• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.797-806
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• 2006

In the data warehouse environment, materialized views are typically used to support efficient query processing. Materialized views need to be updated when source data change. Since the update of the views need impose a significant overhead, it is essential to update the views efficiently. Though various view maintenance strategies have been discussed in the past, the efficient maintenance of SPJ materialized views has not been sufficiently investigated. In this paper, we propose an efficient incremental view maintenance method for SPJ materialized views that minimizes the total accesses to data sources. The proposed method finds an optimal view maintenance strategy using a dynamic programming algorithm. We also present various experimental results that shows the efficiency of our proposed method.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.661-670
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• 2003

Materialized views which are stored views of the database offer opportunities for significant performance gain in query valuation by providing fast access to pre-computed data. The question of when and how to use a materialized view in processing a given query is a difficult one attracting a significant amount of research. Whether a materialized view can be used in answering a query depends on the relationship between the view and the query. Proposed in this paper are new ways of utilizing materialized views in answering a query. Semantic relationships are used in addition to syntactic ones. We also utilize a materialized view in answering a query even if it has relations unrelated to the query. We first show the conditions for testing whether a materialized view can be utilized in answering a query and then present the algorithms for testing the conditions and reformulating a query with a materialized view.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.327-338
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• 2001

The view can provide the user an appropriate portion of the database through data integration and filtering. Views can be materialized for query performance improvement, and in that cse, their consistency needs to be maintained against the updates of the underlying data. They can be either recomputed or incrementally refreshed by reflecting the relevant updates. Since XML could represent the structural information of the documents, for the XML materialized views, new techniques that differ from the previous ones for incrementally refreshing the relational views are required. In this paper, we propose a framework of XML materialized view management where the XML view derived from the underlying XML documents are materialized and incrementally refreshed against the updates of the underlying documents.

• The Journal of Society for e-Business Studies
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• v.11 no.4
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• pp.33-48
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• 2006

Since the emergence of XML as the standard for data exchange on the Web, XML warehousing technology is required to efficiently support Web business applications such as e-Commerce. When the RDBMS is employed as the storage for XML warehouse, XML materialized views of the XML warehouse could be provided by leveraging the materialized views of the RDBMS Because XML documents are mapped into relational tuples, an XML query defining an XML materialized view needs to be transformed into SQL. If relational materialized views were defined with the transformed SQL statements, the XML materialized view could be obtained just by XML-tagging the tuples of the corresponding relational materialized views. The foremost advantage of such a scheme is that the RDBMS does take care of XML materialized view consistency except XML tagging whenever their source XML documents are updated. In this paper, we proposed such a scheme of providing XML materialized views, and implemented it using a commercial RDBMS equipped with materialized view facility in Java on Windows 2000 Professional environment. XML documents in TPC-W, Web e-Commerce Benchmark, were used in performance experiments. The experimental results showed that our proposed scheme for XML materialized views was very effective.

• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.24-34
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• 2015

With the development of the semantic web, a large amount of data being produced nowadays is in RDF format. RDF is represented by a triple. An RDF database consisting of triples requires the high cost of join query processing. Materialized view is known as a scheme to reduce the query processing cost by accessing materialized views without accessing the database. It is physically stored the results or the intermediate results of the query processing in a storage area. In this paper, we propose a materialized view selection scheme by using decision tree to solve such a problem. The decision tree considers the size and maintenance costs of the materialized view as well as the profit of query response times. It is shown through performance evaluation that the proposed scheme increases the number of materialized views in the limited storage space and decreases the update rates of the materialized views.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.585-595
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• 2004

A query processing is a critical issue in data warehouse environment since queries on data warehouses often involve hundreds of complex operations over large volumes of data. Data warehouses therefore build a large number of materialized views to increase the system performance. Which views to materialized is an important factor on the view maintenance cost as well as the query performance. The goal of materialized view selection problem is to select an optimal set of views that minimizes total query response time in addition to the view maintenance cost. In this paper, we present an efficient solution for the materialized view selection problem. Although the optimal selection of materialized views is NP-hard problem, we developed a feasible solution by utilizing the characteristics of relational operators such as join, selection, and grouping.

• IE interfaces
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• v.16 no.2
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• pp.229-239
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• 2003

The On-Line Analytical Processing (OLAP) tools access data from the data warehouse for complex data analysis, such as multidimensional data analysis, and decision support activities. Current research has lead to new developments in all aspects of data warehousing, however, there are still a number of problems that need to be solved for making data warehousing effective. View maintenance, one of them, is to maintain view in response to updates in source data. Keeping the view consistent with updates to the base relations, however, can be expensive, since it may involve querying external sources where the base relations reside. In order to reduce maintenance costs, it is possible to maintain the views using information that is strictly local to the data warehouse. This process is usually referred to as "self-maintenance of views". A number of algorithm have been proposed for self maintenance of views where they keep some additional information in data warehouse in the form of auxiliary views. But those algorithms did not consider a consistency of materialized views using view self-maintenance. The purpose of this paper is to research consistency problem when self-maintenance of views is implemented. The proposed "conveyor algorithm" will resolved a complete consistency of materialized view using self-maintenance with considering network delay. The rationale for conveyor algorithm and performance characteristics are described in detail.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.511-537
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• 2013

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.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.387-398
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• 2003

Materialized views have received much attention for query performance improvement. They need to be refreshed whenever their underlying data sources are updated. They could be recomputed from scratch or they could be incrementally refreshed by reflecting only those portions of updates that affect them. With emergence of XML as the standard for data exchange on the Web, active research is under way on effectively storing and retrieving XML documents. In this paper, we describe a performance study on the incremental refresh of XML materialized views for the case where XML documents are stored in a relational DBMS, and XML materialized views are maintained with incremental refresh. We describe implementation of a prototype XML storage system that supports XML materialized views and their incremental refresh, and report the performance results obtained with the implemented system through a detailed set of experiments on the incremental refresh of XML materialized views. The results show that the XML view maintenance with incremental refresh outperforms the ordinary view recomputation.

• Journal of Information Processing Systems
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• v.2 no.2
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• pp.67-75
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• 2006

In order to acquire a precise and quick response to an analytical query, proper selection of the views to materialize in the data warehouse is crucial. In traditional view selection algorithms, all relations are considered for selection as materialized views. However, materializing all relations rather than a part results in much worse performance in terms of time and space costs. Therefore, we present an improved algorithm for selection of views to materialize using the clustering method to overcome the problem resulting from conventional view selection algorithms. In the presented algorithm, ASVMRT (Algorithm for Selection of Views to Materialize using Reduced Table), we first generate reduced tables in the data warehouse using clustering based on attribute-values density, and then we consider the combination of reduced tables as materialized views instead of a combination of the original base relations. For the justification of the proposed algorithm, we reveal the experimental results in which both time and space costs are approximately 1.8 times better than conventional algorithms.