jrudolph

import java.math.BigInteger
import java.net.DatagramPacket
import java.net.DatagramSocket
import java.net.InetAddress
import java.security.KeyPairGenerator
import java.security.MessageDigest
import java.security.SecureRandom
import java.security.interfaces.ECPrivateKey
import java.security.interfaces.ECPublicKey
import java.security.spec.ECPoint

jrudolph

package akka.sbt.jmh.completion

import java.io.FileInputStream
import java.util.Collections

import pl.project13.scala.sbt.SbtJmh.JmhKeys.Jmh
import sbt._
import Keys._
import org.openjdk.jmh.runner.BenchmarkList
import org.openjdk.jmh.runner.BenchmarkListEntry

jrudolph

# use persofoto.de to crop a foto to the right dimensions

# then use this script to lay it out on a 1600x2312 jpg to print as 9x13
montage mein-passfoto.jpg mein-passfoto.jpg mein-passfoto.jpg mein-passfoto.jpg -geometry 622x898+89+129 out.jpg

jrudolph

import java.util.concurrent.ThreadLocalRandom
import javax.sound.sampled._

// Program to generate THX Deep Note sound according to the sheet music
// published to celebrate its 35th birthday
// https://twitter.com/THX/status/1000077588415447040
object THX extends App {
  val sampleRate = 44100f
  val af = new AudioFormat(
        sampleRate,

jrudolph

In general, performance differences are usually negligible as long as they don't turn up during benchmarking (you probably know what people say about premature optimization...).

So, it's mostly a matter of style. Writing a GraphStage is the lowest level you can implement something in akka-stream. It's very explicit and somewhat predictable what happens but the amount of code to write can be quite cumbersome and with a growing number of ports, managing the state space and all the possible interactions can be quite a challenge.

Wiring up predefined combinators using the GraphDSL is therefore often recommended. In the best case it's just "plug and play". On the other hand, it also introduces new degrees of freedom and non-determinism as elements flow

jrudolph

/*
 * Copyright (C) 2009-2017 Lightbend Inc. <http://www.lightbend.com>
 */

import sbt._
import Keys._

package sbt {
  object Access {
    def compilerReporter = sbt.Keys.compilerReporter

jrudolph

TargetVersion: Scala 2.13 LastVersion: Scala 2.12

jrudolph

import java.io.File

import scala.io.Source

object StackDumpAnalyzer extends App {
  val ThreadLine = """"([^"]+)" #(\d+) prio=(\d+) os_prio=(\d+) tid=0x([0-9a-f]+) nid=0x([0-9a-f]+) (.*)""".r

  val file = "ThreadDump.txt"

  case class ThreadState(name: String, id: Int, prio: Int, osPrio: Int, tid: Long, nid: Int, state: String)

jrudolph

/* sbt -- Simple Build Tool
 * Copyright 2011 Mark Harrah, Eugene Yokota
 */
package sbt
package myinspect

import java.io.File

import Def.{ScopedKey, compiled, flattenLocals}

jrudolph

Intel(R) Core(TM) i7-3840QM CPU @ 2.80GHz
Turbo off

Linux 64bit

jmh:run -i 4 -wi 4 -f 1 -p throughPut=1 -p dispatcher=affinity-dispatcher,default-fj-dispatcher   .*AffinityPoolReq.*

[info] Benchmark                                                            (dispatcher)                           (mailbox)  (throughPut)   Mode  Cnt        Score         Error  Units
[info] AffinityPoolRequestResponseBenchmark.queryUserServiceActor    affinity-dispatcher  SingleConsumerOnlyUnboundedMailbox             1  thrpt    4  3634030.863 ± 3728431.081  ops/s
[info] AffinityPoolRequestResponseBenchmark.queryUserServiceActor  default-fj-dispatcher  SingleConsumerOnlyUnboundedMailbox             1  thrpt    4  4031047.752 ± 1552394.546  ops/s