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Adaptive Merging on Phase Change Memory (2204.01667v3)

Published 4 Apr 2022 in cs.DB and cs.ET

Abstract: Indexing is a well-known database technique used to facilitate data access and speed up query processing. Nevertheless, the construction and modification of indexes are very expensive. In traditional approaches, all records in the database table are equally covered by the index. It is not effective, since some records may be queried very often and some never. To avoid this problem, adaptive merging has been introduced. The key idea is to create index adaptively and incrementally as a side-product of query processing. As a result, the database table is indexed partially depending on the query workload. This paper faces a problem of adaptive merging for phase change memory (PCM). The most important features of this memory type are: limited write endurance and high write latency. As a consequence, adaptive merging should be investigated from the scratch. We solve this problem in two steps. First, we apply several PCM optimization techniques to the traditional adaptive merging approach. We prove that the proposed method (eAM) outperforms a traditional approach by 60%. After that, we invent the framework for adaptive merging (PAM) and a new PCM-optimized index. It further improves the system performance by 20% for databases where search queries interleave with data modifications.

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References (35)
  1. Updating a Cracked Database. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, SIGMOD ’07. ACM, New York, NY, USA. ISBN 978-1-59593-686-8, 2007 pp. 413–424. 10.1145/1247480.1247527.
  2. Database Cracking. In: CIDR 2007, Third Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 7-10, 2007, Online Proceedings. 2007.
  3. Self-organizing Tuple Reconstruction in Column-stores. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, SIGMOD ’09. ACM, New York, NY, USA. ISBN 978-1-60558-551-2, 2009 pp. 297–308. 10.1145/1559845.1559878.
  4. Cracking the Database Store. In: In CIDR. 2005.
  5. Graefe G, Kuno H. Self-selecting, Self-tuning, Incrementally Optimized Indexes. In: Proceedings of the 13th International Conference on Extending Database Technology, EDBT ’10. ACM, New York, NY, USA. ISBN 978-1-60558-945-9, 2010 pp. 371–381. 10.1145/1739041.1739087.
  6. Main memory adaptive indexing for multi-core systems. In: Tenth International Workshop on Data Management on New Hardware, DaMoN 2014, Snowbird, UT, USA, June 23, 2014. 2014 pp. 3:1–3:10. 10.1145/2619228.2619231.
  7. Merging What’s Cracked, Cracking What’s Merged: Adaptive Indexing in Main-Memory Column-Stores. PVLDB, 2011. 4(9):585–597. 10.14778/2002938.2002944.
  8. Optimized Adaptive Hybrid Indexing for In-memory Column Stores. In: Hong B, Meng X, Chen L, Winiwarter W, Song W (eds.), Database Systems for Advanced Applications - 18th International Conference, DASFAA 2013, International Workshops: BDMA, SNSM, SeCoP, Wuhan, China, April 22-25, 2013. Proceedings, volume 7827 of Lecture Notes in Computer Science. Springer, 2013 pp. 101–111. 10.1007/978-3-642-40270-8_9.
  9. Enhancing Lifetime and Security of PCM-based Main Memory with Start-gap Wear Leveling. In: Proceedings of the 42Nd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 42. ACM, New York, NY, USA. ISBN 978-1-60558-798-1, 2009 pp. 14–23. 10.1145/1669112.1669117.
  10. Wear-Aware Algorithms for PCM-Based Database Buffer Pools. In: Chen Y, Balke W, Xu J, Xu W, Jin P, Lin X, Tang TY, Hwang E (eds.), Web-Age Information Management - WAIM 2014 International Workshops: BigEM, HardBD, DaNoS, HRSUNE, BIDASYS, Macau, China, June 16-18, 2014 Revised Selected Papers, volume 8597 of Lecture Notes in Computer Science. Springer, 2014 pp. 165–176. 10.1007/978-3-319-11538-2_16.
  11. Efficient Space Management and Wear Leveling for PCM-Based Storage Systems. In: Wang G, Zomaya AY, Pérez GM, Li K (eds.), Algorithms and Architectures for Parallel Processing - 15th International Conference, ICA3PP 2015, Zhangjiajie, China, November 18-20, 2015. Proceedings, Part IV, volume 9531 of Lecture Notes in Computer Science. Springer, 2015 pp. 784–798. 10.1007/978-3-319-27140-8_54.
  12. Rethinking Database Algorithms for Phase Change Memory. In: CIDR 2011, Fifth Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 9-12, 2011, Online Proceedings. www.cidrdb.org, 2011 pp. 21–31. URL http://cidrdb.org/cidr2011/Papers/CIDR11\_Paper3.pdf.
  13. Viglas SD. Write-limited Sorts and Joins for Persistent Memory. Proc. VLDB Endow., 2014. 7(5):413–424. 10.14778/2732269.2732277.
