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Upcoming events (5)
We have two great talks lined up for this event. Scala 3, what does it means for me? By Joan Goyeau We’ve all heard about Dotty or Scala 3 either through Martin Odersky’s great talks or features listing on Dotty’s website. This sounds like a big change but how will it affect me as a Scala user in my day to day development? Here at Netflix we are processing millions of events per second with Scala, so we’ve hit a few corner cases of the language that often end up in complicated and boilerplate workarounds that new features in Scala 3 are believed to be solving. Please join this talk to see what the future of the Scala landscape looks like for you and discuss your own compilation stories. About Joan Goyeau Data Engineer @ Netflix Passionate about Scala and solving data related problems. Maintainer of Orkestra.tech, a typesafe CI/CD server as a library. Scaling up ML Experimentation at Tubi 5x and Beyond By Alexandros Bantis The Tubi.tv streaming app (https://tubitv.com/) is installed on over 50 million mobile and OTT devices. To meet the needs of a fast-growing audience Tubi is enabling rapid machine learning (ML) experimentation using Scala. Ranking Service serves pre-computed personalization requests. It is a critical component of our next-generation machine learning services that has helped ramp up our rate of experimentation by 5x. It's built with Scala/Akka, ScalaPB, Kinesis, ScyllaDB, and has experimentation support built into the domain model. This presentation will discuss some of the challenges, motivations and experiences related to this project. About Alexandros Bantis Alexandros Bantis, Senior Scala Engineer, Tubi Alexandros has been building out the next generation of ML personalization services at Tubi over the past year. Before that he spent three years at Apple building out the publishing pipeline for Apple.com. Outside of Scala, he can usually be found at the playground with his children.
Compilation speed is a large pain point for many Scala developers. Twitter is one of the world’s largest Scala shops, and we continuously integrate all our projects at once in our monorepo. Lowering build times is crucial to help Twitter continue developing fast and safely. While Scala compilation is difficult to parallelize, the Language Tools team at Twitter has been working on a Scala outliner, Rsc, which produces the equivalent of C++ header files for Scala. Armed with these outlines, Scala compilation parallelism can be unlocked, allowing developers to take advantage of parallel, and even distributed, compilation to iterate ever faster. Learn how we're rolling out a Scala outliner into our continuous integration pipeline, while using open source APIs and implementations to compile and test millions of lines of code thousands of times a day to support low latency builds of Twitter's projects from source. Also important is community feedback on our ideas surrounding the developer experience of Rsc. About our Speaker: Win Wang Win Wang (https://www.linkedin.com/in/winwang) is a functional programming enthusiast working at Twitter to better the Scala developer experience. Currently focused on reducing compile times.
Please register at https://swift.tf! This is a joint meetup with Swift for TensorFlow. If you RSVP here you'll be waitlisted and nothing else will happen! We need a downtown SF location for this meetup providing food and beer for developers! Eugene Burmako was a student of Martin Odersky, the creator of Scala at EPFL, and the creator of Macro Paradise. After that he was a team lead at Twitter, developing Reasonable Scala (rsc). Recently Eugene joined Google where he works with Chris Lattner, the creator of Swift, on Swift for TensorFlow. As a compiler specialist who worked on developer effectiveness, Eugene has unique insights into the ecosystems of both languages. While his first impressions are still fresh, Eugene will share his impressions of Swift with us.
First Talk: ArKi-KV : Abusing Tagless Final Approach to build a key-value store by Sandeep Virdi There has been a lot of interest in the Tagless Final Approach/Pattern in the Scala-FP community. ArKi-KV is a simple LSM (Log Structured Merge Tree) based key value store that explores multiple functional programming concepts, including the Tagless Final Approach/Pattern. ArKi-KV uses cats/cats-effects for its functional and concurrent parts and jnr/jffi for off heap memory management. About Sandeep Virdi: Sandeep Virdi (https://www.linkedin.com/in/sandeep-virdi) is a Senior Software Engineer at Rally Health, building micro-services at scale using Scala. I've been using Scala professionally for 5+ years. Second Talk: Improve Microservice & Container Performance Interaction; no code Changes By Roland Lee With the deployment of microservices and containers in the cloud, network latency can be a primary cause of slow application response times. Additionally, most scale problems are due to inefficient database access. In this talk, we will introduce the concept of a database proxy, which provides SQL visibility and performance improvement for developers, without any code changes. We will review existing solutions and introduce a new approach that is distributed and avoids network latency. We will demo 1) Automated query caching and 2) Read/Write splitting. About Roland Lee Heimdall Data is an AWS Advanced Technology partner specializing in improving backend performance for SQL databases. Roland Lee (https://www.linkedin.com/in/leeroland) is head of products at Heimdall Data. His career has primarily focused on improving the scale and reliability, of high-end distributed systems.