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題名 MapReduce skyline query processing with partitioning and distributed dominance tests
作者 Koh, Jia-Ling
Chen, Chia-Ching
Chan, Chih-Yu
Chen, Arbee L.P.
貢獻者 資科系
關鍵詞 Cloud computing; Skyline query computation; Parallel processing; MapReduce
日期 2017-01
上傳時間 22-Nov-2017 16:25:54 (UTC+8)
摘要 In this paper, in order to efficiently process skyline queries by the MapReduce framework, two algorithms are proposed to prevent the bottleneck of centrally finding the global skyline from the local skylines. The proposed algorithms aim to reduce the number of dominance tests, which check whether a data point is dominated by another data point, and perform the necessary dominance tests in parallel. The first algorithm uses a grid-based and an angle-based partitioning schemes to divide the data space into segments for finding the local skyline data points. Two sets of rules are designed respectively for the two partitioning methods to reduce the number of dominance tests among the local skyline data points to find the skyline data points. The second algorithm uses the skyline data points discovered from sample data points to filter out most non-skyline data points in the mappers. For the remaining data points, the dominance relationship between the grid-partitioning segments is used to further reduce the number of dominance tests performed in both the mapper and the reducer. The experiment results show that the proposed two algorithms have significant improvement on response time compared with the related works.
關聯 Information Sciences, Volume 375, Pages 114-137
資料類型 article
DOI https://doi.org/10.1016/j.ins.2016.09.046
dc.contributor 資科系
dc.creator (作者) Koh, Jia-Lingen_US
dc.creator (作者) Chen, Chia-Chingen_US
dc.creator (作者) Chan, Chih-Yuen_US
dc.creator (作者) Chen, Arbee L.P.en_US
dc.date (日期) 2017-01
dc.date.accessioned 22-Nov-2017 16:25:54 (UTC+8)-
dc.date.available 22-Nov-2017 16:25:54 (UTC+8)-
dc.date.issued (上傳時間) 22-Nov-2017 16:25:54 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/114857-
dc.description.abstract (摘要) In this paper, in order to efficiently process skyline queries by the MapReduce framework, two algorithms are proposed to prevent the bottleneck of centrally finding the global skyline from the local skylines. The proposed algorithms aim to reduce the number of dominance tests, which check whether a data point is dominated by another data point, and perform the necessary dominance tests in parallel. The first algorithm uses a grid-based and an angle-based partitioning schemes to divide the data space into segments for finding the local skyline data points. Two sets of rules are designed respectively for the two partitioning methods to reduce the number of dominance tests among the local skyline data points to find the skyline data points. The second algorithm uses the skyline data points discovered from sample data points to filter out most non-skyline data points in the mappers. For the remaining data points, the dominance relationship between the grid-partitioning segments is used to further reduce the number of dominance tests performed in both the mapper and the reducer. The experiment results show that the proposed two algorithms have significant improvement on response time compared with the related works.en_US
dc.format.extent 2751734 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Information Sciences, Volume 375, Pages 114-137en_US
dc.subject (關鍵詞) Cloud computing; Skyline query computation; Parallel processing; MapReduceen_US
dc.title (題名) MapReduce skyline query processing with partitioning and distributed dominance testsen_US
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/j.ins.2016.09.046
dc.doi.uri (DOI) https://doi.org/10.1016/j.ins.2016.09.046