Approximate Query Processing for Big Data in Heterogeneous Databases

被引：5
作者：
Muniswamaiah, Manoj [1 ]
Agerwala, Tilak [1 ]
Tappert, Charles C. [1 ]
机构：
[1] Pace Univ, Seidenberg Sch CSIS, New York, NY 10038 USA
来源：
2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2020年
关键词：
Big Data; approximate query processing (AQP); database; query optimizer;
D O I：
10.1109/BigData50022.2020.9378310
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Big Data analytics is used in decision making. It involves heavy computation to obtain exact answers. To alleviate this problem, approximate query processing (AQP) was adopted, which provides approximate results with error bounds. The AQP models which have been proposed are supported only by a single database. In an organization, big data is stored in multiple databases that have different data models. This research aims to provide AQP as a middleware solution using query optimization for heterogeneous databases.
引用
收藏
页码：5765 / 5767
页数：3
相关论文
共 50 条
  • [11] Query Processing Techniques for Big Spatial-Keyword Data
    Mahmood, Ahmed
    Aref, Walid G.
    SIGMOD'17: PROCEEDINGS OF THE 2017 ACM INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2017, : 1777 - 1782
  • [12] A Review on Recent Trends in Query Processing and Optimization in Big Data
    Deepak Kumar
    Vijay Kumar Jha
    Wireless Personal Communications, 2022, 124 : 633 - 654
  • [13] A Solution to Query Processing Challenges Through Smart Query Processor for Big Data Analytics
    Vaidya G.M.
    Kshirsagar M.M.
    SN Computer Science, 4 (2)
  • [14] A Review on Recent Trends in Query Processing and Optimization in Big Data
    Kumar, Deepak
    Jha, Vijay Kumar
    WIRELESS PERSONAL COMMUNICATIONS, 2022, 124 (01) : 633 - 654
  • [15] Efficient Data Placement and Replication for QoS-Aware Approximate Query Evaluation of Big Data Analytics
    Xia, Qiufen
    Xu, Zichuan
    Liang, Weifa
    Yu, Shui
    Guo, Song
    Zomaya, Albert Y.
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2019, 30 (12) : 2677 - 2691
  • [16] Stream Processing of Scientific Big Data on Heterogeneous Platforms - Image Analytics on Big Data in Motion
    Najmabadi, S. M.
    Klaiber, M.
    Wang, Z.
    Baroud, Y.
    Simon, S.
    2013 IEEE 16TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE 2013), 2013, : 965 - 970
  • [17] Heterogeneous Architectures for Big Data Batch Processing in MapReduce Paradigm
    Goudarzi, Maziar
    IEEE TRANSACTIONS ON BIG DATA, 2019, 5 (01) : 18 - 33
  • [18] Building pipelines for heterogeneous execution environments for big data processing
    Wu D.
    Zhu L.
    Xu X.
    Sakr S.
    Sun D.
    Lu Q.
    1600, IEEE Computer Society (33): : 60 - 67
  • [19] Data source selection for approximate query
    Guo, Hongjie
    Li, Jianzhong
    Gao, Hong
    JOURNAL OF COMBINATORIAL OPTIMIZATION, 2022, 44 (04) : 2443 - 2459
  • [20] From Databases to Big Data
    Madden, Sam
    IEEE INTERNET COMPUTING, 2012, 16 (03) : 4 - 6
12345