Java ラブなヌーラボにおける Scala + Playframework 体験記
Presentation slides at https://jissenscala.doorkeeper.jp/events/19660
Systems Programming at Twitter
Systems Programming at Twitter Facebook, October 30, 2012 Marius Eriksen Twitter Inc. (Press space or enter to navigate to the next slide, left arrow to go backwards.) A history lesson Twitter evolves 2009: Pure Ruby-on-Rails app with MySQL; lots of memcache. Materialized timelines into memcaches. Social graph moved to a service. Delayed work through queues. 2010: Starting to move timelines out to
Scalaz
This document provides an overview of Scalaz and functional programming concepts like Functor, Applicative, and Monad as they relate to the Option type in Scalaz. It discusses Option syntax, constructing Options, working with Options using fold, map, and other methods, and defines Option as an instance of Functor, Applicative, and Monoid. It also briefly touches on concepts like context bounds and
アドテク×Scala×パフォーマンスチューニング
アドテク×Scala meetup 2014-11-20 http://connpass.com/event/8384/Read less
Scaling Gilt: from monolith ruby app to micro service scala service architecture
Scaling Gilt: from monolith ruby app to micro service scala service architecture This document summarizes Yoni Goldberg's talk on Gilt's transition from a monolithic Ruby on Rails application to a distributed system of over 450 Scala microservices. Some of the key challenges they faced included scaling issues as traffic grew, difficulties deploying and testing changes across many interdependent se
Building microservices with Scala, functional domain models and Spring Boot
Building microservices with Scala, functional domain models and Spring Boot The document discusses building microservices with Scala, functional domain models, and Spring Boot. It describes using an event-driven and event sourcing architecture to solve data consistency issues with microservices and NoSQL databases. Event sourcing involves storing business events and replaying them to recreate stat
Scala and big data in ICM. Scoobie, Scalding, Spark, Stratosphere. Scalar 2014
Scala and big data in ICM. Scoobie, Scalding, Spark, Stratosphere. Scalar 2014 This document discusses various big data frameworks including Spark, Scoobi, Hadoop, and GraphX. It provides an example of using Spark to interactively analyze log data stored on HDFS. Spark allows loading data into memory and running multiple queries efficiently. The document also discusses benefits of Spark such as it
Building Distributed Systems in Scala
Apr 11, 2010Download as KEY, PDF174 likes35,542 views "In this session, Twitter engineer Alex Payne will explore how the popular social messaging service builds scalable, distributed systems in the Scala programming language. Since 2008, Twitter has moved the development of its most critical systems to Scala, which blends object-oriented and functional programming with the power, robust tooling, a
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あなたのScalaを爆速にする7つの方法 – Scala Matsuri 2016でお話しました
はてなブックマーク in Scala
Scala with DDD
Talks and Papers
Scala による自然言語処理
Developers Summit 2014 「Play2/Scalaでドメイン駆動設計を利用した大規模Webアプリケーションのスクラム開発の勘所」
RESTful HTTP on the JVM
12 Things Java Developers Should Know About Scala | alvinalexander.com