Abstract
Semi-stream processing has become an emerging area of research in the field of data stream management. One common operation in semi-stream processing is joining a stream with disk-based master data using a join operator. This join operator typically works under limited main memory and this memory is generally not large enough to hold the whole disk-based master data. Recently, a number of semi-stream join algorithms have been proposed in the literature to achieve an optimal performance but still there is room to improve the performance. In this paper we propose a novel Semi-Stream Cache Join (SSCJ) using a front-stage cache module. The algorithm takes advantage of skewed distributions, and we present results for Zipfian distributions of the type that appear in many applications. We analyze the performance of SSCJ with a well known related join algorithm, HYBRIDJOIN (Hybrid Join). We also provide the cost model for our approach and validate it with experiments.
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Naeem, M.A., Weber, G., Dobbie, G., Lutteroth, C. (2013). SSCJ: A Semi-Stream Cache Join Using a Front-Stage Cache Module. In: Bellatreche, L., Mohania, M.K. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2013. Lecture Notes in Computer Science, vol 8057. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40131-2_20
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DOI: https://doi.org/10.1007/978-3-642-40131-2_20
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