This post continues a larger series of posts on the Trino Summit 2022 sessions. Following the Keynote: State of Trino session, engineers from Apple shared the current usage of Trino at Apple. They discuss how they support Trino as a service for multiple end-users, and the critical features that drew Apple to Trino. They wrap up with some challenges they have faced and some development they have planned to contribute to Trino.
Trino is deployed at scale in Apple, and it continues to see tremendous adoption across multiple teams at Apple. Yathi Peddyshetty, Software Engineer @ Apple
The commonplace adhoc and BI analytics use cases make up a lot of how Apple uses Trino today. They also have increasing uses in federated querying and A/B testing.
To deploy Trino as a service, Apple has an in-house Kubernetes operator to manage the Trino cluster lifecycles. They also created an orchestrator to provision and simplify cluster creation and management. They make this a self-service console that allows users to provision their own clusters per request. Their custom orchestrator also takes care of autoscaling and other technical complexities of maintaining a scalable Trino system.
Apple primarily uses Iceberg, Hive, and Cassandra connectors. They have a heavy focus on Apache Iceberg as their table format and have contributed a significant amount of PRs to improve interoperability between Trino and Spark, and increased coverage of Iceberg APIs. Other challenges Apple face stem from the lack of flexible routing of queries to achieve zero downtime, and having pluggable optimizer rules and operators.
Apple has various features on their roadmap to eventually contribute to the community. This includes, exposing remaining functionality in the Iceberg APIs, support all partition transforms, predicate pushdowns, bucketed joins, simple aggregate pushdowns, Iceberg native views in Trino, and more.
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