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Tuesday, June 20 • 9:00am - 11:00am
Integrating Julia in Real-world, Distributed Pipelines

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After attending this workshop, you will have the skills needed to integrate Julia in real-world environments. Not only that, you will understand at least one strategy for distributing Julia data analysis at production scale on large data sets and streaming data.

The Roadmap of the workshop will include:
  1. Intro - This section will explore any barriers to pushing Julia into production. What to do in real-world environments and what are the challenges of integrating Julia at production scale?
  2. Making your Julia analysis portable - Here, we will learn how to containerize Julia analyses, which goes a long way to making them deployable within organizations. We will also explore the trade offs with containerization and common gotchas. In this case, we will use Docker to containerize an example data analysis written in Julia.
  3. Distributing your Julia analysis at scale - Finally, we will learn how to take our Docker-ized Julia analysis and distributed at scale. That is, we will learn how to orchestrate the distribution of that analysis across a cluster and how to distribute data between instances of Julia. To do this, we will employ Kubernetes and Pachyderm.
The workshop will be completely example/demo based and will include individual exercises for the students.

avatar for Daniel Whitenack

Daniel Whitenack

Data Scientist and Lead Developer Advocate, Pachyderm
Daniel (@dwhitena) is a Ph.D. trained data scientist working with Pachyderm (@pachydermIO). Daniel develops innovative, distributed data pipelines which include predictive models, data visualizations, statistical analyses, and more. He has spoken at conferences around the world... Read More →

Tuesday June 20, 2017 9:00am - 11:00am
Stephens Lounge