  14. Jurga M, Macyna W. Implementation of the Aggregated R-Tree for Phase Change Memory. In: Hartmann S, Ma H, Hameurlain A, Pernul G, Wagner RR (eds.), Database and Expert Systems Applications - 29th International Conference, DEXA 2018, Regensburg, Germany, September 3-6, 2018, Proceedings, Part II, volume 11030 of Lecture Notes in Computer Science. Springer, 2018 pp. 301–309. 10.1007/978-3-319-98812-2_26.
  15. DPTree: Differential Indexing for Persistent Memory. Proc. VLDB Endow., 2019. 13(4):421–434. 10.14778/3372716.3372717.
  16. Redesign the Memory Allocator for Non-Volatile Main Memory. JETC, 2017. 13(3):49:1–49:26. 10.1145/2997651.
  17. Scalable high performance main memory system using phase-change memory technology. In: Keckler SW, Barroso LA (eds.), 36th International Symposium on Computer Architecture (ISCA 2009), June 20-24, 2009, Austin, TX, USA. ACM, 2009 pp. 24–33. 10.1145/1555754.1555760.
  18. Power management of hybrid DRAM/PRAM-based main memory. In: Stok L, Dutt ND, Hassoun S (eds.), Proceedings of the 48th Design Automation Conference, DAC 2011, San Diego, California, USA, June 5-10, 2011. ACM, 2011 pp. 59–64. 10.1145/2024724.2024738.
  19. A Durable and Energy Efficient Main Memory Using Phase Change Memory Technology. In: Proceedings of the 36th Annual International Symposium on Computer Architecture, ISCA ’09. ACM, New York, NY, USA. ISBN 978-1-60558-526-0, 2009 pp. 14–23. 10.1145/ 1555754.1555759.
  20. MigrantStore: Leveraging Virtual Memory in DRAM-PCM Memory Architecture. CoRR, 2015. abs/1504.04297. 1504.04297, URL http://arxiv.org/abs/1504.04297.
  21. Wear-leveling for PCM main memory on embedded system via page management and process scheduling. In: 2014 IEEE 20th International Conference on Embedded and Real-Time Computing Systems and Applications, Chongqing, China, August 20-22, 2014. IEEE Computer Society, 2014 pp. 1–9. 10.1109/RTCSA.2014.6910513.
  22. Curling-PCM: Application-specific wear leveling for phase change memory based embedded systems. In: 18th Asia and South Pacific Design Automation Conference, ASP-DAC 2013, Yokohama, Japan, January 22-25, 2013. IEEE, 2013 pp. 279–284. 10.1109/ASPDAC.2013.6509609.
  23. A Survey on PCM Lifetime Enhancement Schemes. ACM Comput. Surv., 2019. 52(4):76:1–76:38. 10.1145/3332257.
  24. Making B+-tree Efficient in PCM-based Main Memory. In: Proceedings of the 2014 International Symposium on Low Power Electronics and Design, ISLPED ’14. ACM, New York, NY, USA. ISBN 978-1-4503-2975-0, 2014 pp. 69–74. 10.1145/2627369.2627630.
  25. XB+-Tree: A Novel Index for PCM/DRAM-Based Hybrid Memory. In: Cheema MA, Zhang W, Chang L (eds.), Databases Theory and Applications - 27th Australasian Database Conference, ADC 2016, Sydney, NSW, Australia, September 28-29, 2016, Proceedings, volume 9877 of Lecture Notes in Computer Science. Springer, 2016 pp. 357–368. 10.1007/978-3-319-46922-5_28.
  26. FPTree: A Hybrid SCM-DRAM Persistent and Concurrent B-Tree for Storage Class Memory. In: Özcan F, Koutrika G, Madden S (eds.), Proceedings of the 2016 International Conference on Management of Data, SIGMOD Conference 2016, San Francisco, CA, USA, June 26 - July 01, 2016. ACM, 2016 pp. 371–386. 10.1145/2882903.2915251.
  27. PCR*-Tree: PCM-Aware R*-Tree. J. Inf. Sci. Eng., 2017. 33(5):1359–1374. URL http://jise.iis.sinica.edu.tw/JISESearch/pages/View/PaperView.jsf?keyId=158\_2074.
  28. The Uncracked Pieces in Database Cracking. Proc. VLDB Endow., 2013. 7(2):97–108. 10.14778/2732228.2732229.
  29. Macyna W, Kukowski M. Partially Indexing on Flash Memory. In: Database and Expert Systems Applications - 30th International Conference, DEXA 2019, Linz, Austria, August 26-29, 2019, Proceedings, Part I. 2019 pp. 95–105. 10.1007/978-3-030-27615-7_7.
  30. The Log-Structured Merge-Tree (LSM-Tree). Acta Informatica, 1996. 33(4):351–385. 10.1007/s002360050048.
  31. Optimizing B+-Tree for PCM-Based Hybrid Memory. In: Proceedings of the 19th International Conference on Extending Database Technology, EDBT 2016, Bordeaux, France, March 15-16, 2016, Bordeaux, France, March 15-16, 2016. 2016 pp. 662–663. 10.5441/002/edbt.2016.75.
  32. Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores. Proc. VLDB Endow., 2012. 5(6):502–513. 10.14778/2168651.2168652.
  33. An experimental evaluation and analysis of database cracking. VLDB J., 2016. 25(1):27–52. 10.1007/s00778-015-0397-y.
  34. Database cracking: fancy scan, not poor man’s sort! In: Kemper A, Pandis I (eds.), Tenth International Workshop on Data Management on New Hardware, DaMoN 2014, Snowbird, UT, USA, June 23, 2014. ACM, 2014 pp. 4:1–4:8. 10.1145/2619228.2619232.
  35. An analysis and comparison of database cracking kernels. In: Lehner W, Salem K (eds.), Proceedings of the 14th International Workshop on Data Management on New Hardware, Houston, TX, USA, June 11, 2018. ACM, 2018 pp. 10:1–10:10. 10.1145/3211922.3211930.
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