Adaptive indexing for relational keys

G. Graefe, Harumi A. Kuno
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引用次数: 52

Abstract

Adaptive indexing schemes such as database cracking and adaptive merging have been investigated to-date only in the context of range queries. These are typical for non-key columns in relational databases. For complete self-managing indexing, adaptive indexing must also apply to key columns. The present paper proposes a design and offers a first performance evaluation in the context of keys. Adaptive merging for keys also enables further improvements in B-tree indexes. First, partitions can be matched to levels in the memory hierarchy such as a CPU cache and an in-memory buffer pool. Second, adaptive merging in merged B-trees enables automatic master-detail clustering.
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关系键的自适应索引
自适应索引方案,如数据库破解和自适应合并,迄今为止只在范围查询的上下文中进行了研究。这是关系数据库中典型的非键列。对于完全的自管理索引,自适应索引也必须应用于键列。本文提出了一种基于密钥的设计方案,并给出了第一个性能评估。键的自适应合并还可以进一步改进b树索引。首先,分区可以与内存层次结构中的级别相匹配,例如CPU缓存和内存缓冲池。其次,在合并的b树中进行自适应合并,可以实现自动主细节集群。
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