Structured Streaming is new in Apache Spark 2.0, and work is being done to integrate the machine-learning interfaces with this new streaming system. Holden Karau and Seth Hendrickson look at the current state of Structured Streaming and machine learning before walking you through creating your own streaming model. Holden and Seth will also cover how to use structured machine-learning algorithms (if they are merged by the talk). By the end of this session, you’ll have a better understanding of Spark’s Structured Streaming API as well as how machine learning works in Spark.
Holden Karau is a software development engineer at IBM and is active in open source. Prior to IBM, she worked on a variety of big data, search, and classification problems at Alpine, Databricks, Google, Foursquare, and Amazon. Holden is the author of Learning Spark and has assisted with Spark workshops. She graduated from the University of Waterloo with a bachelors of mathematics in computer science.
Seth Hendrickson is a data scientist and Scala developer in IBM’s Spark Technology Center. Seth is focused on developing highly parallel machine-learning algorithms for the Apache Spark cluster computing ecosystem.
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