Blend: A Unified Data Discovery System
Fuente:
arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866913590471032832 |
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| author | Esmailoghli, Mahdi Schnell, Christoph Miller, Renée J. Abedjan, Ziawasch |
| author_facet | Esmailoghli, Mahdi Schnell, Christoph Miller, Renée J. Abedjan, Ziawasch |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_02656 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Blend: A Unified Data Discovery System Esmailoghli, Mahdi Schnell, Christoph Miller, Renée J. Abedjan, Ziawasch Databases 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. |
| title | Blend: A Unified Data Discovery System |
| topic | Databases |
| url | https://arxiv.org/abs/2310.02656 |