Scala, Akka & Software Tradeoffs Explored

Konrad `@ktosopl` Malawski @ Scalapeno 2016
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The things we don’t see
Exploring the unseen worlds of the Scala,
Akka and Software in general

Konrad `@ktosopl` Malawski @ Scalapeno 2016
The things we don’t see
Exploring the unseen worlds of the Scala,
Akka and Software in general

Konrad `@ktosopl` Malawski
akka.io
typesafe.com
geecon.org
Java.pl / KrakowScala.pl
sckrk.com / meetup.com/Paper-Cup @ London
GDGKrakow.pl
lambdakrk.pl

“The things we don’t see”
What it means (at least for me, and in this talk)
… in Software in general
… in Scala (programming languages)
… in Akka (concurrency, distributed systems)

The things we don’t see…
in Software

A world of tradeoffs
Reality
At the core of it…
This talk is about trade-offs.

Measure
What we can’t measure, we can’t improve.
And often: simply don’t improve at all.

Measure
What we can’t measure, we can’t improve.
And often: simply don’t improve at all.
“ArrayDeque surely will be faster here!”
Wha..! Turns out it isn’t, let’s see why…

Measure, to gain understanding of your system
OMG! I changed all the settings to “more”!
And it’s not improving…!

Measure, to gain understanding of your system
OMG! I changed all the settings to “more”!
And it’s not improving…!
Hmm… weird.
Where do you see the bottleneck?

Measure, and don’t be that guy
OMG!
That lib is 1000x better in serving a file!!!
I’ll use kernel bypass networking for my blog!
Have & understand actual performance requirements,
don’t invent them based on high frequency trading* talks :-)
* I’m assuming here that’s not your business, if it is – carry on.

The things we don’t see…
in Scala

A thing about nulls
"I call it my billion-dollar mistake." 
Sir C.A. R. Hoare, on his invention of the null reference

A thing about nulls
something.calculateSum(2, 2)
What does this code do?

A thing about nulls
something.calculateSum(2, 2)
What does this code do?
a) return 4
b) NullPointerException!
c) System.exit(0) // though I have a love-hate relationship with this answer…

The curious case of Options
Scala Option – 2007 (Scala 2.5, sic! http://www.scala-lang.org/old/node/165)
Guava Optional – 2011 (since v10.0)
Java Optional – 2014 (since v1.8)

sealed abstract class Option[+A]
extends Product with Serializable { self =>
def isEmpty: Boolean
def isDefined: Boolean = !isEmpty
def get: A
@inline final def getOrElse[B >: A](default: => B): B =
if (isEmpty) default else this.get

sealed abstract class Option[+A]
extends Product with Serializable { self =>
def isEmpty: Boolean
def isDefined: Boolean = !isEmpty
def get: A
@inline final def getOrElse[B >: A](default: => B): B =
if (isEmpty) default else this.get
public final class Optional<T> {
 
public boolean isPresent() {
return value != null;
}
 
public T get() {
if (value == null)
throw new NoSuchElementException("No value present");
return value;
}
public T orElseGet(Supplier<? extends T> other) {
return value != null ? value : other.get();
}

val o: Option[String] = ???
o.foreach(_.toUpperCase(Locale.ROOT)) // ok, sure
o match {
case Some(value) => value.toUpperCase(Locale.ROOT)
case None => "_"
}
We all have the same “mistake”:
get seems innocent, but it’s not…
final Optional<String> optional = Optional.of("");
optional.map(it -> it.toUpperCase(Locale.ROOT));
if (optional.isPresent()) {
optional.get().toUpperCase();
}

Can we do better than that though?
“What the eyes don’t see,
the programmer does not invoke.”

Blocking is the new “you broke the build!”

