TY - JOUR
T1 - REGAL+
T2 - 44th International Conference on Very Large Data Bases, VLDB 2018
AU - Tan, Wei Chit
AU - Zhang, Meihui
AU - Elmeleegy, Hazem
AU - Srivastava, Divesh
N1 - Publisher Copyright:
© 2018 VLDB Endowment.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85058903115&partnerID=8YFLogxK
U2 - 10.14778/3229863.3236240
DO - 10.14778/3229863.3236240
M3 - Conference article
AN - SCOPUS:85058903115
SN - 2150-8097
VL - 11
SP - 1982
EP - 1985
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 12
Y2 - 27 August 2018 through 31 August 2018
ER -