Stepping beyond ETL in batches, large enterprises are looking at ways to generate more up-to-date insights. As we step into the age of Continuous Application, this session will explore the ever more popular Structure Streaming API in Apache Spark, its application to R, and building examples of machine learning use cases. Starting with an introduction to the high-level concepts, the session will dive into the core of the execution plan internals and examine how SparkR extends the existing system to add the streaming capability. Learn how to build various data science applications on data streams integrating with R packages to leverage the rich R ecosystem of 10k+ packages. Session hashtag: #SFdev2
Felix Cheung is a Committer of Apache Spark and a PMC/Committer of Apache Zeppelin. He has been active in the Big Data space for 3+ years, he is a co-organizer of the Seattle Spark Meetup, presented several times and he was a teaching assistant to the very popular edx Introduction to Big Data with Apache Spark, and Scalable Machine Learning MOOCs in the summer of 2015.