The Penn DB Group headed to Boston this week for the VLDB conference!
At the main conference, undergraduate alumni Daniel Xue presented his paper about fully concurrent GROUP BY aggregation, which was his senior thesis at Penn last year. Daniel’s work shows that a simple custom hash table may be the key ingredient!
At the AIDB workshop, Ph.D. student Jeff Tao presented a full paper on generating query optimization benchmarks with Bayesian optimization via Gremlin, which won a best paper honorable mention! Jeff’s work produced queries with an order of magnitude more headroom (optimization potential) than existing, hand-crafted benchmarks.
Also the AIDB workshop, MA/MS graduate Wangshu Hong presented a short paper about extending learned query optimizers, like Balsa, to DuckDB. Wangshu’s work also showed how censored observations could improve training stability for RL-powered learned optimizers.
At DASHSys, Ph.D. student Zixuan Yi presented her work on Data Canvas, a provenance-guided harness for agentic data engineering. Zixuan’s work allows a swarm of agents to collaboratively build large datasets, with hard lineage guarantees and support for human-driven repairs. A full version of Zixuan’s work will be presented at COLM this year.
