From the 1 of 12 linked papers with an AI index.
12 papers
IDSTune: A Multi-Agent Collaborative Framework for Integrated Database System Tuning
Yiyan Li, Guanli Liu, Renata Borovica-Gajic +6
Database tuning is critical for achieving high performance in modern database management systems (DBMSs). Existing methods typically optimize a single component---knobs, indexes, o…
Hollywood: Towards a Large Movie Dataset for Database Benchmarking
Ivan Iachnyk, Mihail Stoian, Andreas Kipf
The IMDb real-world dataset of the JOB benchmark has been extensively used in the last decade as part of the research line on cardinality estimation, given its ability to stress te…
OptFSST: Optimized FSST String Compression
Hedi Chehaidar, Mihail Stoian, Moritz Stargalla +1
The paper introduces OptFSST, an enhanced version of Fast Static Symbol Table compression that uses dynamic programming and heuristic table construction to achieve better compressi…
SemCEB: A Cardinality Estimation Benchmark for Semantic Operators
Andreas Zimmerer, Claudius Kühn, Yang Li +3
Modern data systems increasingly expose multi-modal large language models as semantic operators: SQL operators, including filters and joins, whose predicates are defined by a natur…
MLSkip: Data Skipping for ML Filters via Lightweight Metadata
Mihail Stoian, Mark Gerarts, Pascal Ginter +3
Database vendors recently released AI functions that can be used in filter predicates. As such functions often rely on costly, black-box ML models, they unveil new data management…
Redbench: Workload Synthesis From Cloud Traces
Johannes Wehrstein, Roman Heinrich, Mihail Stoian +5
Workload traces from cloud data warehouse providers reveal that standard benchmarks such as TPC-H and TPC-DS fail to capture key characteristics of real-world workloads, including…