Blend: A Unified Data Discovery System

October 04, 2023 Β· Declared Dead Β· πŸ› IEEE International Conference on Data Engineering

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Authors Mahdi Esmailoghli, Christoph Schnell, RenΓ©e J. Miller, Ziawasch Abedjan arXiv ID 2310.02656 Category cs.DB: Databases Citations 12 Venue IEEE International Conference on Data Engineering Last Checked 3 months ago
Abstract
Most research on data discovery has so far focused on improving individual discovery operators such as join, correlation, or union discovery. However, in practice, a combination of these techniques and their corresponding indexes may be necessary to support arbitrary discovery tasks. We propose BLEND, a comprehensive data discovery system that supports existing operators and enables their flexible pipelining. BLEND is based on a set of lower-level operators that serve as fundamental building blocks for more complex and sophisticated user tasks. To reduce the execution runtime of discovery pipelines, we propose a unified index structure and a rule-based optimizer that rewrites SQL statements into low-level operators when possible. We show the superior flexibility and efficiency of our system compared to ad-hoc discovery pipelines and stand-alone solutions.
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