Name
Title | ||
|---|---|---|
How, Where, and Why Data Provenance Improves Query Debugging A Visual Demonstration of Fine-Grained Provenance Analysis for SQL |
Abstract | ||
|---|---|---|
Data provenance is meta-information about the origin and processing history of data. We demonstrate the provenance analysis of SQL queries and use it for query debugging. How-provenance determines which query expressions have been relevant for evaluating selected pieces of output data. Likewise, Where- and Why-provenance determine relevant pieces of input data. The combined provenance notions can be explored visually and interactively. We support a feature-rich SQL dialect with correlated subqueries and focus on bag semantics. Our fine-grained provenance analysis derives individual data provenance for table cells and SQL expressions. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ICDE53745.2022.00292 | 2022 IEEE 38TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2022) |
Keywords | DocType | ISSN |
Data Provenance, Databases, Debugging, SQL | Conference | 1084-4627 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tobias Müller | 1 | 0 | 0.68 |
| Pascal Engel | 2 | 0 | 0.34 |