Shared Foundations Of Composable Data Systems – Biswapesh Chattopadhyay, Google

Shared Foundations Of Composable Data Systems – Biswapesh Chattopadhyay, Google

Data processing systems have evolved significantly over the last decade, driven by various factors such as the advent of cloud computing, increasingly complexity of applications such as ML, HTAP, Streaming, Observability and Graph processing. However, historically, these frameworks have evolved independently, leading to significant fragmentation of the stack. In this talk, I will talk about how this has evolved in the open source and at Meta, and how we are solving this problem through the Shared Foundations effort, leading to composable systems. This has resulted in significantly better performance, more features, higher engineering velocity and a more consistent user experience.

Prism: Presto Gateway Service at Uber – Hitarth Trivedi, Uber

Prism: Presto Gateway Service at Uber – Hitarth Trivedi, Uber

Prism is a gateway service for all Presto queries at Uber. It addresses Uber specific needs in four main areas – resource management, query gating, monitoring, and security. It is responsible for proxying over three million weekly queries from 6000+ weekly active users across all of Uber. Presto has variable execution times due to high multi-tenancy at Uber. Prism helps in overcoming those challenges using features like query routing, load balancing, query gating, session parameter checks, failover clusters which helps in maintaining a 99.9% availability and reliability SLA for Presto at Uber. Functionality – Query Execution: 1. Async execution API returns data stream 2. Async execution API returns File Descriptor – Routing – Prism can route queries to different clusters based on client sources. Other functionalities: Load Balancing, Query Gating, Failover, Session Properties, Security

Using Presto’s BigQuery Connector for Better Performance and Ad-hoc Query connector for better performance and ad-hoc query in the Cloud – George Wang & Roderick Yao

Using Presto’s BigQuery Connector for Better Performance and Ad-hoc Query connector for better performance and ad-hoc query in the Cloud – George Wang & Roderick Yao

The Google BigQuery connector gives users the ability to query tables in the BigQuery service, Google Cloud’s fully managed data warehouse. In this presentation, we’ll discuss the BigQuery Connector plugin for Presto which uses the BigQuery Storage API to stream data in parallel, allowing users to query from BigQuery tables via gPRC to achieve a better read performance. We’ll also discuss how the connector enables interactive ad-hoc query to join data across distributed systems for data lake analytics.