Fast & Functional (Scala Matsuri, JP)

@miciek AST & UNCTIONAL F F Room A, 14:00 In
this talk we are going to create a functional and blazingly fast microservice in Scala. We will use f u n c t i o n a l p r o g r a m m i n g abstractions to quickly mix & match different HTTP libraries, state implementations and concurrency configurations. Each step will be followed by a performance analysis using different tools from JVM toolbox.

@miciek λ Michał Płachta www.michalplachta.com @miciek AST & UNCTIONAL F
F

@miciek Hello, I’d like to hear a functional programming joke
関数型プログラミングの冗談を聴いたことがある

@miciek OK. Why did the chicken cross the road? functional
programming joke どうしてニワトリは道路路を渡るの？

@miciek cross the road? I don’t know. Why? 分かりません。どうしてでしょう?

@miciek It’s very simple really. I don’t know. Why? それは本当にとても簡単です。

@miciek The best way to understand it comes from the
idea of contravariant functor. It’s very simple really. 理理解するための最良の⽅方法は、反変ファンクターの考えから来ています。

@miciek As you probably know, a functor is just a
mapping between categories that respects the category structure; a homomorphism, if you will. contravariant functor. ファンクターは圏の構造を保った写像で、準同型写像とも⾔言われます

@miciek Now, some constructions that we want to express look
like functors but in some sense “turn morphisms around”. We call these contravariant functors. will. さて、私たちが表現したいいくつかの構造はファンクタのように⾒見見えますが、ある意味では「変形を逆転させる」のです。私たちはこれらの反変ファンクタと呼びます。

@miciek As you have probably noticed, we can indeed define
a contravariant functor as simply a covariant functor on opposite categories, invoking the obvious correspondence. Of course you have already noticed the obvious connection this has with the category theoretic generalization of topological presheaves — a presheaf on a topology is just a contravariant functor from the… 私たちは反変ファンクターを単に逆圏の共変ファンクターとして定義しなおすことができます。もちろん、これが圏論的なトポロジカルなプリシーフの⼀一般化に関連していることにすでにお分かりですね (以下延々

@miciek 私は Haskell の冗談を聞きたいです。

@miciek AST & UNCTIONAL F F

@miciek UNCTIONAL F very modular plug & play using functional
mechanics quickly replacing modules without affecting the logic simple real-world service in Scala モジュール性、プラグアンドプレイ

@miciek F 1st meaning: PERFORMANCE AST Fast の第⼀一義は、実⾏行行速度

@miciek F 2nd meaning: DEV SPEED AST very modular plug
& play Fast の第⼆二義は、開発速度

@miciek In this talk… AST & UNCTIONAL F F modularity
(the λ way!) plug & play simple real-world service in Scala

@miciek Influencer Stats インフルエンサーの統計情報

@miciek We need a marketing strategy for our product! Marketing
マーケティング

@miciek Remember when… Old Ways Don’t Work …people watched TV
みんながテレビを⾒見見ていた時代の古いやり⽅方は通⽤用しない

@miciek Influencers 22 237 likes 2302 likes, 70 retweets 201
232 views, 23987 likes 502 123 views, 2012 likes …and more 今のインフルエンサー

@miciek Influencers items aggregation 1 201 882 views, 423 987
likes …and more All tweets, youtube videos, etc for one product ⼀一つのプロダクトに関して全てのアイテムを集約

@miciek Influencer Stats service collection of videos how many total
views how many total likes 動画、PV、like 数など

@miciek Requirement #1 Collections ability to add & update Collections
of videos … COLLECTION 1 … COLLECTION 2 要件1: 動画のコレクションを作成、更更新できること

@miciek Requirement #2 Fetch YouTube Stats ability to fetch individual
video stats through YouTube API YouTube API 20 views, 2 likes 要件2: 個々の動画に関して統計を取得できること

@miciek Requirement #3 Calculate Stats ability to calculate & return
Collection statistics … 1 201 882 views, 423 987 likes 要件3: コレクション全体の統計情報を集計できること

@miciek Non-functional requirements ✓HTTP Web Server ✓HTTP Client ✓Collection Storage
✓Logging ⾮非機能要件

@miciek PURE Side-effect’y f input value output value f input
value hard to keep separate hard to test easy to keep separate easy to test 副作⽤用はテストしづらい

@miciek PURE ✓Save & Load Collections ✓Fetch YouTube Stats ✓HTTP
Web Server ✓HTTP Client ✓Collection storage ✓Logging Side-effect’y ✓Calculate Stats f video #1 stats video #2 stats aggregated stats とは⾔言っても機能の多くは副作⽤用を伴う

