在数据库和逻辑编程系统中试验递归查询
Experimenting with recursive queries in database and logic programming systems
摘要：
本文考虑了大量（可能是分布式的）数据的推理问题。目前，现有的建议显示出一些局限性：{ \em（i）}由于推理通常在主存中进行的事实，可以同时处理的数据的量是有限的; { \em（ii）}与外部的交互（和独立的）DBMS不是微不足道的，在某些情况下，根本不允许;{ \em（iii）}当前实现的效率对于它们在涉及大量数据的复杂推理任务中的利用仍然是不够的。本文提供了在这种情况下的贡献，它提出了一个新的系统，称为DLV $^{DB}$，旨在解决这些问题。此外，本文报告了一个彻底的实验分析的结果，我们已经进行了比较我们的系统与几个国家的最先进的系统（包括逻辑和数据库）的一些经典的演绎问题;其他测试系统是：LDL++，XSB，Smodels和三个顶级的商业DBMS。DLV $^{DB}$在递归查询上的性能甚至明显优于商业数据库系统。逻辑程序设计理论与实践（Theory and Practice of Logic Programming，TPLP）
英文摘要：
This paper considers the problem of reasoning on massive amounts of (possibly distributed) data. Presently, existing proposals show some limitations: {\em (i)} the quantity of data that can be handled contemporarily is limited, due to the fact that reasoning is generally carried out in main-memory; {\em (ii)} the interaction with external (and independent) DBMSs is not trivial and, in several cases, not allowed at all; {\em (iii)} the efficiency of present implementations is still not sufficient for their utilization in complex reasoning tasks involving massive amounts of data. This paper provides a contribution in this setting; it presents a new system, called DLV$^{DB}$, which aims to solve these problems. Moreover, the paper reports the results of a thorough experimental analysis we have carried out for comparing our system with several state-of-the-art systems (both logic and databases) on some classical deductive problems; the other tested systems are: LDL++, XSB, Smodels and three top-level commercial DBMSs. DLV$^{DB}$ significantly outperforms even the commercial Database Systems on recursive queries. To appear in Theory and Practice of Logic Programming (TPLP)
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
