REGAL+: Reverse engineering SPJA queries

Wei Chit Tan, Meihui Zhang, Hazem Elmeleegy, Divesh Srivastava

Research output: Contribution to journalConference articlepeer-review

9 Citations (Scopus)
Plum Print visual indicator of research metrics
  • Citations
    • Citation Indexes: 9
  • Captures
    • Readers: 18
see details

Abstract

The goal of query reverse engineering is to re-generate the SQL query that produced a given result from some known database. The problem has many real world applications where users need to better understand the lineage and trust- worthiness of various data reports even when the authors of those reports are no longer reachable or are unable to provide the required explanations anymore. It gets more challenging as the complexities of both the query and database schema increase. Prior work has addressed the reverse engineering of constrained types of SQL queries and sometimes on constrained schemas, such as single-table schemas. In this demonstration, we present a framework called REGAL+, which builds upon, and extends prior work to enable the discovery of Select-Project-Join-Aggregation (SPJA) queries over arbitrary schemas. Without any prior schema knowledge or SQL expertise, the user only needs to upload a data report (e.g., as a spreadsheet), and the system will automatically compute and display the queries capable of generating that report from the database.

Original languageEnglish
Pages (from-to)1982-1985
Number of pages4
JournalProceedings of the VLDB Endowment
Volume11
Issue number12
DOIs
Publication statusPublished - 2018
Event44th International Conference on Very Large Data Bases, VLDB 2018 - Rio de Janeiro, Brazil
Duration: 27 Aug 201831 Aug 2018

Fingerprint

Dive into the research topics of 'REGAL+: Reverse engineering SPJA queries'. Together they form a unique fingerprint.

Cite this

Tan, W. C., Zhang, M., Elmeleegy, H., & Srivastava, D. (2018). REGAL+: Reverse engineering SPJA queries. Proceedings of the VLDB Endowment, 11(12), 1982-1985. https://doi.org/10.14778/3229863.3236240