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Developing a Dynamic Materialized View Index for Efficiently Discovering Usable Views for Progressive Queries
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  • Developing a Dynamic Materialized View Index for Efficiently Discovering Usable Views for Progressive Queries
  • Developing a Dynamic Materialized View Index for Efficiently Discovering Usable Views for Progressive Queries
저자명
Zhu. Chao,Zhu. Qiang,Zuzarte. Calisto,Ma. Wenbin
간행물명
Journal of information processing systems
권/호정보
2013년|9권 4호|pp.511-537 (27 pages)
발행정보
한국정보처리학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Numerous data intensive applications demand the efficient processing of a new type of query, which is called a progressive query (PQ). A PQ consists of a set of unpredictable but inter-related step-queries (SQ) that are specified by its user in a sequence of steps. A conventional DBMS was not designed to efficiently process such PQs. In our earlier work, we introduced a materialized view based approach for efficiently processing PQs, where the focus was on selecting promising views for materialization. The problem of how to efficiently find usable views from the materialized set in order to answer the SQs for a PQ remains open. In this paper, we present a new index technique, called the Dynamic Materialized View Index (DMVI), to rapidly discover usable views for answering a given SQ. The structure of the proposed index is a special ordered tree where the SQ domain tables are used as search keys and some bitmaps are kept at the leaf nodes for refined filtering. A two-level priority rule is adopted to order domain tables in the tree, which facilitates the efficient maintenance of the tree by taking into account the dynamic characteristics of various types of materialized views for PQs. The bitmap encoding methods and the strategies/algorithms to construct, search, and maintain the DMVI are suggested. The extensive experimental results demonstrate that our index technique is quite promising in improving the performance of the materialized view based query processing approach for PQs.