Ken Jones walks you through the core APIs for using Spark, fundamental mechanisms and basic internals of the framework, SQL and other high-level data access tools, and Spark’s streaming capabilities and machine learning APIs. Join in to learn how to perform machine learning on Spark and explore the algorithms supported by the Spark MLlib APIs.
Each topic includes a lecture combined with hands-on exercises that use Spark through an elegant web-based notebook environment. Notebooks allow you to code jobs, data analysis queries, and visualizations using your own Spark cluster, accessed through a web browser. You can keep the notebooks and continue to use them with the free Databricks Community Edition offering. Alternatively, each notebook can be exported as source code and run within any Spark environment.
Spark overview
Spark internals
Graph processing with GraphFrames
Spark ML’s Pipeline API for machine learning
Spark Structured Streaming
Ken Jones is an Apache Spark instructor at Databricks. Ken has thousands of hours of in-class instruction experience presenting classes on Spark, Scala, and other open source technologies to Fortune 500 companies and individual developers worldwide. Previously, Ken was a senior instructor at Twitter, where in his role as coordinator for Twitter’s engineering onboarding program, he taught classes on Scala programming and backend service development in Scala. Ken also spent several years teaching Android application development and Android operating system internals, as well as several programming languages. He is the coauthor of Practical Programming in Tcl and Tk, 4th edition, and Tcl and the Tk Toolkit, 2nd edition. Ken lives in San Diego, CA, with his husband, Dean, and their cat, Jasper. He enjoys traveling extensively for work to accumulate airline miles and hotel points so that he can travel extensively for pleasure. When not in front of a class or wandering about strange cities, he likes to read and watch science fiction and fantasy, listen to jazz and ’80s alternative music, and mix (and drink) cocktails.
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If you have any questions, please email me directly at josephk@databricks.com.