On-Demand Recordings from PrestoCon’s, Webinars, Meetups, and more
While using the Presto Iceberg connector, the in-heap cache in Presto is likely overloaded. In this talk, Beinan and Chunxu will share the design, implementation, and optimization of the off-heap cache to address the scalability challenges. You will learn how to cache Iceberg data and metadata for the Presto Iceberg connector, followed by future work on improving table scans using Apache Arrow.
Tecton is the leading feature platform for real-time machine learning. Rather than build new SQL engines from scratch, Tecton connects to your existing engine to transform raw data into features for machine learning. This talk will cover Tecton’s new integration with Athena for feature engineering. Derek will demonstrate how Tecton with Athena is the fastest way to build feature pipelines and put new models in production.
Apache Iceberg is an open table format for huge analytic datasets. The Presto Iceberg connector consolidates the SQL engine and the table format, to empower high-performant data analytics. Here, Beinan and Chunxu would like to discuss and share the architectural design of the Presto Iceberg connector, advanced Iceberg feature support (such as native iceberg connector, row-level deletion, and iceberg v2 support), and the future roadmap.
Apache Iceberg is an open table format for huge analytic datasets. At Twitter, engineers are working on the Presto-Iceberg connector, aiming to bring high-performance data analytics on Iceberg to the Presto ecosystem. Here, Chunxu would like to share what they have learned during the development, hoping to shed light on the future work of interactive queries.