Self-monitoring query execution for adaptive query processing

被引:13
作者
Gounaris, A [1 ]
Paton, NW [1 ]
Fernandes, AAA [1 ]
Sakellariou, R [1 ]
机构
[1] Univ Manchester, Dept Comp Sci, Manchester M13 9PL, Lancs, England
基金
英国工程与自然科学研究理事会;
关键词
query monitoring; adaptive query processing; query execution; operators;
D O I
10.1016/j.datak.2004.05.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Adaptive query processing generally involves a feedback loop comprising monitoring, assessment and response. So far, individual proposals have tended to group together an approach to monitoring, a means of assessment, and a form of response. However, there are many benefits in decoupling these three phases, and in constructing generic frameworks for each of them. To this end, this paper discusses monitoring of query plan execution as a topic in its own right, and advocates an approach based on self-monitoring algebraic operators. This approach is shown to be generic and independent of any specific adaptation mechanism, easily implementable and portable, sufficiently comprehensive, appropriate for heterogeneous distributed environments, and more importantly, capable of driving on-the-fly adaptations of query plan execution. An experimental evaluation of the overheads and of the quality of the results obtained by monitoring is also presented. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:325 / 348
页数:24
相关论文
共 31 条
  • [11] GRAEFE G, 1990, SIGMOD REC, V19, P102, DOI 10.1145/93605.98720
  • [12] Haas PJ, 1999, SIGMOD RECORD, VOL 28, NO 2 - JUNE 1999, P287, DOI 10.1145/304181.304208
  • [13] HELLERSTEIN JM, 2000, IEEE DATA ENG B, V23, P7
  • [14] IOANNIDIS Y, 1991, P ACM SIGMOD C, P268
  • [15] Query optimization
    Ioannidis, YE
    [J]. ACM COMPUTING SURVEYS, 1996, 28 (01) : 121 - 123
  • [16] Ives ZG, 1999, SIGMOD RECORD, VOL 28, NO 2 - JUNE 1999, P299, DOI 10.1145/304181.304209
  • [17] KABRA N, 1998, P ACM SIGMOD INT C M, P106
  • [18] The state of the art in distributed query processing
    Kossmann, D
    [J]. ACM COMPUTING SURVEYS, 2000, 32 (04) : 422 - 469
  • [19] MADDEN S, 2000, P ACM SIGMOD 2002, P49
  • [20] Ng K. W., 1999, Proceedings. Eleventh International Conference on Scientific and Statistical Database Management, P264, DOI 10.1109/SSDM.1999.787642