Load Shedding for Temporal Queries over Data Streams
نویسندگان
چکیده
منابع مشابه
Load Shedding for Temporal Queries over Data Streams
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...
متن کاملLoad 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 ...
متن کاملWindow-aware Load Shedding for Data Streams
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...
متن کاملA Temporal Foundation for Continuous Queries over Data Streams
Despite the surge of research in continuous stream processing, there is still a semantical gap. In many cases, continuous queries are formulated in an enriched SQL-like query language without specifying the semantics of such a query precisely enough. To overcome this problem, we present a sound and precisely defined temporal operator algebra over data streams ensuring deterministic query result...
متن کاملClusterSheddy : Load Shedding Using Moving Clusters over Spatio-temporal Data Streams
Moving object environments are characterized by large numbers of objects continuously sending location updates. At times, data arrival rates may spike up, causing the load on the system to exceed its capacity. This may result in increased output latencies, potentially leading to invalid or obsolete answers. Dropping data randomly, the most frequently used approach in the literature for load she...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computing Science and Engineering
سال: 2011
ISSN: 1976-4677
DOI: 10.5626/jcse.2011.5.4.294