论文标题
具有灵活地址空间的有效数据管理
Efficient Data Management with a Flexible Address Space
论文作者
论文摘要
数据管理应用程序使用结构化文件存储其数据，其中通常对数据进行排序以提供索引和查询。但是，在文件的地址空间中并不自然支持有关数据的现场插入和删除数据。为了避免在排序的文件中反复重写现有数据以允许进行更改，应用程序通常会采用额外的间接层，例如映射表和日志，以使更改不合适。但是，这种方法会增加访问成本和过度复杂性。 本文提出了一种新型的存储引擎，该引擎提供了灵活的地址空间，可以有效地执行任意大小的数据（例如插入和删除）的就地更新。有了这种机制，应用程序可以在线性地址空间中以最小的复杂性来管理分类的数据。广泛的评估表明，建立在其顶部的钥匙值商店可以通过简单的实现来实现高性能和效率。
Data management applications store their data using structured files in which data are usually sorted to serve indexing and queries. However, in-place insertions and removals of data are not naturally supported in a file's address space. To avoid repeatedly rewriting existing data in a sorted file to admit changes in place, applications usually employ extra layers of indirections, such as mapping tables and logs, to admit changes out of place. However, this approach leads to increased access cost and excessive complexity. This paper presents a novel storage engine that provides a flexible address space, where in-place updates of arbitrary-sized data, such as insertions and removals, can be performed efficiently. With this mechanism, applications can manage sorted data in a linear address space with minimal complexity. Extensive evaluations show that a key-value store built on top of it can achieve high performance and efficiency with a simple implementation.
