Provenance-based Data Skipping

Reproducibility Batches

Authors

• Xing Niu
• Ziyu Liu
• Pengyuan Li
• Boris Glavic
• Dieter Gawlick
• Vasudha Krishnaswamy
• Zhen Hua Liu
• Danica Porobic

Materials

Abstract

Database systems use static analysis to determine upfront which data is needed for answering a query and use indexes and other physical design techniques to speed-up access to that data. However, for important classes of queries, e.g., HAVING and top-k queries, it is impossible to determine up-front what data is relevant. To overcome this limitation, we develop provenance-based data skipping (PBDS), a novel approach that generates provenance sketches to concisely encode what data is relevant for a query. Once a provenance sketch has been captured it is used to speed up subsequent queries. PBDS can exploit physical design artifacts such as indexes and zone maps.

bibtex

@article{NL21,
  author = {Niu, Xing and Liu, Ziyu and Li, Pengyuan and Glavic, Boris and Gawlick, Dieter and Krishnaswamy, Vasudha and Liu, Zhen Hua and Porobic, Danica},
  keywords = {Provenance, Data Skipping, Relevance-based Data Management},
  title = {Provenance-based Data Skipping},
  journal = {Proceedings of the VLDB Endowment},
  projects = {Relevance-based Data Management},
  pages = {451 - 464},
  volume = {15},
  issue = {3},
  year = {2021},
  doi = {10.14778/3494124.3494130},
  reproducibility = {https://github.com/IITDBGroup/2021_pbds_reproducibility},
  reproducibilitybatch = {available},
  venueshort = {{PVLDB}},
  pdfurl = {https://vldb.org/pvldb/vol15/p451-niu.pdf},
  longversionurl = {https://arxiv.org/pdf/2104.12815}
}

Reference

Provenance-based Data Skipping Xing Niu, Ziyu Liu, Pengyuan Li, Boris Glavic, Dieter Gawlick, Vasudha Krishnaswamy, Zhen Hua Liu and Danica Porobic Proceedings of the VLDB Endowment. 15, 3 (2021) , 451–464.