guizmaii

import java.util.concurrent._
import akka.dispatch.{Dispatcher, ExecutorServiceDelegate}
import config.Config
import helpers.ScalaLogger

class ExecutionContextMonitor()(implicit metricsService: MetricsClient, config: Config) {
  private val log = ScalaLogger.get(this.getClass)

  private val scheduler = Executors.newSingleThreadScheduledExecutor()

guizmaii

#!/bin/sh

# Use AWS CLI to get the most recent version of an AMI that 
# matches certain criteria. Has obvious uses. Made possible via
# --query, --output text, and the fact that RFC3339 datetime
# fields are easily sortable.

export AWS_DEFAULT_REGION=us-east-1

aws ec2 describe-images \

guizmaii

#!/bin/sh

# Use AWS CLI to get the most recent version of an AMI that 
# matches certain criteria. Has obvious uses. Made possible via
# --query, --output text, and the fact that RFC3339 datetime
# fields are easily sortable.

export AWS_DEFAULT_REGION=us-east-1

aws ec2 describe-images \

guizmaii

class Integer
  N_BYTES = [42].pack('i').size
  N_BITS = N_BYTES * 16
  MAX = 2 ** (N_BITS - 2) - 1
  MIN = -MAX - 1
end

p Integer::MAX              #=> 4611686018427387903
p Integer::MAX.class        #=> Fixnum
p (Integer::MAX + 1).class  #=> Bignum

guizmaii

Latency Comparison Numbers
--------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

guizmaii

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

guizmaii

import cats.data.NonEmptyList
import cats.Eq

import scala.collection.GenTraversableOnce

sealed trait NonEmptySet[T] extends (T => Boolean) {
  def head: T
  def set: Set[T]
  def +(t: T): NonEmptySet[T]
  def ++(ts: NonEmptySet[T]): NonEmptySet[T]

guizmaii

import cats.data.NonEmptyList
import cats.Eq

import scala.collection.GenTraversableOnce

sealed trait NonEmptySet[T] extends (T => Boolean) {
  def head: T
  def set: Set[T]
  def +(t: T): NonEmptySet[T]
  def ++(ts: NonEmptySet[T]): NonEmptySet[T]

guizmaii

@ import $ivy.`org.typelevel::cats-effect:0.10.1` 

@ import cats._, cats.data._, cats.implicits._, cats.effect._

@ def lift(i: Int): IO[Int] = Timer[IO].sleep(1.second) >> IO { 
  
     println(Thread.currentThread.getName + "At time = " + java.time.Instant.now)
     i
  } 

guizmaii

@ import $ivy.`org.typelevel::cats-effect:0.10.1` 

@ import cats._, cats.data._, cats.implicits._, cats.effect._, scala.concurrent.duration._, import scala.concurrent.ExecutionContext.Implicits.global

@ def lift(i: Int): IO[Int] = Timer[IO].sleep(1.second) >> IO { 
  
     println(Thread.currentThread.getName + "At time = " + java.time.Instant.now)
     i
  }