论文标题

在虚拟内存中倾向于自适应存储视图

Towards Adaptive Storage Views in Virtual Memory

论文作者

Schuhknecht, Felix, Henneberg, Justus

论文摘要

传统上,DBMS将其存储层与索引层分开。当存储层物理地实现数据库并为其提供低级访问方法时,顶部的索引层可以更快地定位搜索的条目。尽管这清楚地将问题分开了,但它也为已经复杂的执行路径增加了一定程度的间接水平。在这项工作中,我们提出了一种替代设计:我们自然地通过将自适应的粗粒状索引方案直接集成到存储层中来自然地融合它们。我们通过利用OS提供的虚拟内存管理子系统的工具:在最低级别上,我们以物理主内存的形式实现了数据库内容。最重要的是,我们允许创建任意的许多虚拟内存存储视图,这些存储视图将其映射到具有某些感兴趣的数据库的子集。该创建作为查询处理的副产品完全适应。为了加快查询答案,我们将每个查询自动路由到最合适的虚拟视图。这样,我们自然地将存储层组成核心,并逐渐改善提供的扫描性能。

Traditionally, DBMSs separate their storage layer from their indexing layer. While the storage layer physically materializes the database and provides low-level access methods to it, the indexing layer on top enables a faster locating of searched-for entries. While this clearly separates concerns, it also adds a level of indirection to the already complex execution path. In this work, we propose an alternative design: Instead of conservatively separating both layers, we naturally fuse them by integrating an adaptive coarse-granular indexing scheme directly into the storage layer. We do so by utilizing tools of the virtual memory management subsystem provided by the OS: On the lowest level, we materialize the database content in form of physical main memory. On top of that, we allow the creation of arbitrarily many virtual memory storage views that map to subsets of the database having certain properties of interest. This creation happens fully adaptively as a side-product of query processing. To speed up query answering, we route each query automatically to the most fitting virtual view(s). By this, we naturally index the storage layer in its core and gradually improve the provided scan performance.

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