Building A Feature Store For Hyper Growth

Tuesday, October 11, 12:40pm - 1:05pm (EDT)

Time shown in-04:00 America, New York

Speaker: Brian Seo, Doordash

In the last year Doordash has seen tremendous increases in the number of use cases on its machine learning platform, causing a dramatic growth in the number of models and features being generated. This in turn has exposed the challenges and limitations of using Redis at scale. The ML Platform team at DoorDash ultimately opted to explore a complementary disk based storage backend as a supplement to our existing tech, ultimately landing on using CRDB. There have been many learnings on upload throughput, query performance, and general design patterns that we’d like to share with the broader ML community. In this presentation we’ll go over our feature store architecture and some of the learnings in supporting CRDB in addition to Redis and our thoughts on what it takes to build a feature store that can scale up rapidly on demand.

Add to Calendar 2022/10/11 09:40:00 2022/10/11 10:05:00 America/Los_Angeles Building A Feature Store For Hyper Growth Speaker: Brian Seo, Doordash

In the last year Doordash has seen tremendous increases in the number of use cases on its machine learning platform, causing a dramatic growth in the number of models and features being generated. This in turn has exposed the challenges and limitations of using Redis at scale. The ML Platform team at DoorDash ultimately opted to explore a complementary disk based storage backend as a supplement to our existing tech, ultimately landing on using CRDB. There have been many learnings on upload throughput, query performance, and general design patterns that we’d like to share with the broader ML community. In this presentation we’ll go over our feature store architecture and some of the learnings in supporting CRDB in addition to Redis and our thoughts on what it takes to build a feature store that can scale up rapidly on demand. Online false MM/DD/YYYY 30 OPAQUE apQfLtmRnzOiFbgoNmal132273

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Feature Store Summit 2022

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