mlsanityData to 7 Oct 2026

Blend: A Unified Data Discovery System

arXiv 2310.02656 ↗First posted 4 Oct 2023cs.DBcited by 4

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Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Oct 2023.

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Citing papers per year: 2025: 2; 2026: 2.

4 papers.