基于马尔可夫分析的物化视图替换
Materialized View Replacement using Markovs Analysis
摘要：
物化视图在以数据为中心的大型应用程序中用于加快查询处理。物化视图的效率取决于对现有物化视图的查询结果的发现程度。物化视图的构造遵循不同的方法。因此，物化视图的功效取决于形成这些视图所基于的方法。物化视图的构造通常是耗时的，并且在一定时间之后，当查询的性质改变时，物化视图的性能降低。在这种情况下，可以从头开始构建新的物化视图，也可以升级现有视图。物化视图的新构造具有较高的时间复杂度，因此修改已有视图是一种较好的解决方案，在物化视图维护方案下对物化视图的修改过程进行了分类。物化视图维护是一个连续的过程，可以对系统进行调优，以确保性能保持恒定。如果一个物化视图的构造过程不被物化视图的维护方案所支持，系统将遭受性能下降。本文提出了一种新的物化视图维护方案，利用马尔可夫分析来保证性能的一致性。这里选择马尔可夫分析来预测稳态概率超过初始概率。
英文摘要：
Materialized view is used in large data centric applications to expedite query processing. The efficiency of materialized view depends on degree of result found against the queries over the existing materialized views. Materialized views are constructed following different methodologies. Thus the efficacy of the materialized views depends on the methodology based on which these are formed. Construction of materialized views are often time consuming and moreover after a certain time the performance of the materialized views degrade when the nature of queries change. In this situation either new materialized views could be constructed from scratch or the existing views could be upgraded. Fresh construction of materialized views has higher time complexity hence the modification of the existing views is a better solution.Modification process of materialized view is classified under materialized view maintenance scheme. Materialized view maintenance is a continuous process and the system could be tuned to ensure a constant rate of performance. If a materialized view construction process is not supported by materialized view maintenance scheme that system would suffer from performance degradation. In this paper a new materialized view maintenance scheme is proposed using markovs analysis to ensure consistent performance. Markovs analysis is chosen here to predict steady state probability over initial probability.
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