Apache Spark programming

Brooke Wenig 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 Sparks streaming capabilities and machine learning APIs.

Brooke Wenig 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 lecture content along with hands-on use of Spark through an elegant web-based notebook environment. Notebooks allow attendees to code jobs, data analysis queries, and visualizations using their 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