基于缓存敏感B+树的节点压缩技术

Rize Jin, Tae-Sun Chung
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引用次数: 3

摘要

关注缓存的索引已经研究了十年。这些索引结构可以增强数据局部性并减少缓存丢失。缓存敏感B+-tree (CSB+-tree)是用于主存数据库系统的最先进的高性能索引树。但是,在最坏的情况下,CSB+-tree的空间利用率可能会下降到25%。本文的主要贡献是利用压缩机制提高CSB+-树的空间效率。我们进行了实验研究。结果表明,压缩的CSB+-树通过利用现代硬件的优势,可以显著节省空间,并为搜索和删除操作带来额外的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Node Compression Techniques Based on Cache-Sensitive B+-Tree
Cache-conscious indices have been researched for a decade. These index structures can enhance data locality and reduce cache misses. Cache-Sensitive B+-tree (CSB+-tree) is a state-of-the-art, high performance index tree for main-memory database systems. However, in the worst case, the space utilization of CSB+-tree can fall to 25%. The main contribution of this paper is to improve space efficiency of CSB+-tree by using compression mechanisms. We have conducted experimental studies. Results show that the compressed CSB+-trees can yield significant space savings with additional benefits for search and delete operations by utilizing the superiority of modern hardware.
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