Holden Karau

Principal Software Engineer @ IBM Spark Technology Center

Holden Karau is transgender Canadian, and an active open source contributor. When not in San Francisco working as a software development engineer at IBM’s Spark Technology Center, Holden talks internationally on Spark and holds office hours at coffee shops at home and abroad. Holden is a co-author of numerous books on Spark including High Performance Spark (which she believes is the gift of the season for those with expense accounts) & Learning Spark. She is a Spark committer and makes frequent contributions to Spark, specializing in PySpark and Machine Learning. Prior to IBM she worked on a variety of distributed, search, and classification problems at Alpine, Databricks, Google, Foursquare, and Amazon. She graduated from the University of Waterloo with a Bachelor of Mathematics in Computer Science. Outside of software she enjoys playing with fire, welding, scooters, poutine, and dancing.

Apache Spark Beyond Shuffling – Why it isn’t magic – but also where there is some really cool magic.

Apache Spark is one the most popular general purpose distributed systems in the past few years. Apache Spark has APIs in Scala, Java, Python and more recently a few different attempts to provide support for R, C#, and Julia. This talk looks at Apache Spark from a performance/scaling point of view and the work we need to do to be able to handle large datasets. In essence parts of this talk could be considered “the impact of design decisions from years ago and how to work around them.” It’s not all doom and gloom though, we will explore the new APIs and the exciting new things we can do with them with a brief detour into how to work around some of the trade-offs in the new APIs – but mostly focused on the new exciting shiny things we can play with. A basic background with Apache Spark will probably make the talk more exciting or depressing depending on your point of view but for those new to Apache Spark just enough to understand whats going will be covered at the start. The presenter would of course encourage you to buy and read her books on the topic (“Learning Spark” & “High Performance Spark”), because which presenter doesn’t do that.

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