calvinlfer

Quick Tips for Fast Code on the JVM

I was talking to a coworker recently about general techniques that almost always form the core of any effort to write very fast, down-to-the-metal hot path code on the JVM, and they pointed out that there really isn't a particularly good place to go for this information. It occurred to me that, really, I had more or less picked up all of it by word of mouth and experience, and there just aren't any good reference sources on the topic. So… here's my word of mouth.

This is by no means a comprehensive gist. It's also important to understand that the techniques that I outline in here are not 100% absolute either. Performance on the JVM is an incredibly complicated subject, and while there are rules that almost always hold true, the "almost" remains very salient. Also, for many or even most applications, there will be other techniques that I'm not mentioning which will have a greater impact. JMH, Java Flight Recorder, and a good profiler are your very best friend! Mea

calvinlfer

val (recycleQueue, recycleSource) =
  Source
    .queue[SoilStateReading](100, OverflowStrategy.dropTail)
    .prefixAndTail(0)
    .map(_._2)
    .toMat(Sink.head)(Keep.both)
    .run()
StreamConverters.fromInputStream(() => this.getClass.getClassLoader.getResourceAsStream("sensors.log"))
  .via(SoilStateReading.csvParser)
  .merge(Source.fromFutureSource(recycleSource))

calvinlfer

import akka.actor.ActorSystem
import akka.stream._
import akka.stream.scaladsl._

import scala.io.StdIn
import scala.util.Random

object SimplePartitionSample extends App {

  implicit val system = ActorSystem()

calvinlfer

Thread Pools

Thread pools on the JVM should usually be divided into the following three categories:

1. CPU-bound
2. Blocking IO
3. Non-blocking IO polling

Each of these categories has a different optimal configuration and usage pattern.

calvinlfer

package sample.eventdriven.scala

import akka.actor.{Actor, ActorRef, ActorSystem, Inbox, Props}
import akka.persistence.PersistentActor

import scala.concurrent.ExecutionContext.Implicits._
import scala.concurrent.duration._

// ===============================================================
// Demo of an Event-driven Architecture in Akka and Scala.

calvinlfer

// Setup 
val rejectionHandler = RejectionHandler.default
val logDuration = extractRequestContext.flatMap { ctx =>
  val start = System.currentTimeMillis()
  // handling rejections here so that we get proper status codes
  mapResponse { resp =>
    val d = System.currentTimeMillis() - start
    logger.info(s"[${resp.status.intValue()}] ${ctx.request.method.name} ${ctx.request.uri} took: ${d}ms")
    resp
  } & handleRejections(rejectionHandler)