In this talk, Alan Shreve will begin by talking about decentralizing the web, but then he will talk about stream multiplexing in Go as a foundation for RPC. Specifically, he'll cover the Muxado library he built for this purpose (https://github.com/inconshreveable/muxado). Alan will explain how muxado makes a great building block for custom protocols and RPC, outline the design of the public API, and go over some of the clever tricks employed in the implementation to make muxado fast. This talk was recorded at the GoSF meetup at Heroku.
In this talk, Anand Henry, Senior Software Engineer at Eventbrite, talks about their use of Apache Cassandra. Anand focuses on the Eventbrite data model & access patterns and the architecture of an Apache Cassandra Powered Recommendation Engine. He also goes over Cassandra as a data store to serve recommendations based on email, mobile push notifications, and web APIs. Later in the talk he touches on user audit logging with Apache Cassandra. This talk was recorded at the DataStax Cassandra SF Users meetup.
At Chartbeat we are thinking about adding probabilistic counters to our infrastructure, HyperLogLog (HLL) in particular. One of the challenges with something like this is to make it redundant and have somewhat good performance. Since HyperLogLog is a relatively new approach to cardinality approximation there are not many off the shelf solutions, so why not try and implement HLL in Cassandra?
The last hackweek I spent hacking Apache Cassandra. My goal was to add a HyperLogLog data type to the database, so I could count billions of unique items with very small memory footprint and get redundancy for free. However, the work I’ve done was not entirely a success, but it wasn’t a failure either. The project was much more complicated than I initially anticipated. There are tons and tons of layers of abstractions and it requires a significant amount of time to how things work. So, In this post I am going to walk you through some Cassandra internals and the changes that are necessary to add a new data type. All code examples will refer to Cassandra 2.x. Of course I don’t have fully working HLL implementation in cassandra (see the final section), but it was a nice hack.
If you're building a new web application, the problems that you run into generally fit into one of 4 categories:
1) Prototyping: I want to build something quickly.
2) Adapting: I want to be able to easily iterate on my code base.
3) Testing: I want to make sure that the app works.
4) Scaling: I want to utilize server resources efficiently.
In this presentation, Valeri Karpov from MongoDB will provide a high-level overview of how the MEAN stack, and in particular Node.js and npm, solve each of these pain points. This talk was recorded at the node.js meetup at Pivotal Labs. This talk was recorded at the NodeJS meetup at Pivotal Labs.
While building Jux.com, there was a need for applying transformations and effects to images in a way that would work across devices. The Magickly app was built as a stateless image effects API. To demonstrate its flexibility, the app was converted into a gem and used to power Mustachio - better known as mustachify.me. In this talk, Aidan Feldman, education hacker at Github, will cover some of the architecture decisions for Magickly, some fun findings about ImageMagick, and the internals of both gems. This talk was recorded at the Anatomy of a Ruby Gem meetup at Artsy.
In this talk, Daniel Krasner covers rapid development of high performance scalable text processing solutions for tasks such as classification, semantic analysis, topic modeling and general machine learning. He demonstrates how Python modules, in particular the Rosetta Python library, can be used to process, clean, tokenize, extract features, and build statistical models with large volumes of text data. The Rosetta library focuses on creating small and simple modules (each with command line interfaces) that use very little memory and are parallelized with the multiprocessing package. Daniel also touches on LDA topic modeling and different implementations thereof (Vowpal Wabbit and Gensim). The talk is part presentation, and part “real life” example tutorial. This talk was recorded at the NYC Machine Learning meetup at Pivotal Labs.
Front-end engineers have gone through a bit of a renaissance in recent years. There’s been a wild and wonderful spurt in innovation that has completely changed what it means to be a front-end developer. We now have a vast and wide array of tools available to us, allowing us to develop faster and smarter. We now can push the limits of what a modern web browser can do, accomplishing things that two years ago seemed impossible. Bottom line, right now is an amazing time to be a front-end developer.
In early December, we held our first ever hack-day. Each product manager teamed up with one to two engineers for the day to think up and develop any idea that they wanted. At the end of hack-day, each team then presented their concepts, demoed the results, and explained how they thought their hack improved the application.
On the morning of hack-day, my partner Jeff Rand and I holed up in a corner of the office with a hearty breakfast of pancakes, bacon and eggs and quickly came up with a list of about 10-15 ideas, from improvements that we knew Members or our Sales team had asked for, to improvements to the codebase that we knew needed attention. We had two basic requirements:
In this talk, Niklas Nielsen from Mesosphere, talks about Apache Mesos, a cluster manager that provides efficient resource isolation and sharing across distributed applications or frameworks. In this talk, Niklas will go over how to write frameworks for Apache Mesos in Go. It can run Apache Hadoop, MPI, Hypertable, Apache Spark, Storm, Chronos, Marathon, and other applications on a dynamically shared pool of nodes. The biggest user of Mesos is Twitter, where it runs on thousands of servers. Airbnb runs all of their data infrastructure on it, processing petabytes of data. This talk was recorded at the GoSF meetup at Heroku.