As part of Project Tungsten, we started an ongoing effort to substantially improve the memory and CPU efficiency of Apache Spark’s backend execution and push performance closer to the limits of modern hardware. In this talk, we’ll take a deep dive into Apache Spark’s unified memory model and discuss how Spark exploits memory hierarchy and leverages application semantics to manage memory explicitly (both on and off-heap) to eliminate the overheads of JVM object model and garbage collection.
Session hashtag: #EUdd2
Wenchen Fan is a software engineer at Databricks, working on Spark Core and Spark SQL. He mainly focuses on the Apache Spark open source community, leading the discussion and reviews of many features/fixes in Spark. He is a Spark committer and a Spark PMC member.