Most database teams optimize what they see in workload logs. But those very optimizations change what users choose to run!
In our CIDR paper, we argue that industrial workloads exhibit ๐ฌ๐ฎ๐ซ๐ฏ๐ข๐ฏ๐จ๐ซ๐ฌ๐ก๐ข๐ฉ ๐๐ข๐๐ฌ: logs reflect a negotiation between users and the platform.
- OLAP workloads are dominated by repetitive queries -- how can we optimize them? A promising direction is to do ๐ผ๐ณ๐ณ๐น๐ถ๐ป๐ฒ query optimization, allowing for a much more thorough plan search. Two new SIGMOD papers! ๐งต
- At aiDM@SIGMOD, PhD student Zixuan Yi will present LimeQO, the first *workload-level* learned query optimizer: simultaneously learning to optimize an entire query workload at once! By casting the problem as low rank matrix completion, we show that linear methods are all you need.
- Greatly enjoyed talking with Jack! We discussed the "research journey," what it means for DB research to be impactful, and new work from our lab about query optimization!๐จ The first episode in our #HighImpact series with Ryan Marcus (@RyanMarcus) is available now! ๐ง Listen on Spotify โก๏ธ open.spotify.com/show/6IQIF9oRSโฆ ๐ง Listen on Apple โก๏ธ podcasts.apple.com/us/podcast/disโฆ


