Java Mission Control(jmc) adaptation for Scala profiling


I use Java Mission Control, jmc github pretty often and it’s really cool tool for analyzing and profiling JVM apps. I’m using it even for Scala projects, but reading Java stack-traces for Scala and mapping them back to original Scala code slows you down. Here is pretty simple Scala code (Example.scala):

import scala.util.Random
import scala.math

object Example {
	val MaxRandomNumber: Int = 1000000

	def main(args: Array[String]): Unit = {
		val rnd = new Random()
		val nums = Array.fill[Int](5*1024*1024)(rnd.nextInt(MaxRandomNumber))

		val mapped = { x =>
		val odds = nums.filter(x => x % 2 == 1)
		val collected = nums.collect { case x if x % 2 == 0 =>
			Math.pow(x, 0.3)

		println(s"mapped size: ${mapped.size}")
		println(s"odds size: ${odds.size}")
		println(s"collected size: ${collected.size}")

Compile via: scalac Example.scala
Run via: scala Example -J-XX:+UnlockCommercialFeatures -J-XX:+FlightRecorder -J-XX:FlightRecorderOptions=defaultrecording=true,disk=true,maxage=10h,dumponexit=true,loglevel=info
And here is how its stack-trace looks. It takes sometime to map back Java stack-trace to actual Scala code:

Does it make sense to make jmc aware of Scala? Does community uses it?



It may be helpful to distinguish frames by line number: