Abstract
Different types of data skew can result in load imbalance in the context of parallel joins under the shared nothing architecture. We study one important type of skew, join product skew (JPS). A static approach based on frequency classes is proposed which takes for granted the data distribution of join attribute values. It comes from the observation that the join selectivity can be expressed as a sum of products of frequencies of the join attribute values. As a consequence, an appropriate assignment of join sub-tasks that takes into consideration the magnitude of the frequency products can alleviate the join product skew. Motivated by the aforementioned remark, we propose an algorithm, called Handling Join Product Skew (HJPS), to handle join product skew.
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Kyritsis, V., Lekeas, P.V., Souliou, D., Afrati, F. (2012). A New Framework for Join Product Skew. In: Lacroix, Z., Vidal, M.E. (eds) Resource Discovery. RED 2010. Lecture Notes in Computer Science, vol 6799. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27392-6_1
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DOI: https://doi.org/10.1007/978-3-642-27392-6_1
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