Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA
michael dddd

michael dddd
Software Engineer, Databricks

Website | @michaelarmbrust

Michael Armbrust is the lead developer of the Spark SQL and Structured Streaming projects at Databricks. Michael’s interests broadly include distributed systems, large-scale structured storage, and query optimization. Michael holds a PhD from UC Berkeley, where his thesis focused on building systems that allow developers to rapidly build scalable interactive applications and specifically defined the notion of scale independence.

Sessions

11:50am12:30pm Wednesday, March 15, 2017
Spark & beyond
Location: LL21 C/D
Secondary topics:  Streaming
michael dddd (Databricks), Tathagata Das (Databricks)
Average rating: ****.
(4.29, 7 ratings)
Apache Spark 2.0 introduced the core APIs for Structured Streaming, a new streaming processing engine on Spark SQL. Since then, the Spark team has focused its efforts on making the engine ready for production use. Michael Armbrust and Tathagata Das outline the major features of Structured Streaming, recipes for using them in production, and plans for new features in future releases. Read more.