// BAD! (due to the blocking in Future):
implicit val defaultDispatcher = system.dispatcher
val routes: Route = post {
complete {
Future { // uses defaultDispatcher
Thread.sleep(5000) // will block on the default dispatcher,
System.currentTimeMillis().toString // starving the routing infra
}
}
}

// BAD! (due to the blocking in Future):
implicit val defaultDispatcher = system.dispatcher
val routes: Route = post {
complete {
Future { // uses defaultDispatcher
Thread.sleep(5000) // will block on the default dispatcher,
System.currentTimeMillis().toString // starving the routing infra
}
}
}
http://stackoverﬂow.com/questions/34641861/akka-http-blocking-in-a-future-blocks-the-server/34645097#34645097

The curious case of Futures
public class CompletableFuture<T> implements Future<T>, CompletionStage<T> {
public T get() throws InterruptedException, ExecutionException {
// ...
}
public T get(long timeout, TimeUnit unit)
throws InterruptedException, ExecutionException, TimeoutException {
// ...
}

Anyone remember the days before
scala.concurrent.Future?
Back to the Future, in which we discuss Akka and Twitter Futures in 2012 :-)
https://groups.google.com/forum/?fromgroups=#!topic/akka-user/eXiBV5V7ZzE%5B1-25%5D

// ...
}
// ...
}
trait Future[+T] extends Awaitable[T] {
// THERE IS NO GET!
// Closest thing to it is...
def value: Option[Try[T]]
// However it’s not that widely known actually
// Notice that it is non-blocking!

// ...
}
// ...
}
trait Future[+T] extends Awaitable[T] {
// THERE IS NO GET!
// Closest thing to it is...
def value: Option[Try[T]]
// However it’s not that widely known actually
// Notice that it is non-blocking!
object Await {
@throws(classOf[TimeoutException])
@throws(classOf[InterruptedException])
def ready[T](awaitable: Awaitable[T], atMost: Duration): awaitable.type =
blocking(awaitable.ready(atMost)(AwaitPermission))
@throws(classOf[Exception])
def result[T](awaitable: Awaitable[T], atMost: Duration): T =
blocking(awaitable.result(atMost)(AwaitPermission))
}

Java strongly valued ﬁtting-in with existing types.
This forced exposing the get() method.
Scala had a clean-slate, could keep out of sight methods
we don’t want devs to call as they’re dangerous.
“If you don’t see a way at ﬁrst sight…
maybe it was hidden on purpose?”

Hidden scaladoc features
Akka HTTP 2.4.2
we didn’t know about the
hidden feature as well actually :-)

Akka HTTP 2.4.4
Started using the scaladoc
@group feature.

Akka HTTP 2.4.4
Started using the scaladoc
@group feature.
/**
* @groupname basic Basic directives
* @groupprio basic 10
*/
trait BasicDirectives {
/**
* @group basic
*/
def mapInnerRoute(f: Route Route): Directive0 =
Directive { inner f(inner(())) }
/**
* @group basic
*/
def mapRequestContext(f: RequestContext RequestContext): Directive0 =
mapInnerRoute { inner ctx inner(f(ctx)) }
// unlocked by:
scala -groups

Trait representation, in Scala 2.11
trait T { def foo = "bar!" }
class A extends T
class B extends T with SomethingElse

./target/scala-2.11/classes/scalapeno/Example$class.class
./target/scala-2.11/classes/scalapeno/Example.class
$ javap -v ./target/scala-2.11/classes/scalapeno/Example.class
Classfile target/scala-2.11/classes/scalapeno/Example.class
Last modified 25-Apr-2016; size 475 bytes
MD5 checksum fe12967b00411cde03bdc57f0ca6869b
Compiled from "Example.scala"
public interface scalapeno.Example
minor version: 0
major version: 50
flags: ACC_PUBLIC, ACC_INTERFACE, ACC_ABSTRACT
{
public abstract java.lang.String newMethod();
descriptor: ()Ljava/lang/String;
flags: ACC_PUBLIC, ACC_ABSTRACT
}

