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Transaction reordering with application to synchronized scans
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Conference on Information and Knowledge Management archive
Proceeding of the 17th ACM conference on Information and knowledge management table of contents
Napa Valley, California, USA
POSTER SESSION: Poster session 1/industry table of contents
Pages 1335-1336  
Year of Publication: 2008
ISBN:978-1-59593-991-3
Authors
Gang Luo  IBM T.J. Watson Research Center, Hawthorne, NY, USA
Jeffrey F. Naughton  University of Wisconsin-Madison, Madison, WI, USA
Curt J. Ellmann  Teradata, Madison, WI, USA
Michael W. Watzke  Teradata, Madison, WI, USA
Sponsors
ACM: Association for Computing Machinery
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

Traditional workload management methods mainly focus on the current system status while information about the interaction between queued and running transactions is largely ignored. An exception to this is the transaction reordering method, which reorders the transaction sequence submitted to the RDBMS and improves the transaction throughput by considering both the current system status and information about the interaction between queued and running transactions. The existing transaction reordering method only considers the reordering opportunities provided by analyzing the lock conflict information among multiple transactions. This significantly limits the applicability of the transaction reordering method. In this paper, we extend the existing transaction reordering method into a general transaction reordering framework that can incorporate various factors as the reordering criteria. We show that by analyzing the resource utilization information of transactions, the transaction reordering method can also improve the system throughput by increasing the resource sharing opportunities among multiple transactions. We provide a concrete example on synchronized scans and demonstrate the advantages of our method through experiments with a commercial parallel RDBMS.


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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G. Luo, J. F. Naughton, and C. J. Ellmann et al. Transaction Reordering and Grouping for Continuous Data Loading. BIRTE 2006: 34--49. Springer Lecture Notes in Computer Science 4365. Full version available as IBM research report RC24087.
 
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G. Luo, J. F. Naughton, and C. J. Ellmann et al. Full version of this paper available as IBM research report RC24264 at pages.cs.wisc.edu/~gangluo/syncscan.pdf, 2008.

Collaborative Colleagues:
Gang Luo: colleagues
Jeffrey F. Naughton: colleagues
Curt J. Ellmann: colleagues
Michael W. Watzke: colleagues