4 papers
The Case for TPU-Accelerated Analytical Query Processing
Yeounoh Chung, Jaehyun Ha, Helena Caminal +4
Large-scale analytical query processing requires computing substrates capable of immense distributed scale-out. Tensor Processing Units (TPUs) perfectly embody this extreme-scale a…
CADENZA: Compiling Natural-Language Intent into Task-Specific Operator DAGs for Semantic Query Processing
Jaehyun Ha, Yongjoo Park, Wook-Shin Han
Semantic query processing engines (SQPEs) extend relational query processing with semantic operators that are executed via model inference over unstructured data. Optimizing such q…
CADENZA in Action: Breaking the Monolith with Intent-Dependent Plan Spaces for Semantic Queries
Jaehyun Ha, Yongjoo Park, Wook-Shin Han
Semantic query processing engines execute semantic operators, whose behavior is specified by natural-language intents, via model inference over multimodal data. Most existing optim…
Guaranteeing the Õ(AGM/OUT) Runtime for Uniform Sampling and OUT Size Estimation over Joins
Kyoungmin Kim, Jaehyun Ha, George Fletcher +1
We propose a new method for estimating the number of answers OUT of a small join query Q in a large database D, and for uniform sampling over joins. Our method is the first to sati…