Scala mutable map is in average 63% worst than java HashMap, and 42% worst in median

MapBenchmark.scala

import java.util.ArrayList
import java.util.HashMap
import scala.collection.JavaConverters.asScalaBufferConverter
import scala.collection.mutable.{Map => MapMutable}

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

    val hm = new HashMap[String, String]()
    hm.put("teste1", "ok1")
    hm.put("teste2", "ok2")

    val mm = MapMutable[String, String]()
    mm.put("teste1", "ok1")
    mm.put("teste2", "ok2")

    val series = 1000

    val timesHashmap = new ArrayList[Long](series)
    val timesMutable = new ArrayList[Long](series)

    val times = 1000000

    0.to(series).foreach { i =>
      if (i % 100 == 0) println(i)
      timesHashmap.add(timeit(() => many(times, (_) => hm.get("teste2"))))
      timesMutable.add(timeit(() => many(times, (_) => mm.get("teste2"))))
    }

    println("hashmap mean=", mean(timesHashmap), "p50=", px(timesHashmap, 50), "p99=", px(timesHashmap, 99))
    println("mutable mean=", mean(timesMutable), "p50=", px(timesMutable, 50), "p99=", px(timesMutable, 99))
  }

  def mean(m: ArrayList[Long]): Double = {
    val n = m.asScala.toList
    n.sum / n.size.toFloat
  }

  def px(m: ArrayList[Long], x: Int): Double = {
    val n = m.asScala.toList
    val p = (n.size / 100.0 * x).toInt
    n.sortBy(a => a).apply(p)
  }

  def timeit(f: Function0[Unit]): Long = {
    val before = System.currentTimeMillis()
    f()
    System.currentTimeMillis() - before
  }

  def many(times: Int, f: Function1[Int, Unit]): Unit = {
    0.to(times).foreach(f)
  }

  def getHashMap(key: String, map: HashMap[String, String]): Unit = {
    map.get(key)
  }
}