Detecting Redundancy in Data Warehouse Evolution
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Keywords:
Materialized view
Representation
Data redundancy
To improve the affection of OLAP queries is an important aspect of data warehouse domain. It affects the efficiency of queries in data warehouse directly. There have been many researches articles to resolve the problem, such as PBS and PBUS algorithm. But the methods don't take the dynamic changes of the queries in to account. Base on the PBUS algorithm, a novel method is proposed to select materialized views of multidimensional data called dynamic selection Strategy. It is more effective than other solutions.
Materialized view
Online analytical processing
Dimensional modeling
Multidimensional data
Affection
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A data warehouse stores materialized views of data from one or more sources, with the purpose of efficiently implementing decision-support or OLAP queries. Materialized view selection is one of the crucial decisions in designing a data warehouse for optimal efficiency. The goal is to select an appropriate set of views that minimizes sum of the query response time and the cost of maintaining the selected views, given a limited amount of resource, e.g., materialization time, storage space, etc. In this article, we present an improved PGA algorithm to accomplish the view selection problem; the experiments show that our proposed algorithm shows it’s superior.
Materialized view
Online analytical processing
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A data warehouse stores lots of materialized views to provide efficient decision-support or OLAP queries. The view-selection problem addresses the selection of a fittest set of materialized views under the limitation of storage space forms a challenge in data warehouse research. In this paper, we present genetic algorithms to choose materialized views. We also use experiments to demonstrate the power of our approach.
Materialized view
Online analytical processing
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The process of refreshing data warehouse is often considered as a problem of the maintenance of materialized views,but in the unstable network traditional algorithms for the maintenance of materialized viesw will lead to anomaly problems.This paper presents a new algorithm for the maintenance of materialized views based on traditional data warehouse model to accomplish the refreshment of data warehouse,and we prove the feasibility of our algorithm by validation.
Materialized view
Online analytical processing
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Everyday an enormous amount of data is retrieved and transmitted. To avoid the chaos, data mining and warehousing is used. A data warehouse is a set of materialized views defined over remote source relations. These materialized views must be maintained in response to actual relation updates in the remote sources. During the initial design and evolution of data warehouse, the designer has to handle problems of selecting views to materialize in the data warehouse. A design objective can be the minimization of a cost function or a constraint of available space. AND/OR DAG expression is used to represent alternative ways of evaluating multiple queries and views and sub expression sharing. Proposed approach can be used to optimize the views for the better performance of the data warehouse
Materialized view
Dimensional modeling
Minification
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The data warehouse self-maintenance problem is substantially the problem of making materialized views self-maintainable.Because the exiting policies of materialized views self-maintenance cannot effectually reduce superfluous data in the integration and data sources of data warehouse,the response velocity of data warehouse environment will be tampered.The decomposing views system for data warehouse self-maintenance and improves the present pattern of decomposing views through deriving local views definations of single data source from the global definitions of materialized views.In conclution,the system not only can realize the functions of de-composing and rewriting materialized views,but also can heighten the efficiency of data warehouse self-maintainance.
Materialized view
Dimensional modeling
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A data warehouse stores lots of materialized views to provide an efficient decision-support or OLAP queries. The view-selection problem addresses to select a fittest set of materialized views from a variety of MVPPs (Yang, 1997) forms a challenge in data warehouse research. In this paper, we present genetic algorithm to choose materialized views. We also use experiments to demonstrate the power of our approach.
Materialized view
Online analytical processing
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A data warehouse stores large amounts of materialized views to accelerate OLAP queries. The selection of materialized view is an important decision in designing data warehouse. The paper presents an efficient algorithm for materialized views selection based on searching view in the layer of data cube. The analysis and experimental study show that the algorithm has better solution and high efficiency.
Materialized view
Online analytical processing
Data cube
Cube (algebra)
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The notion of data warehouse can be defined as subject-oriented, integrated, nonvolatile and time-variant collection of data in support of making management’s decision effectively, for the success of data warehouse accurate and timely consolidated information as well as quick query response times is the fundamental requirement. To avoid accessing from base table and increase the speed of queries posted to a Data warehouse, we can use some pre-computed intermediate results from the query processing stored in the data warehouse called materialized views. The result of effective Materialized view selection provides an efficient data warehousing system. However, the materialized view needs to be effectively maintained to keep its contents integrated and consistent with the contents of its data sources. The materialized views have maintenance cost, that’s why materialization of all views is not possible.
Materialized view
Table (database)
Dimensional modeling
Online analytical processing
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The data warehouse is a repository of information collected from multiple, possibly heterogeneous, autonomous, distributed databases. The information stored at the data warehouse is in form of views, referred to as materialized views. One of the most important decisions in designing a data warehouse is selection of right views to be materialized. So, we develop algorithms to select a set of views to materialize in data warehouse in order to minimize the total view maintenance cost under the constraint of a given query response time. We call it query cost view_ selection problem (QC_VSP). In this paper, First, we propose the cost model of QC_VSP. Second, we design algorithms for QC_VSP. Third, we use experiments do demonstrate the power of our approach.
Materialized view
Realization (probability)
Dimensional modeling
Expressive power
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