Titlebook: Database Systems for Advanced Applications; 25th International C Yunmook Nah,Bin Cui,Steven Euijong Whang Conference proceedings 2020 Sprin

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Consultants and Consultancy in Education,as schema normalization, data cleansing. In modern big data environments, data are partitioned, so that single-node FD discovery algorithms are inefficient without parallelization. However, existing parallel distributed algorithms bring huge communication costs and thus perform not well enough..To s

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Jacques Corcos,Mikolaj Przydaczy results. This query is practical in detecting prospective customers for online business in social networks. Existing work on R.GSKQ only explored efficient approaches in answering a single query per time, which could not be efficient in processing multiple queries in a query batch. In many real-li

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Heterogeneous Replicas for Multi-dimensional Data Managemention method allows different replicas to be logically identical while having different physical data layouts on the disk. We verified the efficiency of our method in a NoSQL system, Cassandra, with the TPC-H dataset and with a synthetically generated dataset. The results show that our method outperfo

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Latency-Aware Data Placements for Operational Cost Minimization of Distributed Data Centers effective algorithm, Latency-aware and operational Cost minimization Data Placement (LCDP), which partitions the data into multiple data groups according to the data access rates and greedily selects . data centers incurring the minimum cost for each data in each data group. We prove that algorithm

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