将Orca优化器集成到MySQL中

A. Marathe, S. Lin, Weidong Yu, Kareem El Gebaly, P. Larson, Calvin Sun, Huawei, Calvin Sun
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引用次数: 4

摘要

MySQL查询优化器是为相对简单的oltp类型查询而设计的;对于更复杂的查询,它的局限性很快就会显现出来。例如,连接顺序优化只考虑左深计划,并使用贪婪算法选择连接顺序。与其继续修补MySQL优化器,为什么不将更复杂的查询优化委托给另一个更有能力的优化器呢?本文报告了我们将Orca优化器集成到MySQL中的经验。Orca是一个可扩展的开源查询优化器——最初由Pivotal的Greenplum dbms使用——专门为要求苛刻的分析工作负载而设计。提交给MySQL的查询被路由到Orca进行优化,结果计划被返回到MySQL执行。优化过程中需要的元数据和统计信息从MySQL的数据字典中检索。实验结果显示了显著的性能提升。在TPC-DS基准测试中,Orca的计划在99个查询中的10个查询中速度超过10倍,在3个查询中速度超过100倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating the Orca Optimizer into MySQL
The MySQL query optimizer was designed for relatively simple, OLTP-type queries; for more complex queries its limitations quickly become apparent. Join order optimization, for example, considers only left-deep plans, and selects the join order using a greedy algorithm. Instead of continuing to patch the MySQL optimizer, why not delegate optimization of more complex queries to another more capable optimizer? This paper reports on our experience with integrating the Orca optimizer into MySQL. Orca is an extensible open-source query optimizer—originally used by Pivotal’s Greenplum DBMS—specifically designed for demanding analytical workloads. Queries submitted to MySQL are routed to Orca for optimization, and the resulting plans are returned to MySQL for execution. Metadata and statistical information needed during optimization is retrieved from MySQL’s data dictionary. Experimental results show substantial performance gains. On the TPC-DS benchmark, Orca’s plans were over 10X faster on 10 of the 99 queries, and over 100X faster on 3 queries.
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