./target/scala-2.11/classes/scalapeno/Example$class.class
./target/scala-2.11/classes/scalapeno/Example.class
$ javap -v ./target/scala-2.11/classes/scalapeno/Example.class
Classfile target/scala-2.11/classes/scalapeno/Example.class
MD5 checksum fe12967b00411cde03bdc57f0ca6869b
minor version: 0
major version: 50
{
public abstract java.lang.String newMethod();
flags: ACC_PUBLIC, ACC_ABSTRACT
}
$ javap -v ./target/scala-2.11/classes/scalapeno/Example$class.class
Classfile target/scala-2.11/classes/scalapeno/Example$class.class
Last modified 01-May-2016; size 450 bytes
MD5 checksum ea679b7db9d6275dbe9dff53475000c2
public abstract class scalapeno.Example$class
minor version: 0
major version: 50
flags: ACC_PUBLIC, ACC_SUPER, ACC_ABSTRACT
public static java.lang.String newMethod(scalapeno.Example);
descriptor: (Lscalapeno/Example;)Ljava/lang/String;
flags: ACC_PUBLIC, ACC_STATIC
Code:
stack=1, locals=1, args_size=1
0: ldc #9 // String
2: areturn

New trait encoding using default methods
https://github.com/scala/scala/pull/5003

./target/scala-2.12.0-M4/classes/scalapeno/Example.class
$ javap -v ./target/scala-2.12.0-M4/classes/scalapeno/Example.class
Classfile scala-2.12.0-M4/classes/scalapeno/Example.class
MD5 checksum 07bad6e3b9c5d73b1276e5e7af937e29
minor version: 0
major version: 52
{
public java.lang.String newMethod();
flags: ACC_PUBLIC
Code:
stack=1, locals=1, args_size=1
0: ldc #12 // String
2: areturn
LocalVariableTable:
Start Length Slot Name Signature
0 3 0 this Lscalapeno/Example;
LineNumberTable:
line 4: 0

The things we don’t see… in…

The things we don’t see… in ‫ַּכֹו‬‫ע‬?

The things we don’t see in… The Queen of Laponia?!

The things we don’t see… in Akka, the open source project.

Akka Actor in one sentence:
Messaging as a core abstraction, not slap-on afterthought.
Messages! Not method calls.
Akka in one sentence:
A toolkit for building highly distributed and concurrent apps.

http://c2.com/cgi/wiki?AlanKayOnMessaging

Waldo J,Wyant G,Wollrath A, Kendall S.A @ Sun Microsystems Laboratories. 1994.
Note on Distributed Computing

Methods: // locally:
val value: Long = local.calculateSum(2, 2)
// if it’s parallel then we need some middle man to handle concurrency issues hm…
// but remote will have big latency so...
val value: Future[Long] = remote.calculateSum(2, 2)
// Q1: what is actually put on the wire?
// Q2: what about retrying to different host,
// - now need magic to handle it...
// Q3: can the downstream directly respond to upstream?
// - ok, so we could build a special method that does this
// Q4: what if the networking breaks...? Do I need to try/catch?
// ... but why, if it could be a simple message send :-)

Methods: // locally:
val value: Long = local.calculateSum(2, 2)
// if it’s parallel then we need some middle man to handle concurrency issues hm…
// but remote will have big latency so...
val value: Future[Long] = remote.calculateSum(2, 2)
// Q1: what is actually put on the wire?
// Q2: what about retrying to different host,
// - now need magic to handle it...
// Q3: can the downstream directly respond to upstream?
// - ok, so we could build a special method that does this
// Q4: what if the networking breaks...? Do I need to try/catch?
// ... but why, if it could be a simple message send :-)
Messages: // locally:
local ! CalculateSum(2, 2)
// I'll get a reply in a bit, or I can retry etc etc.
// Actor is can be running in parallel, on multi-core etc, same API.
// what can happen?
// JVM can crash => effectively message loss
// remotely
remote ! CalculateSum(2, 2)
// what can happen?
// message loss
// receiver of the msg can crash... => message loss

class OneWayProxyActor extends Actor {
val downstream: ActorRef = ???
def receive = {
case StateQuery(q) =>
sender() ! run(q)
case req: IncomingRequest =>
downstream forward transformed(req)
}
def run(any: Any) = ???
}

What do we not see in these scenarios though?

Local synchronous methods are trivial to trace:
that’s what a StackTrace is.
But the tradeoff is very high: scalability / resilience – all lost.

Local synchronous methods are trivial to trace:
that’s what a StackTrace is.
But the tradeoff is very high: scalability / resilience – all lost.
Tracing async / distributed systems is not quite solved yet…
Dapper / Zipkin are not a new things,
they’re the beginning of a journey – not the complete solution…

I can totally do the same
with REST HTTP calls!