@miciek PURE ✓Save & Load Collections ✓Fetch YouTube Stats ✓HTTP
Web Server ✓HTTP Client ✓Collection storage ✓Logging Side-effect’y ✓Calculate Stats ULTIMATE GOAL move as much as we can to the PURE side できる限り多くの機能を pure 側へと移⾏行行させる

@miciek ULTIMATE GOAL move as much as we can to
the PURE side できる限り多くの機能を pure 側へと移⾏行行させる

@miciek ULTIMATE GOAL move as much as we can to
the PURE side to test in isolation to reason in isolation to easily swap components (because they are isolated) 隔離された単体でテストしたり、論理理的に振る舞いを分析したり、コンポーネントを差し替えるのが容易易な状態になるのが究極の⽬目標

@miciek What happens next… intro code Java code performance tests
t we are here

@miciek Modular programming using algebras 代数を利利⽤用したモジュラープログラミング

@miciek Model e.g. -a YouTube video -instagram post -tweet Model
の実装を考える

@miciek Pure logic f video #1 stats video #2 stats
aggregated stats 純粋なロジック

@miciek Pure logic

@miciek Pure logic … 1 201 882 views, 423 987
likes easy to test easy to reason about PURE WIN!

@miciek Can it be as easy as this? f input
value output value NOPE では次のような関数は？

@miciek Can it be as easy as this? 1. get
collection collectionId 2. get videoIds from it 3. for each videoId, call YouTube API 4.call our pure calculate function (and log some things in between) f input value output value f input value output value いくつか問題があります。

@miciek Can it be as easy as this? 1. get
collection collectionId 2. get videoIds from it 3. for each videoId, call YouTube API 4. call our calculate function NOPE because side effects 副作⽤用があるからです。

@miciek Side-effect’y stuff

@miciek Side-effect’y stuff 1. get collection collectionId 2. get videoIds
from it 3. for each videoId, call YouTube API 4. call our pure calculate function

@miciek Specific effect type 特定の作⽤用を表す型が使われています。

@miciek Too powerful effect type :( 作⽤用型が強すぎます。

@miciek Side-effect’y stuff 1. get collection collectionId 2. get videoIds
from it 3. for each videoId, call YouTube API 4. call our pure calculate function F doesn’t do anything F is chosen by the user モナドの F とだけ弱く指定します。

@miciek synchronous asynchronous IO effect type F[_]

@miciek Constrained? A doesn’t do anything A is chosen by
the user

@miciek We can’t constrain ourselves What we have What we
want F doesn’t do anything F is chosen by the user 制限を後付けすることはできません。

@miciek Constraints Liberate F doesn’t do anything F is chosen
by the user Constraints Liberate Liberties Constrain 制限は解放し、⾃自由は制限する

@miciek Get collection collectionId

@miciek Get collection collectionId just an algebra

@miciek Get videoIds from it

@miciek For each videoId call YouTube API

@miciek Call our pure calculate function

@miciek (and log some things in between)

@miciek Signature is enough

@miciek

@miciek PURE ✓Collections interpreter ✓HTTP Web Server ✓HTTP Client interpreter
✓Collection storage interpreter ✓Logging interpreter Side-effect’y ✓Calculate Stats ✓Collections algebra ✓HTTP Client algebra ✓Logging algebra ✓getStats algorithm on F

@miciek algebras ✓Collections interpreter ✓HTTP Client interpreter ✓Collection storage interpreter
✓Logging interpreter interpreters ✓Collections algebra ✓HTTP Client algebra ✓Logging algebra 代数 | インタプリタ

@miciek algebra interpreter

@miciek What happens next… intro code Java code performance tests
t we are here

@miciek algebra interpreters - AkkaHttp - Hammock (Apache) - Http4s
- InMem LinkedList - InMem TrieMap - Log All - Max 1k/sec (dropping rest) plug & play 代数 | インタプリタ

@miciek Make it fast ⾼高速化

@miciek @miciek Warning Do not perform any of the following
stunts on PRODUCTION. 注意! プロダクションで⾏行行ってはいけません

@miciek wrk -t1 -c16 -d30s --latency URL We will use
wrk 1 thread 16 connections 30 sec duration ベンチマークツール: wrk

@miciek We will use async-profiler jps cd async-profiler ./profiler.sh -d
10 -f <FILE> <PID> https://github.com/jvm-profiling-tools/async-profiler プロファイラ: async-profiler

