gistfile1.scala

val entryBuilder=PhoneEntry.newBuilder()
val aggregateBuilder = Aggregate.newBuilder()
val phoneBook = new mutable.HashMap[Long,PhoneEntry]()
val balances = new ListBuffer[Double]()
val hoursBreakdown = new Array[Int](24)
val sample = calls.head
var sumDuration = 0L
var sumPricing = 0.0
var minDuration = Long.MaxValue
var maxDuration = Long.MinValue
var hadAnyDiscount = false
var sumDiscount = 0.0
var sumAddCharge = 0.0
var minBalance = Double.MaxValue
var maxBalance = Double.MinValue

for (call<-calls) {
    sumDuration += call.duration
    minDuration = if (call.duration<minDuration) call.duration else minDuration
    maxDuration = if (call.duration>maxDuration) call.duration else maxDuration
    
    sumPricing +=  call.pricing
    
    sumDiscount += call.discount
    hadAnyDiscount = if (call.discount>0) true else hadAnyDiscount
    
    sumAddCharge += call.addCharge
    
    minBalance = if (call.balance>minBalance) call.balance else minBalance
    maxBalance = if (call.balance>maxBalance) call.balance else maxBalance
    balances += call.balance
    
    phoneBook(call.toNumber) =  buildPhoneEntry(call)
    hoursBreakdown(call.hour) += 1
}

val count =balances.size // we can use balances as it is the same size
val avgDuration = sumDuration.toDouble / count.toDouble
val avgPricing = sumPricing / count
val avgDiscount = sumDiscount / count
val avgAddCharge = sumAddCharge / count
val sortedBalances = balances.toList.sorted    // second pass just on balanced -> to get median
val mid : Int= sortedBalances.size / 2
val medianBalance = if (calls.size % 2 ==0) (sortedBalances(mid)+sortedBalances(mid+1)) /2 else sortedBalances(mid)