Speculative Query Execution in Relational Databases with Graph Modelling

被引:2
|
作者
Sasak-Okon, Anna [1 ]
机构
[1] Marie Curie Sklodowska Univ, Pl Marii Curie Sklodowskiej 5, PL-20031 Lublin, Poland
关键词
D O I
10.15439/2016F123
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In computer architecture, speculative execution is the process of executing instructions ahead of their normal schedule[1]]. Grama et al.[2] introduce the concept of speculative decomposition as a possibility to execute one or more of possible branches in parallel with computation which are expected to determine the branch choice. The following paper introduces the method of speculative query execution in relational databases. Query queue can be seen as a line of sequential instructions and thus changing their order can result in some errors. Author introduce a middleware called the Speculative Layer which, based on a specific graph representation, executes some additional Speculative Queries. Results of those Speculative Queries can be used while executing queries from the queue providing a befit which is a shorter response time. The paper describes the process of graph modelling for groups of queries in order to initiate speculative computations, metrics used to evaluate Speculative Queries and experimental results for a test database and a group of input queries.
引用
收藏
页码:1383 / 1387
页数:5
相关论文
共 50 条
  • [1] Graph-Based Speculative Query Execution in Relational Databases
    Sasak-Okon, Anna
    Tudruj, Marek
    [J]. 2017 16TH INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED COMPUTING (ISPDC-2017), 2017, : 122 - 131
  • [2] Graph-Based Speculative Query Execution for RDBMS
    Sasak-Okon, Anna
    Tudruj, Marek
    [J]. PARALLEL PROCESSING AND APPLIED MATHEMATICS (PPAM 2017), PT I, 2018, 10777 : 303 - 313
  • [3] GRAPHiQL: A Graph Intuitive Query Language for Relational Databases
    Jindal, Alekh
    Madden, Samuel
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2014, : 441 - 450
  • [4] Query execution time estimation in graph databases based on graph neural networks
    He, Zhenzhen
    Yu, Jiong
    Gu, Tiquan
    Yang, Dexian
    [J]. JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2024, 36 (04)
  • [5] An Algorithm for Solving Natural Language Query Execution Problems on Relational Databases
    Enikuomehin, A. O.
    Okwufulueze, D. O.
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2012, 3 (10) : 169 - 175
  • [6] Query Processing under GLAV Mappings for Relational and Graph Databases
    Calvanese, Diego
    De Giacomo, Giuseppe
    Lenzerini, Maurizio
    Vardi, Moshe Y.
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2012, 6 (02): : 61 - 72
  • [7] Query Languages for Graph Databases
    Wood, Peter T.
    [J]. SIGMOD RECORD, 2012, 41 (01) : 50 - 60
  • [8] Query with Assumptions for Probabilistic Relational Databases
    Zhang, Caicai
    Mei, Zhuolin
    Wu, Bin
    Zhao, Zhiqiang
    Yu, Jing
    Wang, Qingqing
    [J]. TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2020, 27 (03): : 923 - 932
  • [9] Query answering in relational inductive databases
    Kerdprasop, Kittisak
    Kerdprasop, Nittaya
    Ritthongchailert, Apichai
    [J]. DEXA 2007: 18TH INTERNATIONAL CONFERENCE ON DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 2007, : 329 - +
  • [10] A FUZZY QUERY LANGUAGE FOR RELATIONAL DATABASES
    TAKAHASHI, Y
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1991, 21 (06): : 1576 - 1579