)



        // Price the bond

        val valuator = new SimpleBondValuator(bond, Helper.curveCoeffs)



        val price = valuator.price



        // Add the price into the aggregate sum

        sum + price

      }    

      

      val t1 = System.nanoTime

      Result(portfId,value,bondIds.size,t0,t1)

  }

  

  /**

   * Maps a portfolio to a single price

   * @param portId Portfolio id

   * @param fitter Curve fitting coefficients

   * @returns List of (portf id, bond value))

   */

  def mapping(portfId: Int, fitter: List[Double]): List[(Int,Result)] = {

    // Value each bond in the portfolio

    val t0 = System.nanoTime

    

    // Connect to the portfolio collection

    val portfsCollecton = mongo("Portfolios")

    

    // Retrieve the portfolio 

    val portfsQuery = MongoDBObject("id" -> portfId)



    val portfsCursor : MongoCursor = portfsCollecton.find(portfsQuery)

    

    // Get the bonds in the portfolio

    val bondIds = MongoHelper.asList(portfsCursor,"instruments")

    

    // Connect to the bonds collection

    val bondsCollection = mongo("Bonds")

    

    val value = bondIds.foldLeft(0.0) { (sum, id) =>

      // Get the bond from the bond collection

      val bondQuery = MongoDBObject("id" -> id)



      val bondCursor: MongoCursor = bondsCollection.find(bondQuery)



      val bond = MongoHelper.asBond(bondCursor)



//      print("bond(" + bond + ") = ")

      

      // Price the bond

      val valuator = new SimpleBondValuator(bond, fitter)



      val price = valuator.price



//      println("%8.2f".format(price))

      

      // The price into the aggregate sum

      sum + price

    }    

    

    val t1 = System.nanoTime

    

    List((portfId, Result(portfId,value,bondIds.size,t0,t1)))

  }

  

  /**

   * Reduces trivially portfolio prices.

   * Since there's only one price per porfolio, there's nothing

   * really to reduce! 

   * @param portfId Portfolio id

   * @param vals Bond valuations

   * @returns List of portfolio valuation, one per portfolio

   */

  def reducing(portfId: Int,vals: List[Result]): List[Result] = {

    List(vals(0))

  }

}