Abstract
High contention frequently explodes in E-commerce scenario when promotions are held. However, modern multi-core main-memory databases cannot achieve ideal performance under high contention. Transactions contending for the same resources must be executed serially in traditional architecture to guarantee correctness, which severely chokes database management systems. In this paper, we propose to optimize the transaction processing scheme for highly contended E-commerce workloads. First, we analyze the characteristics of these workloads in detail. Second, we design to filter ineffective operations at IO layer instead of sending them to executing layer, considering the limited number of items involved in the promotion. Third, we make out a homogeneous operation merging scheme to share database execution resources, e.g., locks, and improve parallelization. We implement a prototype, Filmer, to demonstrate our idea. Filmer launches filtering and merging for contended transactions to make full use of system resources and improve parallelization. Extensive experiments show that filtering and merging improve the throughput by up to 1.95\(\times \) and 2.55\(\times \) respectively.
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References
Alomari, M., Cahill, M., Fekete, A., Rohm, U.: The cost of serializability on platforms that use snapshot isolation. In: ICDE, pp. 576–585. IEEE (2008)
Bernstein, P.A., Hadzilacos, V., Goodman, N.: Concurrency Control and Recovery in Database Systems. Addison-Wesley, Boston (1987)
Candea, G., Polyzotis, N., Vingralek, R.: Predictable performance and high query concurrency for data analytics. VLDB 20(2), 227–248 (2011)
Council, T.P.P.: TPC-C benchmark (1992). https://www.tpc.org/tpcc/
DeCandia, G., et al.: Dynamo: Amazon’s highly available key-value store. In: SOSP, pp. 205–220 (2007)
Faleiro, J.M., Abadi, D.J.: Rethinking serializable multiversion concurrency control. VLDB 8(11), 1190–1201 (2015)
Giannikis, G., Alonso, G., Kossmann, D.: SharedDB: killing one thousand queries with one stone. VLDB 5(6), 526–537 (2012)
Huang, G., et al.: X-Engine: an optimized storage engine for large-scale e-commerce transaction processing. In: SIGMOD, pp. 651–665 (2019)
Makreshanski, D., Giannikis, G., Alonso, G., Kossmann, D.: MQJoin: efficient shared execution of main-memory joins. VLDB 9(6), 480–491 (2016)
Makreshanski, D., Giceva, J., Barthels, C., Alonso, G.: BatchDB: efficient isolated execution of hybrid OLTP+OLAP workloads for interactive applications. In: SIGMOD, pp. 37–50 (2017)
Narula, N., Cutler, C., Kohler, E., Morris, R.: Phase reconciliation for contended in-memory transactions. In: OSDI, pp. 511–524 (2014)
Oracle: Oracle Database 12c: Advanced Queuing Whitepaper (2015)
Pandis, I., Johnson, R., Hardavellas, N., Ailamaki, A.: Data-oriented transaction execution. VLDB 3(1–2), 928–939 (2010)
Prasaad, G., Cheung, A., Suciu, D.: Handling highly contended OLTP workloads using fast dynamic partitioning. In: International Conference on Management of Data, SIGMOD/PODS 2020 (2020)
Rehrmann, R., Binnig, C., Böhm, A., Kim, K., Lehner, W., Rizk, A.: OLTPshare: the case for sharing in OLTP workloads. VLDB 11(12), 1769–1780 (2018)
Ren, K., Faleiro, J.M., Abadi, D.J.: Design principles for scaling multi-core OLTP under high contention. In: SIGMOD, pp. 1583–1598 (2016)
Rodeh, O.: B-trees, shadowing, and clones. TOS 3(4), 2 (2008)
Sellis, T.K.: Multiple-query optimization. TODS 13(1), 23–52 (1988)
Tian, B., Huang, J., Mozafari, B., Schoenebeck, G.: Contention-aware lock scheduling for transactional databases. VLDB 11(5), 648–662 (2018)
Wang, T., Kimura, H.: Mostly-optimistic concurrency control for highly contended dynamic workloads on a thousand cores. VLDB 10(2), 49–60 (2016)
Zhang, C., Li, Y., Zhang, R., Qian, W., Zhou, A.: Benchmarking on intensive transaction processing. Front. Comp. Sci. 14(5), 1–18 (2020)
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Zhang, C., Zhang, S., Chen, T., Zhang, R., Liu, K. (2024). An Optimized Solution for Highly Contended Transactional Workloads. In: Hermanns, H., Sun, J., Bu, L. (eds) Dependable Software Engineering. Theories, Tools, and Applications. SETTA 2023. Lecture Notes in Computer Science, vol 14464. Springer, Singapore. https://doi.org/10.1007/978-981-99-8664-4_23
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DOI: https://doi.org/10.1007/978-981-99-8664-4_23
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