Building a High-Performance Database wit...

#distributedsystems #scala #akka #spark #FiloDB #cassandra Scala and its large ecosystem of libraries are increasingly being used to build highly scalable and performant data systems. In this talk, I share years of experience building high performance data systems using Scala, Akka, and Spark, plus recent experience building FiloDB, a high performance analytics database built on these technologies. How does FiloDB fit into the modern big data streaming world? How do you leverage all the features of Spark to make a database? How do we balance Scala and functional programming with very high performance demands? What are some tips to watch out for when building very very fast Scala code? - Introduction to FiloDB and its use cases for analyzing streaming and static data - How FiloDB fits into the SMACK stack for event storage and deep data analysis / machine learning - Some interesting use cases, such as streaming support for smart cities / IoT - Integration of Spark DataFrames and Data Sources - When to use Futures, Actors, or neither - Writing a reactive, at-least-once data pipeline with back pressure - Reactive stack metrics and performance monitoring - Filo: summing integers at billions of ops per second, taking advantage of processor cache and SIMD with super fast vector operations - Serialization, GC, and off-heap: how to leverage binary data structures for the win