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Preprocessing for Fast Refreshing Materialized Views in DB2

机译:预处理在DB2中快速刷新的物化视图

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Materialized views (MVs) are used in databases and data warehouses to greatly improve query performance. In this context, a great challenge is to exploit commonalities among the views and to employ multi-query optimization techniques in order to derive an efficient global evaluation plan for refreshing the MVs concurrently. IBM DB2~® Universal Database™ (DB2 UDB) provides two query matching techniques, query stacking and query sharing, to exploit commonalities among the MVs, and to construct an efficient global evaluation plan. When the number of MVs is large, memory and time restrictions prevent us from using both query matching techniques in constructing efficient global plans. We suggest an approach that applies the query stacking and query sharing techniques in different steps. The query stacking technique is applied first, and the outcome is exploited to define groups of MVs. The number of MVs in each group is restricted. This allows the query sharing technique to be applied only within groups in a second step. Finally, the query stacking technique is used again to determine an efficient global evaluation plan. An experimental evaluation shows that the execution time of the plan generated by our approach is very close to that of the plan generated using both query matching techniques without restriction. This result is valid no matter how big the database is.
机译:物化视图(MVS)用于数据库和数据仓库,以大大提高查询性能。在这种情况下,一个巨大的挑战是利用视图中的共同性并采用多查询优化技术,以推导出高效的全局评估计划,用于同时刷新MV。 IBM DB2~®通用数据库™(DB2 UDB)提供了两个查询匹配技术,查询堆叠和查询共享,以利用MV之间的共同性,并构建高效的全局评估计划。当MV的数量很大时,内存和时间限制阻止我们在构建高效的全球计划中使用查询匹配技术。我们建议一种方法,它在不同的步骤中应用查询堆叠和查询共享技术。查询叠置技术首先被施加,并且所述结果被利用来定义MV的基团。限制每个组中的MVS数量。这使得能够在第二步骤中仅在基团施加的查询共享技术。最后,再次使用查询堆叠技术来确定有效的全局评估计划。实验评估表明,我们的方法产生的计划的执行时间非常接近使用没有限制的查询匹配技术生成的计划的。无论数据库有多大,此结果都是有效的。

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