Abstract
Joining data streams using various types of windows is an established method of stream processing. The limitation of window size due to memory constraint takes a heavy toll on the accuracy of the query result. Through this paper, we propose a unique windowing technique based on innovative cost functions for join query processing under memory constraints. The logical window construction is controlled through unique data structure and maintained using load shedding technique with least overhead. We applied our technique on XML streams domain and proved the effectiveness of our strategy through measuring the accuracy of the result from joining two XML streams using standard XQuery. With assumption of acceptability of an approximate solution with acceptable error bound in the face of unbounded, complex XML stream, we have tried to come up with a low overhead architecture for load shedding and tested its usefulness through a set of cost functions.
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Dash, R., Fegaras, L. (2010). A Load Shedding Framework for XML Stream Joins. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds) Database and Expert Systems Applications. DEXA 2010. Lecture Notes in Computer Science, vol 6261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15364-8_21
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DOI: https://doi.org/10.1007/978-3-642-15364-8_21
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