Personal schedule for Jared Williams
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Location: Oregon Ballroom 203/204
Opening remarks by the OSCON Data program chairs, Sarah Novotny and Bradford Stephens.
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Keynote
Location: Oregon Ballroom 203/204
Dive into the distributed system that powers OkCupid’s match searches. Learn how we use C++, event-based programming, and SSDs to solve problems that crop up when building a high performance, high availability distributed system.
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Keynote
Location: Oregon Ballroom 203/204
Keynote by Benjamin Black, Co-founder, fast_ip.
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Keynote
Location: Oregon Ballroom 203/204
It's 2021. You have a petabyte drive on your keychain, your startup company leases bulk cloud storage by the exabyte, and you have a million cores for data crunching. You even can have your own copy of the entire world's public semantic data. What do you do with it? If you're not sure yet, I've got plenty of ideas for you.
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Keynote
Location: Oregon Ballroom 203/204
An open microphone question and answer session with the morning's keynote speakers.
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Hadoop gives you the ability to process massive amounts of data at scale. This presentation will show you how hadoop makes use of commodity hardware to allow you to build a system that scales, that deals gracefully with failure of individual nodes, and gives you the power of Map/Reduce to process Petabytes.
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Between the NoSQL movement and new cloud offerings, it seems there are new storage options popping up every day. How do you select which one is the best for your project? The truth is that it's unlikely one option is best for all your needs. This session walks you through the various options considered by one startup and how it selected five separate storage engines - and has no regret doing so!
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Learning the syntax of a new language is easy, but learning to think under a different paradigm is hard. This session helps you transition from a Java writing imperative programmer to a functional programmer, using Java, Clojure and Scala for examples.
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Redis is an entry in the new breed of nosql databases. But it takes a different approach that makes it much more interesting then most of the other key/value stores in the same category. Come learn what makes redis so useful that it seems everyone is adding it to their toolbox.
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This talk introduces an open-source SQL-based system for continuous or ad-hoc analysis of streaming data built on top of Flume-based data collection for Hadoop.
Attendees will understand how to use a new tool to extend their Hadoop data collection pipeline with real-time streaming analytics.
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A look at using Jenkins for continuous integration, focusing on three different use cases at three different companies, along with a general update on the state of the project.
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