Name
Abstract | ||
|---|---|---|
Many applications often require finding sets of entities of interest that meet certain constraints. Such set-based queries (SQs) can be broadly classified into two types: optimization SQs that involve some optimization constraint and enumerative SQs that do not have any optimization constraint. While there has been much research on the evaluation of optimization SQs, there is very little work on the evaluation of enumerative SQs, which represent the most fundamental fragment of set-based queries. In this paper, we address the problem of evaluating enumerative SQs using RDBMS. While enumerative SQs can be expressed using SQL, existing relational engines, unfortunately, are not able to efficiently evaluate such queries due to their complexity. In this paper, we propose a novel evaluation approach for enumerative SQs. Our experimental results on PostgreSQL demonstrate that our proposed approach outperforms the conventional approach by up to three orders of magnitude. HighlightsWe introduce a useful type of relational queries termed enumerative set-based queries.We show that existing relational database engines are unable to efficiently process such complex queries.We propose a novel and efficient approach to evaluate enumerative set-based queries. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.is.2015.08.005 | Information Systems |
Keywords | Field | DocType |
Set-based queries,Multi-query optimization,Relational database systems | SQL,Data mining,Relational database,Computer science,Theoretical computer science,Relational database management system,Database | Journal |
Volume | Issue | ISSN |
55 | C | 0306-4379 |
Citations | PageRank | References |
0 | 0.34 | 24 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guoping Wang | 1 | 488 | 63.02 |
| Chee Yong Chan | 2 | 643 | 199.24 |