I can totally do the same
with REST HTTP calls!
Sure you can (201, 204), but:
In Akka that’s both default,
and exactly 40bytes cheap.

Encapsulation, so nice…
Messages! Not exposing state.
class ComplexLogic {
def add(i: Item): ComplexLogic
def apply(): Effect
}

But it’s “only for testing”!
getter
class ComplexLogic {
def add(i: Item): ComplexLogic
def apply(): Effect
def state: State
}

val logicActor: ActorRef = ???
// no way to access state - for your own good.
logicActor ! Add(item)
logicActor ! Add(item)
logicActor ! Apply
expectMsgType[StateAppliedSuccessfully]
Test:
yes: behaviour and interactions,
not: raw state.

“I want my words back.”
Roland Kuhn
(former Akka Team lead)

We want our words back…!
Two examples of name-collisions causing confusion:
“Scheduler”
&
“Stream”
Naming is hard…

“Scheduler” - but is it the right one?
class CountdownActor extends Actor {
val untilEndOfWorld = 127.days // according to mayan prophecy
// oh, great, a scheduler!
val scheduler = context.system.scheduler
scheduler.scheduleOnce(untilEndOfWorld, self, EndOfTheWorld)
def receive = { case EndOfTheWorld => println("Aaaaa!!!") }
}
http://doc.akka.io/docs/akka/2.4.4/scala/scheduler.html#scheduler-scala

class CountdownActor extends Actor {
val untilEndOfWorld = 127.days // according to mayan prophecy
// oh, great, a scheduler!
val scheduler = context.system.scheduler
scheduler.scheduleOnce(untilEndOfWorld, self, EndOfTheWorld)
def receive = { case EndOfTheWorld => println("Aaaaa!!!") }
}

Into the akka.actor.dungeon
Technically LARS is not in the dungeon,
but couldn’t stop myself from making this reference…

It’s a plain “Hashed Wheel Timer” though!

Optimised for:
• high performance
• lockless insertion
• O(1) insertion
• huge amounts of tasks 
// timeouts - on each request, ask timeouts
Original white paper: Hashed and Hierarchical Timing Wheels:
https://pdfs.semanticscholar.org/0a14/2c84aeccc16b22c758cb57063fe227e83277.pdf

Optimised for:
• high performance
• lockless insertion
• O(1) insertion
• huge amounts of tasks 
// timeouts - on each request, ask timeouts
Not for:
• preciseness
• persistence
Original white paper: Hashed and Hierarchical Timing Wheels:
https://pdfs.semanticscholar.org/0a14/2c84aeccc16b22c758cb57063fe227e83277.pdf

Akka’s Scheduler fun facts!
• Akka impl. after Netty implementation
• Akka impl. improved performance quite a bit
• Netty pulled-in the optimisations
(just one of multiple (both way) healthy interactions) 
=> Yay, healthy Open Source ecosystem!

Error message you’ll likely never see:
LightArrayRevolverScheduler for short: “LARS”

Error message you’ll likely never see:
LightArrayRevolverScheduler for short: “LARS”
“LARS cannot start new thread,
ship’s going down!”

Persistent, reliable job scheduler
Ok, so what do we need for it?

Persistent, reliable job scheduler: Chronos
Ok, so what do we need?
• Persistence
• Replication
• Consensus on who executes

Optimised for:
• ”Like CRON, but distributed”
• Visibility, including management UI
• Retries of failed tasks
• Far-out tasks (usually measured in days etc)
• Consensus on who executes
• Also considered Lightweight
• 2k lines of Scala
• in it’s context… well, it is!
https://www.youtube.com/watch?v=FLqURrtS8IA

Deﬁnitely NOT for:
• millions of tasks inserted per second
• to be run in the next second
… that’s what the the Akka scheduler is for!

Deﬁnitely NOT for:
• millions of tasks inserted per second
• to be run in the next second
… that’s what the the Akka scheduler is for!
Notable mention: Quartz  
(well known long-term scheduler,
with Akka integration and persistence)

“Stream”
What does it mean?!
* when put in “” the word does not appear in project name, but is present in examples / style of APIs / wording.

