| Recently, With explosive applications of information processing in sensor networks, business processing, network monitoring and security, communication, industry manufacturing, and many other areas, more and more data take the form of multiple, rapid, time-varying, possibly unpredictable and unbounded streaming data (data streams) rather than finite stored data set. In all of the applications cited above, it is not feasible to traditional technology on processing data, so data stream query processing technology becomes a new and popular topic in database research area.Query optimized is the uppermost technology of data steam technologies. Continuous queries are the usual queries over data stream whose answers are continuously produced over time unless stopped artificially. During the run time of a query, the execution environments change continuously. Meanwhile some properties of data stream itself change too. Aiming at these variational factors about environment and data stream itself, in order to improve query efficiency and system performance, the query optimized and next moving technology emerge and become a key of data stream query processing technologies.Firstly, this paper presents a novel cost model based on output rate—MaxRateModel aiming at the continuity of queries and variability of system environment and date itself; Secondly, on the basis of MaxRateModel, this paper analyzes and designs complex query optimized algorithm in order to select the optimized query plan with the most output rate; At last, this paper gives corresponding experiments, they proved validity of MaxRateModel and feasibility of query optimized strategy.Migration strategy emerges between old query plan and new query plan, because query optimized strategy needs dynamically reorder operator list during continuous query. This paper researches deeply on the traditional Moving State strategy and presents an new migration strategy—Pmoving( Parallel Moving). Experiments proved... |
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