有效解决数据缺失问题的聚集查询算法-计算机工程与应用.PDF

72 2018 ，54（24 ） Computer Engineering and Applications 计算机工程与应用 有效解决数据缺失问题的聚集查询算法 用 1 1 1 1 1 2 孙 舟 ，田贺平 ，潘鸣宇 ，王伟贤 ，张 禄 ，陈 光 应 1 1 1 1 1 2 SUN Zhou , TIAN Heping , PAN Mingyu , WANG Weixian , ZHANG Lu , CHEN Guang 与 1. 国网北京电力公司，北京 100075 程 2. 南瑞集团，北京 102299 g 1.State Grid Beijing Electric Power Company, Beijing 100075, China r 工 o 2.NARI Group, Beijing 102299, China . 机 j a SUN Zhou, TIAN Heping, PAN Mingyu, et al. Aggregation query processing algorithm for effective solving data 算 e missing problem. Computer Engineering and Applications, 2018, 54 （24 ）：72-78. c 计 w. Abstract ：Recently, both industrial and academic worlds suffer from the problem of incomplete data. Incomplete data （missing value ）significantly reduces the value of data. Existing missing data imputation techniques with high time com- w plexity hardly meet the requirements of real-time applications in the big data era. This paper focuses on how to efficiently w evaluate aggregation queries on incomplete data. Specifically, missing data imputation techniques are integrated with the sample-based approximate query processing. Besides, a block-level sampling strategy is adoptd to speed up the query pro- cessing. All missing values are imputed in the sample and an unbiased estimator of the truth aggregate result is derived. Experiments on both real dataset and synthetic dataset show that the method can produce significant improvements in speed while providing good quality ans