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Data Morphing: An Adaptive, Cache-Conscious Storage Technique

机译:数据变形:一种自适应的,具有缓存意识的存储技术

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The number of processor cache misses has a critical impact on the performance of DBMSs running on servers with large main-memory configurations. In turn, the cache utilization of database systems is highly dependent on the physical organization of the records in main-memory. A recently proposed storage model, called PAX, was shown to greatly improve the performance of sequential file-scan operations when compared to the commonly implemented N-ary storage model. However, the PAX storage model can also demonstrate poor cache utilization for other common operations, such as index scans. Under a workload of heterogenous database operations, neither the PAX storage model nor the N-ary storage model is optimal. In this paper, we propose a flexible data storage technique called Data Morphing. Using Data Morphing, a cache-efficient attribute layout, called a partition, is first determined through an analysis of the query workload. This partition is then used as a template for storing data in a cache-efficient way. We present two algorithms for computing partitions, and also present a versatile storage model that accommodates the dynamic reorganization of the attributes in a file. Finally, we experimentally demonstrate that the Data Morphing technique provides a significant performance improvement over both the traditional N-ary storage model and the PAX model.
机译:处理器高速缓存未命中的数量对在具有大型主内存配置的服务器上运行的DBMS的性能具有至关重要的影响。反过来,数据库系统的缓存利用率在很大程度上取决于主内存中记录的物理组织。与常用的N元存储模型相比,最近提出的一种称为PAX的存储模型被证明可以大大提高顺序文件扫描操作的性能。但是,PAX存储模型还可以证明其他常见操作(例如索引扫描)的缓存利用率很低。在异构数据库操作的工作负载下,PAX存储模型和N元存储模型都不是最佳的。在本文中,我们提出了一种灵活的数据存储技术,称为数据变形。使用数据变形,首先通过对查询工作负载的分析来确定高速缓存有效的属性布局(称为分区)。然后将该分区用作以缓存有效方式存储数据的模板。我们提出了两种用于计算分区的算法,并且还提出了一种通用的存储模型,该模型可以适应文件中属性的动态重组。最后,我们通过实验证明,数据变形技术相对于传统的N元存储模型和PAX模型都提供了显着的性能改进。

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