Adaptive indexing for relational keys

Goetz Graefe, Harumi Kuno
2010 2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010)  
databases, indexes, storage systems, B-trees, adaptive merging, database cracking 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
more » ... s 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. External Posting 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.
doi:10.1109/icdew.2010.5452743 dblp:conf/icde/GraefeK10 fatcat:sv5kfcsxh5bunleof4yckv44lm