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OLTP through the looking glass, and what we found there
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International Conference on Management of Data archive
Proceedings of the 2008 ACM SIGMOD international conference on Management of data table of contents
Vancouver, Canada
SESSION: Research Session 20: Tuning and Probing table of contents
Pages 981-992  
Year of Publication: 2008
ISBN:978-1-60558-102-6
Authors
Stavros Harizopoulos  HP Labs, Palo Alto, CA, USA
Daniel J. Abadi  Yale University, New Haven, CT, USA
Samuel Madden  Massachusetts Institute of Technology, Cambridge, MA, USA
Michael Stonebraker  Massachusetts Institute of Technology, Cambridge, MA, USA
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Online Transaction Processing (OLTP) databases include a suite of features - disk-resident B-trees and heap files, locking-based concurrency control, support for multi-threading - that were optimized for computer technology of the late 1970's. Advances in modern processors, memories, and networks mean that today's computers are vastly different from those of 30 years ago, such that many OLTP databases will now fit in main memory, and most OLTP transactions can be processed in milliseconds or less. Yet database architecture has changed little.

Based on this observation, we look at some interesting variants of conventional database systems that one might build that exploit recent hardware trends, and speculate on their performance through a detailed instruction-level breakdown of the major components involved in a transaction processing database system (Shore) running a subset of TPC-C. Rather than simply profiling Shore, we progressively modified it so that after every feature removal or optimization, we had a (faster) working system that fully ran our workload. Overall, we identify overheads and optimizations that explain a total difference of about a factor of 20x in raw performance. We also show that there is no single "high pole in the tent" in modern (memory resident) database systems, but that substantial time is spent in logging, latching, locking, B-tree, and buffer management operations.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Stavros Harizopoulos: colleagues
Daniel J. Abadi: colleagues
Samuel Madden: colleagues
Michael Stonebraker: colleagues