使用Intel®事务性同步扩展改进内存数据库索引性能

Tomas Karnagel, R. Dementiev, Ravi Rajwar, K. Lai, T. Legler, B. Schlegel, Wolfgang Lehner
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引用次数: 63

摘要

每一代内核数量的增加对高性能内存数据库系统提出了挑战。虽然这些系统使用复杂的高级算法对查询进行分区或并行运行多个查询,但它们也利用低级同步机制来同步对内部数据库数据结构的访问。开发人员经常花费大量的开发和验证工作来改进存在这种同步的并发性。第四代酷睿™处理器中的Intel®Transactional Synchronization Extensions (Intel®TSX)使硬件能够动态地确定线程是否实际上需要同步,即使在保守使用同步的情况下也是如此。本文在一个商业数据库中评估了这种硬件支持的有效性。我们将重点介绍两种索引实现:B+树索引和SAP HANA®数据库系统中使用的Delta存储索引。我们演示了这种支持可以提高数据库数据结构(如索引树)的性能,并为开发更简单、可扩展且易于验证的算法提供了一个引人注目的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving in-memory database index performance with Intel® Transactional Synchronization Extensions
The increasing number of cores every generation poses challenges for high-performance in-memory database systems. While these systems use sophisticated high-level algorithms to partition a query or run multiple queries in parallel, they also utilize low-level synchronization mechanisms to synchronize access to internal database data structures. Developers often spend significant development and verification effort to improve concurrency in the presence of such synchronization. The Intel® Transactional Synchronization Extensions (Intel® TSX) in the 4th Generation Core™ Processors enable hardware to dynamically determine whether threads actually need to synchronize even in the presence of conservatively used synchronization. This paper evaluates the effectiveness of such hardware support in a commercial database. We focus on two index implementations: a B+Tree Index and the Delta Storage Index used in the SAP HANA® database system. We demonstrate that such support can improve performance of database data structures such as index trees and presents a compelling opportunity for the development of simpler, scalable, and easy-to-verify algorithms.
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