Skip to main content Skip to main navigation

Publication

SmartNICs in the Cloud: The Why, What and How of In-network Processing for Data-Intensive Applications

Faeze Faghih; Tobias Ziegler; Zsolt István; Carsten Binnig
In: Pablo Barceló; Nayat Sánchez-Pi; Alexandra Meliou; S. Sudarshan (Hrsg.). Companion of the 2024 International Conference on Management of Data, SIGMOD/PODS 2024, Santiago, Chile, June 9-15, 2024. ACM SIGMOD International Conference on Management of Data (SIGMOD), Pages 556-560, ACM, 2024.

Abstract

Traditional query planners translate SQL queries into query plans to be executed over relational data. However, it is impossible to query other data modalities, such as images, text, or video stored in modern data systems such as data lakes using these query planners. In this paper, we propose Language-Model-Driven Query Planning, a new paradigm of query planning that uses Language Models to translate natural language queries into executable query plans. Different from relational query planners, the resulting query plans can contain complex operators that are able to process arbitrary modalities. As part of this paper, we present a first GPT-4 based prototype called CAESURA and show the general feasibility of this idea on two datasets. Finally, we discuss several ideas to improve the query planning capabilities of today’s Language Models.

More links