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OPTIMIZED INTENTION FOR CONTINUOUS QUERIES IN THE ACTIVE DATA AGGREGATION NETWORK WITH COST MODEL 基于代价模型的主动数据聚合网络中连续查询意图优化
Pub Date : 2013-07-21 DOI: 10.47893/ijcct.2015.1300
R. Indumathi, N. Mookhambika
Within an RDBMS streams of changes to the data and reporting when the result of a query defined over the data changes. These queries are referred to as the continuous queries since they continually produce results whenever new data arrives or existing data changes. To make online decision we require monitoring the continuous queries. Here the aim is to introduce the low-cost, scalable technique to answer continuous aggregation queries using a network of aggregators of dynamic data items. There is significant work in systems that can efficiently deliver the relevant updates automatically and also to provide for getting the optimal set of sub queries with their incoherency bounds which satisfies client query’s coherency requirement with least number of refresh messages sent from aggregators to the client. For optimal query execution divide the query into sub-queries and evaluate each sub-query at a judiciously chosen data aggregator. The main purpose is to response the client with the least number of tasks with the help of random query selection. Random query selection means for the user submitted query the relevant queries, sub queries are generated. A query cost model which can be used to estimate the number of messages required to satisfy the client specified incoherency bound.
在RDBMS中,对数据的更改流和对数据定义的查询结果更改时的报告。这些查询被称为连续查询,因为每当新数据到达或现有数据更改时,它们都会不断地产生结果。为了做出在线决策,我们需要监控连续的查询。本文的目的是介绍一种低成本、可扩展的技术,使用动态数据项的聚合器网络来回答连续的聚合查询。在系统中,如何有效地自动交付相关的更新,以及如何以最少的刷新消息从聚合器发送到客户端来满足客户端查询的一致性要求,从而获得具有非相干边界的最优子查询集是非常重要的工作。为了优化查询执行,将查询划分为子查询,并在明智选择的数据聚合器上评估每个子查询。其主要目的是借助随机查询选择以最少的任务响应客户机。随机查询选择是指对用户提交的查询进行相关查询,生成子查询。查询成本模型,可用于估计满足客户端指定的非一致性边界所需的消息数量。
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International Journal of Information Technology & Computer Sciences Perspectives
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