The document discusses building a serverless architecture in Scala using AWS Lambda. It covers serverless architecture concepts, Function as a Service (FaaS) using AWS Lambda, API Gateway, and Kinesis Streams. It then discusses developing and deploying Scala code to AWS Lambda using SBT plugins and templates, and implementing domain-driven design principles with Hexagonal architecture in a multi-module project structure.
El Barroco fue un período de la historia de la arquitectura entre los años 1600 y 1780 que siguió al Renacimiento y al Manierismo. Se originó en Roma a partir de las formas renacentistas pero luego se diversificó en varios estilos paralelos. Algunas características arquitectónicas del Barroco incluyen sensación de movimiento en las formas, uso de torres, cúpulas y ventanas abundantes, y columnas a veces solo decorativas. Obras importantes fueron la Iglesia del Gesù en Roma y la
The document discusses building a serverless architecture in Scala using AWS Lambda. It covers serverless architecture concepts, Function as a Service (FaaS) using AWS Lambda, API Gateway, and Kinesis Streams. It then discusses developing and deploying Scala code to AWS Lambda using SBT plugins and templates, and implementing domain-driven design principles with Hexagonal architecture in a multi-module project structure.
El Barroco fue un período de la historia de la arquitectura entre los años 1600 y 1780 que siguió al Renacimiento y al Manierismo. Se originó en Roma a partir de las formas renacentistas pero luego se diversificó en varios estilos paralelos. Algunas características arquitectónicas del Barroco incluyen sensación de movimiento en las formas, uso de torres, cúpulas y ventanas abundantes, y columnas a veces solo decorativas. Obras importantes fueron la Iglesia del Gesù en Roma y la
- The document discusses how Scala code is compiled to Java Virtual Machine (JVM) bytecodes. It begins with an introduction to Koichi Sakata, the presenter, and an overview that the session will look at JVM bytecodes for beginners.
- The presentation then asks if attendees know what happens when Scala code is compiled. It is explained that Scala code, like code from other JVM languages, is compiled to class files that contain JVM bytecodes.
- An example Java class file is opened in a binary editor to show the JVM bytecode format. It is explained that class files have a defined format with elements like magic number, version, and bytecode instructions.
Scala Refactoring for Fun and Profit (Japanese subtitles)Tomer Gabel
A talk given at Scala Matsuri 2016 in Tokyo, Japan.
New Scala practitioners often experience the uncomfortable feeling of "not quite getting it." If you've studied the syntax and written tests, maybe production code; if you're becoming comfortable with the language and libraries, but keep worrying that there's "a better way", or that your code isn't "idiomatic enough" - this session is for you.
By refactoring a real, live codebase, this talk will provide you with new tools and increased confidence. Between the provided examples and the ensuing discussion, you will walk away with a better feel for Scala and how to employ it in the real world.
Functional Programming For All - Scala Matsuri 2016Zachary Abbott
This document discusses functional programming concepts including:
- Functional programming uses functions as the main abstraction and restricts side effects.
- Pure functions have no side effects and depend only on their arguments. This enables referential transparency.
- Referential transparency allows expressions to be replaced with their values without changing program behavior.
- The document provides an example of refactoring an impure Scala function to separate pure and impure parts for testability.
Akka Cluster allows distributing actors across multiple JVMs with no single point of failure. The document discusses challenges faced with unreachable members and journal lifecycles when operating an Akka Cluster application at scale for 10 months. For unreachables, triggering a scale-in to mark nodes as down and automating restarts addressed the issue. Journals stored in Redis required cleanup to avoid inconsistencies, as deleting messages did not remove the highest sequence number. Straying from event sourcing's complete event history model weakened ecosystem support.
Zipkin is a distributed tracing system created by Twitter that allows services to record and query traces of requests across microservices. It uses HTTP headers to propagate trace data between services and stores trace data in storage backends like Cassandra, MySQL, or Elasticsearch. The Brave library can be used to instrument Java applications to send trace data to a Zipkin server.
Going bananas with recursion schemes for fixed point data typesPawel Szulc
The document discusses recursion schemes for processing recursive data types in functional programming. It introduces common recursively defined types like lists and binary trees, and mentions applications that involve recursive structures like file systems and databases. It then presents an example of representing mathematical expressions as recursively defined data types and using recursion schemes to evaluate, optimize, and convert expressions to strings.
About Plone Conference Tokyo 2018 Frontend DayKazuhiro Hara
The document announces an upcoming Plone conference in Tokyo from November 5-11, 2018. It will include a related Frontend Day event focused on user interface technologies, design, and smartphone/IoT applications. Frontend Day especially welcomes foreign participants and is looking for speakers to give 20 minute presentations in English. The author is challenging himself to organize and speak at the international conference, being his first presentation in English.
This document provides instructions for creating a desktop application using the descjop template for Clojure projects. It describes downloading Electron, initializing a new project, building the project for development and production, and packaging the application. The template supports Om and Reagent frameworks and runs on macOS, Windows, and Linux. It allows adding basic menus and shortcuts and outlines future goals like supporting main process figwheel and UI frameworks.
5. Play Logプラグイン(架空)のフォルダ構成
➡ app プラグインアプリケーション
• model
- log
➡ sbt-plugin-1 プラグインコンソール
• src
- main
scala
➡ sbt-plugin-2
➡ project
• Build.scala
5
6. デフォルトのPlayのBuild.scala
val
main
=
PlayProject(appName,
appVersion,
appDependencies,
mainLang
=
SCALA).settings(
//
Add
your
own
project
settings
here
)
➡ これを、こんな風にするだけ。
6
7. デフォルトのBuild.scalaを変更
val
main
=
PlayProject(appName,
appVersion,
appDependencies,
mainLang
=
SCALA).settings(
//
Add
your
own
project
settings
here
).aggregate(sbtプラグイン1,
sbtプラグイン2)
➡ あとは、それぞれのプラグイン情報を書くだけ
lazy
val
sbtプラグイン1
=
Project(
プロジェクト名,
ソースフォルダの場所,
各種設定
)
7
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