• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.31-50
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• 1996

In this paper we prescribe a replication server scheme with an algorithm DRF (Differential Refresh File) to refresh multiple materialized views and replicas in distributed environments. Before sending relevant tuples in server sites to client sites, an effective tuple reduction scheme is developed as a preprocessor to reduce the transmission cost. Because it utilizes differential files with out touching base relations, the DRF scheme can help to minimize the number of locks, which enhances the system's performance.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.175-184
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• 2000

A data warehouse is an integrated and summarized collection of data that can efficiently support decision making process. The summarized data at the data warehouse is often stored in materialized views. These materialized views need to be updated when source data change. Since the propagation of updates to the views may impose a significant overhead, it is very important to update the warehouse views efficiently. Though various strategies have been proposed to maintain views in the past, they typically require too much accesses to the data sources when the changes of multiple data sources have to be reflected in the view. In this paper we propose an efficient view update strategy that uses relatively small number of accesses to the data sources. We also show the performance advantage of our method over other existing methods through experiments using TPC-D data and queries.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.318-320
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• 1998

CORBA/JAVA 기반의 멀티데이터 소스에 대한 통합 질의 환경에서 많은 사용자가 질의를 동시에 수행함으로써, 질의 처리 성능 문제가 나타난다. 이러한 문제점을 해결하기 위해서 본 논문에서는 메타데이터를 이용하여 분할된 질의에 대한 실체 뷰(Materialized view)를 관리함으로써, 질의 처리를 향상시키는 기법을 제안한다. 제안된 기법은 자주 사용되는 실체 뷰를 캐쉬에 유지시킴으로써, 재사용율을 높이고, 질의 절차를 감소시켜, 중복되는 질의의 반복 수행을 줄인다.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.325-338
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• 2004

A data warehouse stores information that is collected from multiple, heterogeneous information sources for the purpose of complex querying and analysis. Information in the warehouse is typically stored In the form of materialized views, which represent pre-computed portions of frequently asked queries. One of the most important tasks of designing a warehouse is the selection of materialized views to be maintained in the warehouse. The goal is to select a set of views so that the total query response time over all queries can be minimized while a limited amount of time for maintaining the views is given(maintenance-cost view selection problem). In this paper, we propose an efficient solution to the maintenance-cost view selection problem using a genetic algorithm for computing a near-optimal set of views. Specifically, we explore the maintenance-cost view selection problem in the context of OR view graphs. We show that our approach represents a dramatic improvement in terms of time complexity over existing search-based approaches that use heuristics. Our analysis shows that the algorithm consistently yields a solution that only has an additional 10% of query cost of over the optimal query cost while at the same time exhibits an impressive performance of only a linear increase in execution time. We have implemented a prototype version of our algorithm that is used to evaluate our approach.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.561-570
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• 2002

In order to evaluate the performance of incremental update algorithms, we perform experimental tests on the time of updating view objects. In this paper, the incremental update algorithms are evaluated on two kinds of materialized methods : materialization by value-copy and materialization by preserving object identifiers (OIDs). The result of performance evaluation shows that there is little difference in the updating time of view objects between two materialization methods. The evaluation of query processing on spatial views shows that materialization by value-copy is much better than materialization by preserving OIDs. As the results of overall performance evaluation, it is more desirable to use the incremental update method based on materialization by value-copy than the incremental update method based on materialization by preserving OIDs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1269-1275
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• 2003

This paper addresses several issues on data caching and consistency of cached data in order to process client's queries efficiently in client/server environments. For the purpose, first of all, materialized spatial views are adapted in a client side for data caching, which is called client views. Also, an incremental update scheme using derivation relationships is applied to keep cached data of clients consistent with the rest of server databases. Materialized views support efficient query processing in a client side, however, it is difficult to keep consistent their contents by the update of a server database. In this paper, we devise cost functions on query execution and view maintenance based the cost of spatial operators so as to process client's queries efficiently. When request the client's query, in our query processing scheme, the server determines whether or not materialize it as a view due to evaluation using the related cost functions. Since the scheme supports a hybrid approach based on both view materialization and re-execution, hence, it should improve query execution times in client/server environments.

