Presented By O'Reilly and Cloudera
Make Data Work
March 28–29, 2016: Training
March 29–31, 2016: Conference
San Jose, CA
Dean Wampler

Dean Wampler
Head of Developer Relations, Anyscale

Website | @deanwampler

Dean Wampler is an expert in streaming data systems, focusing on applications of machine learning and artificial intelligence (ML/AI). He is Head of Developer Relations at Anyscale, which is developing Ray for distributed Python, primarily for ML/AI. Previously, he was an engineering VP at Lightbend, where he led the development of Lightbend CloudFlow, an integrated system for building and running streaming data applications with Akka Streams, Apache Spark, Apache Flink, and Apache Kafka. Dean is the author of Fast Data Architectures for Streaming Applications, Programming Scala, and Functional Programming for Java Developers, and he is the coauthor of Programming Hive, all from O’Reilly. He’s a contributor to several open source projects. A frequent conference speaker and tutorial teacher, he’s also the co-organizer of several conferences around the world and several user groups in Chicago. He has a Ph.D. in Physics from the University of Washington.

Sessions

1:50pm–2:30pm Wednesday, 03/30/2016
Spark & Beyond

Location: 210 A/E
Tags: featured
Dean Wampler (Anyscale)
Average rating: ****.
(4.57, 23 ratings)
The success of Apache Spark is bringing developers to Scala. For big data, the JVM uses memory inefficiently, causing significant GC challenges. Spark's Project Tungsten fixes these problems with custom data layouts and code generation. Dean Wampler gives an overview of Spark, explaining ongoing improvements and what we should do to improve Scala and the JVM for big data. Read more.
11:00am–11:40am Thursday, 03/31/2016
Office Hours

Location: Table B (O'Reilly Booth)
Tags: real-time
Dean Wampler (Anyscale)
If you’re using (or considering) Scala and JVM as a big data platform, Dean can answer all your questions about Spark, Mesos, and fast data. Read more.