期刊文献+

列数据库的SQL查询语句编译与优化 被引量:2

Compilation and Optimization of SQL Query Statements on Column-oriented Database
下载PDF
导出
摘要 基于多核CPU和GPU异构平台的列数据库可用于海量数据和复杂查询,但其优化主要集中在底层,并且后端的执行序列只能通过手工硬编码生成,不能适应多样的SQL查询语句。针对该问题,设计并实现一个将SQL查询语句自动转化成执行序列的编译器,研究多个复杂表达式中的公共子表达式消除和原语依赖图合并方法。与手工编码的比较结果表明,该编译器能够提高算术表达式的计算速度,缩短执行SQL查询语句的时间。 A column-oriented database based on a heterogeneous platform of multi-core CPU and GPU can be used for mass data and complex queries. However, the optimization in this database is mainly on physical level and execution sequence for its back-end can only be generated manually, resulting in hard adaptation to varieties of SQL query statements. To solve this problem, this paper designs and implements a compiler that translates SQL query statements into execution sequence. It studies Common Subexpression Elimination(CSE) method in multiple complex expressions and merging method of multiple primitive dependency graphs. Comparing the results with situations where no compiler is used in GSQL, it can be found that this compiler can improve speed of computing multiple complex expressions efficiently and reduce time of processing multiple SQL query statements.
出处 《计算机工程》 CAS CSCD 2013年第6期60-65,共6页 Computer Engineering
基金 广东省科技计划基金资助项目(2011A010801008 2011A090200122 2011A090200027)
关键词 列数据库 原语 编译器 依赖图 公共子表达式消除 查询优化 column-oriented database primitive compiler dependency graph Common Subexpression Elimination(CSE) queryoptimization
  • 相关文献

参考文献1

二级参考文献17

  • 1Idreos S, Kersten M L, Manegold S. Self-organizing tuple reconstruction in column stores[C]//Proceedings of the 35th SIGMOD International Conference. Providence, Rhode, Island: ACM, 2009.
  • 2Ailamaki A, Dewitt D J, Hill M D, et al. Weaving rela- tions for cache performance[C]//Proceedings of the 27th Very Large Data Base Conference. San Francisco: Morgan Kaufmann Publishers Inc, 2001 : 169-180.
  • 3Hankins R, Patel A. Data morphing: An adaptive, cache-conscious storage technique[C]//Proceedings of the 29th Very Large Data Base Conference. Berlin, Germany: VLDB Endowment, 2003: 417-428.
  • 4Turner P M J, Hammond R, Cotton E A DBMS for large statistical database[C]//Proceedings of the 5th Very Large Data Base Conference. Rio de Janeiro, Brazil: VLDB Endowment, 1979: 319-237.
  • 5Copeland G P, Khoshafian S N. A decomposition storage model[C]//Proceedings of SIGMOD International Conference. Austin, Taxes: ACM, 1985: 268-279.
  • 6Boncz P, Zukowski M, Nes N. MonetDB/X100: Hyper- pipelining query execution[C]//Proceedings of the 2nd Biennial Conference on Innovative Data System Research (CIDR 2005). Asilomar, CA: ACM, 2005.
  • 7Carcia-Molina H, Ullman J D, Widom J. Database system implementation[M]. America: Prentice Hall, 2000: 238-302.
  • 8Zhou Lizhu. SQL Server database principle-Design and implementation[M]. Beijing: Tsinghua University Press, 2004.
  • 9Dittrich J. Architecture and implementation of database systems[EB/OL] .[2010-02].http://www.inf.ethz.ch/personal/jensdi/.
  • 10Ivanova M G., Kersten M L, Nes N J, et al. An architecture for recycling intermediates in a column store[C]// Proceedings of the 35th SIGMOD International Conference Providence, Rhode Island, USA: ACM, 2009: 309-320.

共引文献3

同被引文献8

引证文献2

二级引证文献25

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部