A Developer’s View into Spark's Memory Model - Wenchen Fan

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: #SFdev23 About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: https://databricks.com/product/unified-data-analytics-platform Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc/ Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-named-leader-by-gartner