Page 440 - 《软件学报》2025年第5期

2340 软件学报 2025 年第 36 卷第 5 期

32(4): 1129–1150 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/6168.htm [doi: 10.13328/j.cnki.jos.006168]
[23] Chen LY, Chen SM. How does updatable learned index perform on non-volatile main memory? In: Proc. of the 37th IEEE Int’l Conf. on
Data Engineering Workshops. Chania: IEEE, 2021. 66–71. [doi: 10.1109/ICDEW53142.2021.00019]
[24] Zhang Z, Chu ZL, Jin PQ, Luo YP, Xie XK, Wan SH, Luo Y, Wu XF, Zou P, Zheng CY, Wu GA, Rudoff A. PLIN: A persistent learned
index for non-volatile memory with high performance and instant recovery. Proc. of the VLDB Endowment, 2022, 16(2): 243–255. [doi:
10.14778/3565816.3565826]
[25] Wang ZH, Lai BL, Zhao ZY, Lu K, Wan JG. APLI: A high-performance learned index for persistent memory. Journal of Chinese
Computer Systems, 2024, 45(9): 2110–2118 (in Chinese with English abstract). [doi: 10.20009/j.cnki.21-1106/TP.2023-0140]
[26] Kipf A, Marcus R, Van Renen A, Stoian M, Kemper A, Kraska T, Neumann T. SOSD: A benchmark for learned indexes.
arXiv:1911.13014, 2019.
[27] Xie Q, Pang CY, Zhou XF, Zhang XL, Deng K. Maximum error-bounded piecewise linear representation for online stream
approximation. The VLDB Journal, 2014, 23(6): 915–937. [doi: 10.1007/s00778-014-0355-0]
[28] Ding JL, Minhas UF, Yu J, Wang C, Do J, Li YN, Zhang HT, Chandramouli B, Gehrke J, Kossmann D, Lomet D, Kraska T. ALEX: An
updatable adaptive learned index. In: Proc. of the 2020 ACM SIGMOD Int’l Conf. on Management of Data. Portland: ACM, 2020.
969–984. [doi: 10.1145/3318464.3389711]
[29] Ferragina P, Vinciguerra G. The PGM-index: A fully-dynamic compressed learned index with provable worst-case bounds. Proc. of the
VLDB Endowment, 2020, 13(8): 1162–1175. [doi: 10.14778/3389133.3389135]
[30] Galakatos A, Markovitch M, Binnig C, Fonseca R, Kraska T. FITing-tree: A data-aware index structure. In: Proc. of the 2019 Int’l Conf.
on Management of Data. Amsterdam: ACM, 2019. 1189–1206. [doi: 10.1145/3299869.3319860]
[31] Chen JS, Chen K, Shou LD, Jiang DW, Chen G. ALERT: Workload-adaptive learned index based on radix tree. Ruan Jian Xue
Bao/Journal of Software, 2022, 33(12): 4688–4703 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/6354.htm [doi:
10.13328/j.cnki.jos.006354]
[32] Tang CZ, Wang YY, Dong ZY, Hu GS, Wang ZG, Wang MJ, Chen HB. XIndex: A scalable learned index for multicore data storage. In:
Proc. of the 25th ACM SIGPLAN Symp. on Principles and Practice of Parallel Programming. San Diego: ACM, 2020. 308–320. [doi: 10.
1145/3332466.3374547]
[33] Li PF, Hua Y, Jia JN, Zuo PF. FINEdex: A fine-grained learned index scheme for scalable and concurrent memory systems. Proc. of the
VLDB Endowment, 2021, 15(2): 321–334. [doi: 10.14778/3489496.3489512]
[34] Wu JC, Zhang Y, Chen SM, Wang J, Chen Y, Xing CX. Updatable learned index with precise positions. Proc. of the VLDB Endowment,
2021, 14(8): 1276–1288. [doi: 10.14778/3457390.3457393]
[35] Li PF, Lu H, Zhu R, Ding BL, Yang L, Pan G. DILI: A distribution-driven learned index (Extended version). arXiv:2304.08817, 2023.
[36] O’Neil P, Cheng E, Gawlick D, O’Neil E. The log-structured merge-tree (LSM-tree). Acta Informatica, 1996, 33(4): 351–385. [doi: 10.
1007/s002360050048]
[37] Yang J, Kim J, Hoseinzadeh M, Izraelevitz J, Swanson S. An empirical guide to the behavior and use of scalable persistent memory. In:
Proc. of the 18th USENIX Conf. on File and Storage Technologies. Santa Clara: USENIX Association, 2020. 169–182.
[38] Liu XY, Lin ZJ, Wang HQ. Novel online methods for time series segmentation. IEEE Trans. on Knowledge and Data Engineering, 2008,
20(12): 1616–1626. [doi: 10.1109/TKDE.2008.29]
®
[39] Intel Corporation. Intel 64 and IA-32 architectures software developer’s manual. https://www.intel.cn/content/www/cn/zh/developer/
articles/technical/intel-sdm.html
[40] Intel Corporation. Deprecating the PCOMMIT Instruction. https://www.intel.cn/content/www/cn/zh/developer/articles/technical/deprecate-
pcommit-instruction.html
[41] Wongkham C, Lu BT, Liu C, Zhong ZC, Lo E, Wang TZ. Are updatable learned indexes ready? Proc. of the VLDB Endowment, 2022,
15(11): 3004–3017. [doi: 10.14778/3551793.3551848]

附中文参考文献:
[22] 张洲, 金培权, 谢希科. 学习索引: 现状与研究展望. 软件学报, 2021, 32(4): 1129–1150. http://www.jos.org.cn/1000-9825/6168.htm
[doi: 10.13328/j.cnki.jos.006168]
[25] 王中华, 赖必梁, 赵泽阳, 鲁凯, 万继光. APLI: 一种基于持久化内存的高性能学习索引. 小型微型计算机系统, 2024, 45(9):
2110–2118. [doi: 10.20009/j.cnki.21-1106/TP.2023-0140]