Abstract
Phase Change Memory (PCM) is a new non-volatile memory technology that is comparable to traditional DRAM with regard to read latency, and markedly superior with regard to storage density and idle power consumption. Due to these desirable characteristics, PCM is expected to play a significant role in the next generation of computing systems. However, it also has limitations in the form of expensive writes and limited write endurance. Accordingly, recent research has investigated how database engines may be redesigned to suit DBMS deployments on the new technology.
In this paper, we address the pragmatic goal of minimally altering current implementations of database operators to make them PCM-conscious, the objective being to facilitate an easy transition to the new technology. Specifically, we target the implementations of the “workhorse” database operators: sort, hash join and group-by, and rework them to substantively improve the write performance without compromising on execution times. Concurrently, we provide simple but effective estimators of the writes incurred by the new techniques, and these estimators are leveraged for integration with the query optimizer.
Our new techniques are evaluated on TPC-H benchmark queries with regard to the following metrics: number of writes, response times and wear distribution. The experimental results indicate that the PCM-conscious operators collectively reduce the number of writes by a factor of 2 to 3, while concurrently improving the query response times by about 20 % to 30 %. When combined with the appropriate plan choices, the improvements are even higher. In essence, our algorithms provide both short-term and long-term benefits. These outcomes augur well for database engines that wish to leverage the impending transition to PCM-based computing.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
In [5], we present a modified flashsort algorithm, called multi-pivot flashsort, for skewed data.
- 2.
Simulates only the application layer without the OS stack.
- 3.
The hash values of all entries within a bucket are placed contiguously.
References
Chen, S., Gibbons, P.B., Nath, S.: Rethinking database algorithms for phase change memory. In: Proceedings of 5th Biennial Conference on Innovative Data Systems Research (CIDR) (2011)
Ferreira, A., Zhou, M., Bock, S., Childers, B., Melhem, R., Mosse, D.: Increasing PCM main memory lifetime. In: Proceedings of 13th Conference on Design, Automation and Test in Europe (DATE) (2010)
Garg, V., Singh, A., Haritsa, J.R.: On improving write performance in PCM databases. Technical report TR-2015-01, DSL/SERC, IISc, dsl.serc.iisc.ernet.in/publications/report/TR/TR-2015-01.pdf (2015)
Larson, P.-A.: Grouping and duplicate elimination: Benefits of early aggregation. Microsoft Technical report (1997)
Lee, B.C., Ipek, E., Mutlu, O., Burger, D.: Architecting phase change memory as a scalable dram alternative. In: Proceeding of 36th International Symposium on Computer Architecture (ISCA) (2009)
Neubert, K.-D.: The flashsort1 algorithm (1998). http://www.drdobbs.com/database/the-flashsort1-algorithm/184410496
Qureshi, M.K., Karidis, J., Franceschini, M., Srinivasan, V., Lastras, L., Abali, B.: Enhancing lifetime and security of PCM-based main memory with start-gap wear leveling. In: Proceedings of 42nd International Symposium on Microarchitecture (MICRO) (2009)
Qureshi, M.K., Srinivasan, V., Rivers, J.A.: Scalable high performance main memory system using phase-change memory technology. In: Proceedings of 36th International Symposium on Computer Architecture (ISCA) (2009)
Ubal, R., Jang, B., Mistry, P., Schaa, D., Kaeli, D.: Multi2sim: a simulation framework for CPU-GPU computing. In: Proceedings of 21st International Conference on Parallel Architectures and Compilation Techniques (PACT) (2012)
Viglas, S.D.: Write-limited sorts and joins for persistent memory. In: Proceedings of 40th International Conference on Very Large Data Bases (VLDB) (2014)
Wild, S., Nebel, M.E.: Average case analysis of Java 7’s dual pivot quicksort. In: Epstein, L., Ferragina, P. (eds.) ESA 2012. LNCS, vol. 7501, pp. 825–836. Springer, Heidelberg (2012)
Yang, B.-D., Lee, J.-E., Kim, J.-S., Cho, J., Lee, S.-Y., Yu, B.-G.: A low power phase-change random access memory using a data-comparison write scheme. In: Proceedings of 2007 IEEE International Symposium on Circuits and Systems (ISCAS) (2007)
Zhou, P., Zhao, B., Yang, J., Zhang, Y.: A durable and energy efficient main memory using phase change memory technology. In: Proceedings of 36th International Symposium on Computer Architecture (ISCA) (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Garg, V., Singh, A., Haritsa, J.R. (2015). Towards Making Database Systems PCM-Compliant. In: Chen, Q., Hameurlain, A., Toumani, F., Wagner, R., Decker, H. (eds) Database and Expert Systems Applications. Globe DEXA 2015 2015. Lecture Notes in Computer Science(), vol 9261. Springer, Cham. https://doi.org/10.1007/978-3-319-22849-5_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-22849-5_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22848-8
Online ISBN: 978-3-319-22849-5
eBook Packages: Computer ScienceComputer Science (R0)