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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.
陳家慶
貢獻者 資科系
關鍵詞 Cloud computing; Indexing (of information); Testing; Dominance relationships; Grid partitioning; Map-reduce; Mapreduce frameworks; Parallel processing; Partitioning methods; Skyline query; Skyline query processing; Query processing
日期 2017
上傳時間 20-Jul-2017 15:28:07 (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. © 2016
關聯 Information Sciences, 375, 114-137
資料類型 article
DOI http://dx.doi.org/10.1016/j.ins.2016.09.046
dc.contributor 資科系
dc.creator (作者) Koh, Jia-Ling;Chen, Chia-Ching;Chan, Chih-Yu;Chen, Arbee L.P.en-US
dc.creator (作者) 陳家慶zh-tw
dc.date (日期) 2017
dc.date.accessioned 20-Jul-2017 15:28:07 (UTC+8)-
dc.date.available 20-Jul-2017 15:28:07 (UTC+8)-
dc.date.issued (上傳時間) 20-Jul-2017 15:28:07 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/111269-
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. © 2016
dc.format.extent 2751734 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Information Sciences, 375, 114-137
dc.subject (關鍵詞) Cloud computing; Indexing (of information); Testing; Dominance relationships; Grid partitioning; Map-reduce; Mapreduce frameworks; Parallel processing; Partitioning methods; Skyline query; Skyline query processing; Query processing
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) http://dx.doi.org/10.1016/j.ins.2016.09.046