Suddenly everyone jumped on the word “Stream”.
Akka Streams / Reactive Streams started end-of-2013.
“Streams”

Suddenly everyone jumped on the word “Stream”.
Akka Streams / Reactive Streams started end-of-2013.
“Streams”
Akka Streams
Reactive Streams
RxJava “streams”*
Spark Streaming
Apache Storm “streams”*
Java Steams (JDK8)
Reactor “streams”*
Kafka Streams
ztellman / Manifold (Clojure)
Apache GearPump “streams”
Apache [I] Streams (!)
Apache [I] Beam “streams”
Apache [I] Quarks “streams”
Apache [I] Airﬂow “streams” (dead?)
Apache [I] Samza
Scala Stream
Scalaz Streams, now known as FS2
Swave.io
Java InputStream / OutputStream / … :-)

A core feature not obvious to the untrained eye…!
Akka Streams / HTTP
Quiz time!
TCP is a ______ protocol?

A core feature not obvious to the untrained eye…!
Akka Streams / HTTP
Quiz time!
TCP is a STREAMING protocol!

Streaming from Akka HTTP
No demand from TCP
=
No demand upstream
=
Source won’t generate tweets

Streaming from Akka HTTP
No demand from TCP
=
No demand upstream
=
Source won’t generate tweets
=>
Bounded memory
stream processing!

Binary Compatibility
A.K.A. “The thing you think you want, but you actually want much more”
Brian Goetz, Java Language Architect, “Stewardship: The sobering parts” 
https://www.youtube.com/watch?v=2y5Pv4yN0b0

Compatibilities intertwined
Scala versioning scheme is:
Epoch.Major.Minor
Technically Java too is 1.6, 1.7, 1.8 by the way.
Akka releases closely track Scala versions.

Serialization Compatibility
=> Akka Persistence, (experimental in 2.3.x)
Experimental version accidentally used
Java Serialization for Scala’s Option.
Akka now released to both Scala: 2.10 and 2.11.
Scala’s Option changed its serialised form slightly.
Akka Persistence is geared towards long-term
storage of events – even if experimental, we did not
want to block anyone from upgrading to 2.11…!

=> Akka Persistence, in this speciﬁc place,
provides Serialization compatibility of raw Scala
where Scala was allowed to break it.
Because we care about you :-)
// If we are allowed to break serialization compatibility of stored snapshots in 2.4
// we can remove this attempt to deserialize SnapshotHeader with JavaSerializer.
// Then the class SnapshotHeader can be removed. See issue #16009
val oldHeader =
if (readShort(in) == 0xedac) { // Java Serialization magic value with swapped bytes
val b = if (SnapshotSerializer.doPatch) patch(headerBytes) else headerBytes
serialization.deserialize(b, classOf[SnapshotHeader]).toOption
} else None

Plenty of work goes completely un-seen,
“if it works as it should, you don’t see it”.
The Scala ecosystem has matured,
that many projects really care and tend those aspects.

“Why don’t we just magically…”
“In terms of magic in Akka…
we prefer to have None of it.”
quoting myself in silly attempt to coin a phrase (-:

“Why don’t we just magically…”

nums.foldingLeft(0)(_ + _)
// Summing up:

A hidden force behind all our successes…
Before we sum up:

A hidden force behind all our successes…
You!
The Scala community as a whole,
thank you!
Before we sum up:

Everything is a tradeoff.
If you can’t see the tradeoff, look again.
Some things…
you don’t need to see,
some things you do.
Pick wisely.
Don’t believe in “oh yeah it’s magic”.
Seek deeper understanding of things.
Keep learning: “Life is Study!”
Summing up

‫רבה‬ ‫!תודה‬
Thanks for listening!
ktoso @ typesafe.com
twitter: ktosopl
github: ktoso
team blog: letitcrash.com
home: akka.io
Thus spake the Master Programmer:
“After three days without programming,
life becomes meaningless.”

Q/A
(Now’s the time to ask things!)
ktoso @ lightbend.com
twitter: ktosopl
github: ktoso
blog: kto.so
home: akka.io

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