Lilian Harada

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When data are uniformly distributed, parallel hash-based join algorithm scales up well. However, the presence of data skew can cause load imbalance among the processors, significantly deteriorating its performance. In this paper we propose a dynamic skew handling algorithm which deals with this load imbalance, by detecting and handling join product skews at(More)
—Good performance and efficiency, in terms of high quality of service and resource utilization for example, are important goals in a cloud environment. Through extensive measurements of an n-tier application benchmark (RUBBoS), we show that overall system performance is surprisingly sensitive to appropriate allocation of soft resources (e.g., server thread(More)
In this paper we introduce a new query processing method for multi-attribute clustered relations. Many proposals on multi-attribute clustered relations have been done so far. However, an efficient query processing method for these relations has not been proposed and analyzed yet. The multi-attribute clustered relations treat all attributes symmetrically, at(More)