Scaling Cache for Presto Iceberg Connector – Beinan Wang, Alluxio & Chunxu Tang

Scaling Cache for Presto Iceberg Connector – Beinan Wang, Alluxio & Chunxu Tang

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.

A Tour of Presto Iceberg Connector – Beinan Wang, Alluxio & Chunxu Tang, Twitter

A Tour of Presto Iceberg Connector – Beinan Wang, Alluxio & Chunxu Tang, Twitter

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.

Presto and Apache Iceberg – Chunxu Tang, Twitter

Presto and Apache Iceberg – Chunxu Tang, Twitter

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.

How Carbon uses PrestoDB in the Cloud with Ahana to Power its Real-time Customer Dashboards

How Carbon uses PrestoDB in the Cloud with Ahana to Power its Real-time Customer Dashboards

Carbon is a real-time revenue management platform that consolidates revenue and audience analytics, data management, and yield operations into a single solution. Real-time analytics is super critical – their customers rely on real-time data to make revenue decisions. After facing issues around performance, visibility & ease of use, and serverless pricing model with AWS Athena, the team moved to a managed service for PrestoDB in the cloud – Ahana Cloud – to power their customer-facing dashboards. In this session, Jordan will discuss some of the reasons the team moved from AWS Athena to a managed PrestoDB on Intel-optimized AWS instances. He will also dive into their current architecture that includes an Ahana-managed Hive Metastore along with Apache ORC file format and an S3-based data lake. Last, he’ll share some performance benchmarks and talk about what’s next for PrestoDB at Carbon.