Parallelizing Computations of Full Disjunctions

被引:2
|
作者
Paganelli, Matteo [1 ]
Beneventano, Domenico [1 ]
Guerra, Francesco [1 ]
Sottovia, Paolo [1 ,2 ]
机构
[1] DIEF UNIMORE, Via Vivarelli 10, I-41125 Modena, Italy
[2] DISI UNITN, Via Sommar 9, I-38123 Povo, TN, Italy
关键词
Full disjunction; Parallel computing; MapReduce;
D O I
10.1016/j.bdr.2019.07.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In relational databases, the full disjunction operator is an associative extension of the full outerjoin to an arbitrary number of relations. Its goal is to maximize the information we can extract from a database by connecting all tables through all join paths. The use of full disjunctions has been envisaged in several scenarios, such as data integration, and knowledge extraction. One of the main limitations in its adoption in real business scenarios is the large time its computation requires. This paper overcomes this limitation by introducing a novel approach PARAFD, based on parallel computing techniques, for implementing the full disjunction operator in an exact and approximate version. Our proposal has been compared with state of the art algorithms, which have also been re-implemented for performing in parallel. The experiments show that the time performance outperforms existing approaches. Finally, we have experimented the full disjunction as a collection of documents indexed by a textual search engine. In this way, we provide a simple technique for performing keyword search over relational databases. The results obtained against a benchmark show high precision and recall levels even compared with the existing proposals. (C) 2019 Elsevier Inc. All rights reserved.
引用
收藏
页码:18 / 31
页数:14
相关论文
共 50 条
  • [1] Parallelizing Sequential Graph Computations
    Fan, Wenfei
    Xu, Jingbo
    Wu, Yinghui
    Yu, Wenyuan
    Jiang, Jiaxin
    Zheng, Zeyu
    Zhang, Bohan
    Cao, Yang
    Tian, Chao
    SIGMOD'17: PROCEEDINGS OF THE 2017 ACM INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2017, : 495 - 510
  • [2] Parallelizing Sequential Graph Computations
    Fan, Wenfei
    Yu, Wenyuan
    Xu, Jingbo
    Zhou, Jingren
    Luo, Xiaojian
    Yin, Qiang
    Lu, Ping
    Cao, Yang
    Xu, Ruiqi
    ACM TRANSACTIONS ON DATABASE SYSTEMS, 2018, 43 (04):
  • [3] Parallelizing and Optimizing Sparse Tensor Computations
    Baskaran, Muthu Manikandan
    Meister, Benoit
    Lethin, Richard
    PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON SUPERCOMPUTING, (ICS'14), 2014, : 179 - 179
  • [4] Parallelizing Irregular Computations for Molecular Docking
    Solis-Vasquez, Leonardo
    Santos-Martins, Diogo
    Tillack, Andreas F.
    Koch, Andreas
    Eberhardt, Jerome
    Forli, Stefano
    PROCEEDINGS OF IA3 2020: 2020 IEEE/ACM 10TH WORKSHOP ON IRREGULAR APPLICATIONS: ARCHITECTURES AND ALGORITHMS (IA3), 2020, : 12 - 21
  • [5] PARALLELIZING VISIBILITY COMPUTATIONS ON TRIANGULATED TERRAINS
    DEFLORIANI, L
    MONTANI, C
    SCOPIGNO, R
    INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SYSTEMS, 1994, 8 (06): : 515 - 531
  • [6] GRAPE: Parallelizing Sequential Graph Computations
    Fan, Wenfei
    Xu, Jingbo
    Wu, Yinghui
    Yu, Wenyuan
    Jiang, Jiaxin
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2017, 10 (12): : 1889 - 1892
  • [7] Technical Perspective The Power of Parallelizing Computations
    Larus, James
    COMMUNICATIONS OF THE ACM, 2016, 59 (10) : 84 - 84
  • [8] Parameterized Diamond Tiling for Parallelizing Stencil Computations
    Wijesinghe, T.
    Senevirathne, K.
    Siriwardhana, C.
    Visitha, W.
    Jayasena, S.
    Rusira, T.
    Hall, M.
    2017 3RD INTERNATIONAL MORATUWA ENGINEERING RESEARCH CONFERENCE (MERCON), 2017, : 99 - 104
  • [9] Parallelizing message schedules to accelerate the computations of hash functions
    Gueron, Shay
    Krasnov, Vlad
    JOURNAL OF CRYPTOGRAPHIC ENGINEERING, 2012, 2 (04) : 241 - 253
  • [10] An incremental algorithm for computing ranked full disjunctions
    Cohen, Sara
    Sagiv, Yehoshua
    JOURNAL OF COMPUTER AND SYSTEM SCIENCES, 2007, 73 (04) : 648 - 668