A New DBMS Architecture for DB-IR Integration
暂无分享,去创建一个
Nowadays, as there is an increasing need to integrate the DBMS (for structured data) with Information Retrieval (IR) features (for unstructured data), DB-IR integration becomes one of major challenges in the database area[1, 2]. Extensible architectures provided by commercial ORDBMS vendors can be used for DB-IR integration. Here, extensions are implemented using a high-level (typically, SQL-level) interface. We call this architecture loose-coupling. The advantage of loose-coupling is that it is easy to implement. But, it is not preferable for implementing new data types and operations in large databases when high performance is required. In this talk, we present a new DBMS architecture applicable to DB-IR integration, which we call tight-coupling. In tight-coupling, new data types and operations are integrated into the core of the DBMS engine in the extensible type layer. Thus, they are incorporated as the "first-class citizens"[1] within the DBMS architecture and are supported in a consistent manner with high performance. This tight-coupling architecture is being used to incorporate IR features and spatial database features into the Odysseus ORDBMS that has been under development at KAIST/AITrc for over 16 years[3]. In this talk, we introduce Odysseus and explain its tightly-coupled IR features (U.S. patented in 2002[2]). Then, we demonstrate excellence of tight-coupling by showing benchmark results. We have built a web search engine that is capable of managing 20-100 million web pages in a non-parallel configuration using Odysseus. This engine has been successfully tested in many commercial environments. In a parallel configuration, it is capable of managing billons of web pages. This work won the Best Demonstration Award from the IEEE ICDE conference held in Tokyo, Japan in April 2005[3].
[1] 황규영,et al. Inverted index storage structure using subindexes and large objects for tight coupling of information retrieval with database management systems , 2002 .
[2] Jennifer Widom,et al. The Lowell database research self-assessment , 2003, CACM.
[3] Jae-Gil Lee,et al. Odysseus: a high-performance ORDBMS tightly-coupled with IR features , 2005, 21st International Conference on Data Engineering (ICDE'05).