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Database Architecture Optimized for the New Bottleneck: Memory Access
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Peter A. Boncz,
Stefan Manegold, and
Martin L. Kersten
View Paper (PDF)
Return to Main-Memory Caching
In the past decade, advances in speed of commodity CPUs have far out-paced advances in memory latency. Main-memory access is therefore incresasingly a performance bottleneck for many computer applications, including database systems. In this article, we use a simple scan test to show the severe impact of this bottleneck. The insights gained are translated into guidelines for database architecture; in terms of both data structures and algorithms. We discuss how vertically fragmented data structures optimize cache performance on sequential data access. We then focus on equi-join, typically a random-access operation, and introduce radix algorithms for partitioned hash-join. The performance of these algorithms is quantified using a detailed analytical model that incorporates memory access cost. Experiments that validate this model were performed on the Monet database System. We obtained exact statistics on events like TLB misses, L1 and L2 cache misses, by using hardware performance counters found in modern CPUs. Using our cost model, we show how the carefully tuned memory access pattern of our radix algorithms make them perform well, which is confirmed by experimental results.
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@inproceedings{DBLP:conf/vldb/BonczMK99,
author = {Peter A. Boncz and
Stefan Manegold and
Martin L. Kersten},
editor = {Malcolm P. Atkinson and
Maria E. Orlowska and
Patrick Valduriez and
Stanley B. Zdonik and
Michael L. Brodie},
title = {Database Architecture Optimized for the New Bottleneck: Memory
Access},
booktitle = {VLDB'99, Proceedings of 25th International Conference on Very
Large Data Bases, September 7-10, 1999, Edinburgh, Scotland,
UK},
publisher = {Morgan Kaufmann},
year = {1999},
isbn = {1-55860-615-5},
pages = {54-65},
crossref = {DBLP:conf/vldb/99},
bibsource = {DBLP, http://dblp.uni-trier.de} } },
Copyright(C) 2000 ACM
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