Load Shedding using Window Aggregation Queries on Data Streams
نویسندگان
چکیده
منابع مشابه
Load Shedding using Window Aggregation Queries on Data Streams
The processes of extracting knowledge structures for continuous, rapid records are known as the Data Stream Mining. The main issue in stream mining is handling streams of elements delivered rapidly which makes it infeasible to store everything in active storage. To overcome this problem of handling voluminous data we exposed a novel load shedding system using window based aggregate function of ...
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Data stream management systems may be subject to higher input rates than their resources can handle. In this case, results get delayed and Quality of Service (QoS) at system outputs may fall below acceptable levels. Load shedding addresses this problem by allowing data loss in exchange for reduced latency. Drop operators are placed at carefully chosen points in a query plan, in order to relieve...
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Enhancing continuous queries over data streams with temporal functions and predicates enriches the expressive power of those queries. While traditional continuous queries retrieve only the values of attributes, temporal continuous queries retrieve the valid time intervals of those values as well. Correctly evaluating such queries requires the coalescing of adjacent timestamps for value-equivale...
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In this thesis, we are working on the optimized execution of very large number of continuous queries de ned on data streams. Our scope includes both classical query optimization issues adapted to the stream data environment as well as analysis and resolution of overload situations by intelligently discarding data based on applicationdependent quality of service (QoS) information. This paper ser...
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Random samples are common in data streams applications due to limitations in data sources and transmission lines, or to load-shedding policies. Here we introduce a formal error model and show that, besides providing accurate estimates, it improves query answer accuracy by exploiting past statistics. The method is general, robust in the presence of concept drift, and minimises uncertainties due ...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2012
ISSN: 0975-8887
DOI: 10.5120/8598-2362