Abstract
With the dramatic increases in performance requirement of computer hardware and decreases in its cost in recent years, the relevant research in main-memory database is becoming more and more popular and has a prosperous future. Log-based recovery, which is one of its most important research directions, is a set of problems accompanied by volatile memory. Its problem of stagnation in memory/CPU resulted from the slow I/O speed of non-volatile storage now needs to be addressed urgently. However, there is no specific platform for log-based recovery research. So the study aims to address this issue.
For the specific platform issue, we design and implement a simulation platform called RecoS. RecoS aims at an implementation of recovery sub-system of the main-memory database. It uses cluster substrate to simulate more real data storage and developed interfaces for a variety of recovery strategies. We propose three log compression methods in this paper: (1) the dictionary encoding, (2) the indirectly encoding with no threshold limit and (3) the indirect encoding with a threshold limit. We also adapt ARIES and command logging on the platform, which represents physical and logical logging respectively, focusing on their recovery process and some important details. Regard the recovery platform as the core to investigate the performance of the recovery platform with different load by using different log sets.
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Notes
- 1.
This paper is partially supported by the National Natural Science Foundation of China No. 61370154 and No. 61332006, and the Fundamental Research Funds for the Central Universities No. N140404009.
References
Woo, S., Ho Kim, M., Joon Lee, Y.: Accommodating logical logging under fuzzy checkpointing in main memory databases. In: Proceedings of the International Database Engineering and Applications Symposium. IDEAS 1997. IEEE, pp. 53–62 (1997)
Kallman, R., Kimura, H., Natkins, J., et al.: H-store: a high-performance, distributed main memory transaction processing system. Proc. VLDB Endowment 1(2), 1496–1499 (2008)
Stonebraker, M., Madden, S., Abadi, D.J., et al.: The end of an architectural era: (it’s time for a complete rewrite). In: Proceedings of the 33rd International Conference on Very Large Data Bases. VLDB Endowment 2007, pp. 1150–1160 (2007)
Yao, C., Agrawal, D., Chen, G., et al.: Adaptive logging: optimizing logging and recovery costs in distributed In-memory databases. In: International Conference (2016)
Mohan, C., Haderle, D., Lindsay, B., et al.: ARIES: a transaction recovery method supporting fine-granularity locking and partial rollbacks using write-ahead logging. ACM Trans. Database Syst. (TODS) 17(1), 94–162 (1992)
Stonebraker, M., Weisberg, A.: The VoltDB main memory DBMS. IEEE Data Eng. Bull. 36(2), 21–27 (2013)
Salem, K., Garcia-Molina, H.: Checkpointing memory-resident databases. In: Proceedings of the Fifth International Conference on Data Engineering, pp. 452–462. IEEE (1989)
Elnozahy, E.N., Johnson, D.B., Zwaenepoel, W.: The performance of consistent checkpointing. In: Proceedings of the 11th Symposium on Reliable Distributed Systems, pp. 39–47. IEEE(1992)
Malviya, N., Weisberg, A., Madden, S., et al.: Rethinking main memory OLTP recovery. In: 2014 IEEE 30th International Conference on Data Engineering (ICDE), pp. 604–615. IEEE (2014)
Stonebraker, M., Abadi, D.J., Batkin, A., et al.: C-store: a column-oriented DBMS. In: Proceedings of the 31st International Conference on Very Large Data Bases. VLDB Endowment, pp. 553–564 (2005)
Abadi, D.J., Boncz, P.A., Harizopoulos, S.: Column-oriented database systems. Proc. VLDB Endowment 2(2), 1664–1665 (2009)
Garcia-Molina, H., Salem, K.: Main memory database systems: an overview. IEEE Trans. Knowl. Data Eng. 4(6), 509–516 (1992)
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Wu, G., Wang, X., Jiang, Z., Cui, J., Wang, B. (2016). Compression Algorithms for Log-Based Recovery in Main-Memory Data Management. In: Li, YF., et al. Semantic Technology. JIST 2016. Lecture Notes in Computer Science(), vol 10055. Springer, Cham. https://doi.org/10.1007/978-3-319-50112-3_5
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DOI: https://doi.org/10.1007/978-3-319-50112-3_5
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