@miciek We will use flame graphs http://www.brendangregg.com/flamegraphs.html read from bottom

@miciek Version 1 # requests 99% latency avg latency req/s
Version 1 ? ?ms ?ms ? -akka-http (client + server) -log all things -in mem linked list state

@miciek Version 1 Results # requests 99% latency avg latency
req/s Version 1 8510 82.41ms 56.47ms 283.12

@miciek Version 1 Flame Graph

@miciek -don’t change the logic -just change the Logger interpreter
-dropping logs if the rate is > 1k per second Version 2: Dropping logs

req/s Version 1 8510 82.41ms 56.47ms 283.12 Version 2 89 757 62.53ms 6.94ms 2986.26 DroppingLogger

@miciek -don’t change the logic -change the VideoClient type class
instance Version 3: Change the Video Client クライアントを代えてみる

req/s Version 1 8510 82.41ms 56.47ms 283.12 Version 2 89 757 62.53ms 6.94ms 2986.26 Version 3 96 564 13.05ms 5.06ms 3218.48 DroppingLogger Hammock (Apache)

@miciek -don’t change the logic -cache results and call logic
in separate thread Version 4: Statistics Caching

req/s Version 1 8510 82.41ms 56.47ms 283.12 Version 2 89 757 62.53ms 6.94ms 2986.26 Version 3 96 564 13.05ms 5.06ms 3218.48 Version 4 933 303 62.86ms 2.87ms 31 081.82 DroppingLogger Hammock (Apache) Stats Caching

@miciek -don’t change the logic -change the underlying server from
Akka HTTP to Http4s Version 5: Change the Server サーバーを代えてみる

req/s Version 1 8510 82.41ms 56.47ms 283.12 Version 2 89 757 62.53ms 6.94ms 2986.26 Version 3 96 564 13.05ms 5.06ms 3218.48 Version 4 933 303 62.86ms 2.87ms 31 081.82 Version 5 1 158 664 9.05ms 555.80µs 38 596.24 DroppingLogger Hammock (Apache) Stats Caching Http4s Server

@miciek Inventions That Already Exist 既にあるものを発明する

@miciek Introducing…

@miciek

@miciek Introducing… Cheaper taxi that drives on fixed routes! 固定ルートの格安タクシーがあったら...

@miciek This is a BUS. You invented a BUS. Cheaper
taxi that drives on fixed routes! それはバスです。あなたはバスを発⾒見見したのです。

@miciek Introducing… Algebras & Interpreters

@miciek Algebras & Interpreters This is an INTERFACE. You invented
an INTERFACE.

@miciek Scala FP

@miciek Java

@miciek Interfaces

@miciek Interfaces difference: we need to choose the effect type

@miciek Return type difference: we need to choose the effect
type which is very powerful

@miciek Algebras

@miciek Constrained effect type

@miciek Dependencies

@miciek Algebras & Interpreters Not an INTERFACE. major difference: we
can abstract over the effect type and constrain ourselves using F instead of CompletableFuture…

@miciek Conclusions 結論

@miciek -changed infrastructure details -…but our core logic (and tests)
didn’t need to change! What have we done? plug & play quickly replacing non-core-logic modules インフラの詳細を変えましたが、コアロジックは変えていません!

@miciek Modularity / Separation of concerns if we can.. replace
the server implementation replace the state implementation replace the logging implementation replace the video client implementation add caching without changing the core logic (& tests) PURE WIN! コアロジックを変えることなく実装の差し替えに成功しました

@miciek PURE ✓Collections interpreter ✓HTTP Web Server ✓HTTP Client interpreter
✓Collection storage interpreter ✓Logging interpreter Side-effect’y ✓Calculate Stats ✓Collections algebra ✓HTTP Client algebra ✓Logging algebra ✓getStats algorithm on F unit-tested integration-tested very constrained just F[_] no constraints Future, IO, …

@miciek Interpreters integration test https://www.testcontainers.org/

@miciek Interpreters integration test interpreter response https://www.testcontainers.org/

@miciek You learned… AST & UNCTIONAL F F modularity (the
λ way!) plug & play simple real-world service in Scala モジュール性とプラグアンドプレイ

@miciek Learn More https://github.com/miciek/influencer-stats

@miciek λ Michał Płachta www.michalplachta.com @miciek AST & UNCTIONAL F
F Thanks!

Fast & Functional (Scala Matsuri, JP)

Fast & Functional (Scala Matsuri, JP)

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