Videos Archive - PrestoDB

Building Modern Data Lakes for Analytics Using Object Storage – Satish Ramakrishnan, MinIO

The modern data lake is distributed, unstructured and demands performance and scale – or better stated, performance at scale. Modern object stores are the ideal platform to pair with MPP query engines like Presto – particularly as the scale reaches tens or hundreds of petabytes with tens to hundreds of concurrent queries. In this talk, Satish Ramakrishnan will outline the better together attributes of the two technologies with a focus on the most sophisticated modern object storage features – from throughput optimizations, multi-cloud capabilities, cross-cloud active active replication and lifecycle management. Participants will come away with a reference architecture suited to query processing at object scale.

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 Git-like Repository for your Data Lake – Vinodhini Sivakami Duraisamy, Treeverse

A Git-like Repository for your Data Lake – Vinodhini Sivakami Duraisamy, Treeverse We tend to adopt practices that improve the flexibility of development and the velocity of code deployment, but how confident are we that the complex data system is safe once it arrives in production? We must be able to experiment in production and automate actions while minimizing customer pain and reducing damage to code and data. If your product’s value is derived from data in the shape of analytics or machine learning, losing it, or having corrupted data, can easily translate into pain. In this session, you will discover how chaos engineering principles apply to distributed data systems and the tools that enable us to make our data workloads more resilient.

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

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.

Build & Query Secure S3 Data Lakes with Ahana Cloud and AWS Lake Formation

AWS Lake Formation is a service that allows data platform users to set up a secure data lake in days. Creating a data lake with Presto and AWS Lake Formation is as simple as defining data sources and what data access and security policies you want to apply. In this talk, Wen will walk through the recently announced AWS Lake Formation and Ahana integration