• Journal of KIISE:Software and Applications
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• v.26 no.6
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• pp.780-790
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• 1999

데이터 웨어하우스는 의사결정을 위하여 여러 소스로부터 데이터를 계속 축적하는 저장고로 볼 수 있다. 따라서, 데이터웨어하우스와 지역소스사이의 일관성 유지문제는 데이터 웨어하우스 환경에서 가장 중요한 문제중의 하나로 인식되어 오고 있다. 본 논문에서는 실체 뷰를 기반으로 하는 데이터 웨어하우스 시스템에서 통신지연을 고려한 일관성 유지 알고리즘을 제안한다. 기존의 연구와 달리 제안한 알고리즘은 다중 갱신을 허용하면서도 완전 일관성을 수준을 보장한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.593-596
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• 2002

일반적으로 공간질의 처리는 복잡한 대용량 공간데이타를 대상으로 수행하기 때문에 많은 비용과 시간이 필요하다. 특히, 클라이언트/서버 공간 데이터베이스 환경에서는 클라이언트가 자주 이용하는 질의를 반복하여 처리하는 경우에 서버의 부하가 증가되며 질의 응답시간도 길어지게 된다. 따라서 클라이언트/서버 공간 데이타베이스에서 클라이언트측의 공간질의를 효율적으로 처리하기 위해서는 데이터 캐싱 등의 기법이 필요하다. 이를 위하여 본 논문에서는 클라이언트에서 자주 이용되는 공간질의를 뷰로 정의하고 클라이언트에서 실체화하는 방법을 이용하여 데이터 캐싱을 처리한다. 그리고 클라이언트에 실체화된 뷰를 최대한으로 이용하기 위하여 질의 수정 기법을 적용한 공간질의 처리 방법을 제시한다.

• Journal of KIISE:Databases
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• v.28 no.1
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• pp.31-41
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• 2001

데이터 웨어하우스 환경에서 데이터 분석을 위한 OLAP 질의에 대한 응답 시간을 줄이기 위해 실체 뷰 도입을 고려할 수 있다. 데이터 웨어하우스 환경에서 실체 뷰는 차원 테이블 과 사실 테이블의 조인으로 구성되어 있는 조인 뷰로 이루어지므로 지인 비용은 실체 뷰 선택에 영항을 미치는 가장 중요한 요소이다. 본 논문에서는 실체 뷰의 차원 속성 레벨을 이용하여 조인 테이블 추적하는 방법을 정형화하고 조인 비용을 기반으로 한 실체 뷰 선택 알고리즘을 제안한다.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.463-474
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• 2009

To analyze multidimensional data conveniently and efficiently, OLAP (On-Line Analytical Processing) systems or e-business are widely using views in a horizontal form to represent measurement values over multiple dimensions. These views can be stored as materialized views derived from several sources in order to support accesses to the integrated data. The horizontal views can provide effective accesses to complex queries of OLAP or e-business. However, we have a problem of occurring maintenance of the horizontal views since data sources are distributed over remote sites. We need a method that propagates the changes of source tables to the corresponding horizontal views. In this paper, we address incremental maintenance of horizontal views that makes it possible to reflect the changes of source tables efficiently. We first propose an overall framework that processes queries over horizontal views transformed from source tables in a vertical form. Under the proposed framework, we propagate the change of vertical tables to the corresponding horizontal views. In order to execute this view maintenance process efficiently, we keep every change of vertical tables in a differential file and then modify the horizontal views with the differential file. Because the differential file is represented as a vertical form, its tuples should be converted to those in a horizontal form to apply them to the out-of-date horizontal view. With this mechanism, horizontal views can be efficiently refreshed with the changes in a differential file without accessing source tables. Experimental results show that the proposed method improves average performance by 1.2$\sim$5.0 times over the existing methods.