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.
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.
You use multiple tools for databases, for example Azure Data Studio for SQLServer access, Toad or SQLDeveloper for Oracle access, MySQLWorkbench for MySQL databases. Imagine we have one tool and we can query any database, bring any table from any catalog to a single canvas! Now you join, the underlying PrestoDB compatible query is generated. Click a button, you get the profiled data, including distributions and correlations. An amazing tool in action.