Encyclopedia of Big Data Technologies

2019 Edition
| Editors: Sherif Sakr, Albert Y. Zomaya

Hardware-Assisted Transaction Processing

Many-core
  • Pınar TözünEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-77525-8_178

Synonyms

Definitions

Online transaction processing (OLTP) is one of the most important and demanding database applications. A transaction is a unit of work that satisfies the ACID properties (Gray and Reuter 1992). Atomicity ensures that when a transaction ends, either all or none of its effects are visible to the other transactions. Consistency guarantees that the effect of a transaction transforms the database from one consistent state to another. Isolation property gives the illusion that transactions do not interfere with each other’s effects to the database even if they run concurrently. Durability assures that the effects of complete transactions must be persistent in the database. The maintenance of these properties in the face of many concurrent client requests is a big challenge and complicates the design of transaction processing systems. Multiple...

This is a preview of subscription content, log in to check access.

References

  1. Balkesen C, Kunal N, Giannikis G, Fender P, Sundara S, Schmidt F, Wen J, Agrawal S, Raghavan A, Varadarajan V, Viswanathan A, Chandrasekaran B, Idicula S, Agarwal N, Sedlar E (2018) A many-core architecture for in-memory data processing. In: SIGMODGoogle Scholar
  2. Curino C, Jones E, Zhang Y, Madden S (2010) Schism: a workload-driven approach to database replication and partitioning. PVLDB 3:48–57Google Scholar
  3. David T, Guerraoui R, Trigonakis V (2013) Everything you always wanted to know about synchronization but were afraid to ask. In: SOSP, pp 33–48Google Scholar
  4. Dennard RH, Gaensslen FH, Yu HN, Rideout VL, Bassous E, Leblanc AR (1974) Design of ion-implanted MOSFETs with very small physical dimensions. IEEE J Solid-State Circuits 9:256–268CrossRefGoogle Scholar
  5. Diaconu C, Freedman C, Ismert E, Larson PA, Mittal P, Stonecipher R, Verma N, Zwilling M (2013) Hekaton: SQL server’s Memory-optimized OLTP engine. In: SIGMOD, pp 1243–1254Google Scholar
  6. Esmaeilzadeh H, Blem E, St Amant R, Sankaralingam K, Burger D (2011) Dark silicon and the end of multicore scaling. In: ISCA, pp 365–376Google Scholar
  7. Exadata (2015) Oracle corp.: exadata database machine. http://www.oracle.com/technetwork/database/exadata/overview/index.html
  8. Gray J, Reuter A (1992) Transaction processing: concepts and techniques. Morgan Kaufmann Publishers Inc., San FranciscozbMATHGoogle Scholar
  9. Hardavellas N, Ferdman M, Falsafi B, Ailamaki A (2011) Toward dark silicon in servers. IEEE Micro 31(4):6–15CrossRefGoogle Scholar
  10. Helland P (2007) Life beyond distributed transactions: an apostate’s opinion. In: CIDR, pp 132–141Google Scholar
  11. Johnson R, Pandis I (2013) The bionic DBMS is coming, but what will it look like? In: CIDRGoogle Scholar
  12. Johnson R, Pandis I, Stoica R, Athanassoulis M, Ailamaki A (2012) Scalability of write-ahead logging on multicore and multisocket hardware. VLDB J 21:239–263CrossRefGoogle Scholar
  13. Johnson R, Pandis I, Ailamaki A (2014) Eliminating unscalable communication in transaction processing. VLDB J 23(1):1–23CrossRefGoogle Scholar
  14. Jouppi NP, Young C, Patil N, Patterson D, Agrawal G, Bajwa R, Bates S, Bhatia S, Boden N, Borchers A, Boyle R, Cantin P, Chao C, Clark C, Coriell J, Daley M, Dau M, Dean J, Gelb B, Ghaemmaghami TV, Gottipati R, Gulland W, Hagmann R, Ho CR, Hogberg D, Hu J, Hundt R, Hurt D, Ibarz J, Jaffey A, Jaworski A, Kaplan A, Khaitan H, Killebrew D, Koch A, Kumar N, Lacy S, Laudon J, Law J, Le D, Leary C, Liu Z, Lucke K, Lundin A, MacKean G, Maggiore A, Mahony M, Miller K, Nagarajan R, Narayanaswami R, Ni R, Nix K, Norrie T, Omernick M, Penukonda N, Phelps A, Ross J, Ross M, Salek A, Samadiani E, Severn C, Sizikov G, Snelham M, Souter J, Steinberg D, Swing A, Tan M, Thorson G, Tian B, Toma H, Tuttle E, Vasudevan V, Walter R, Wang W, Wilcox E, Yoon DH (2017) In-datacenter performance analysis of a tensor processing unit. In: ISCA, pp 1–12Google Scholar
  15. Kemper A, Neumann T, Finis J, Funke F, Leis V, Mühe H, Mühlbauer T, Rödiger W (2013) Transaction processing in the hybrid OLTP&OLAP main-memory database system HyPer. IEEE DEBull 36(2):41–47Google Scholar
  16. Kongetira P, Aingaran K, Olukotun K (2005) Niagara: a 32-way multithreaded sparc processor. IEEE Micro 25(2):21–29CrossRefGoogle Scholar
  17. Lahiri T, Srihari V, Chan W, MacNaughton N, Chandrasekaran S (2001) Cache fusion: extending shared-disk clusters with shared caches. In: VLDB, pp 683–686Google Scholar
  18. Larson PA, Blanas S, Diaconu C, Freedman C, Patel JM, Zwilling M (2011) High-performance concurrency control mechanisms for main-memory databases. PVLDB 5(4):298–309Google Scholar
  19. Lee J, Kwon YS, Farber F, Muehle M, Lee C, Bensberg C, Lee JY, Lee A, Lehner W (2013) SAP HANA distributed in-memory database system: transaction, session, and metadata management. In: ICDE, pp 1165–1173Google Scholar
  20. Leis V, Kemper A, Neumann T (2014) Exploiting hardware transactional memory in main-memory databases. In: ICDE, pp 580–591Google Scholar
  21. Levandoski J, Lomet D, Sengupta S (2013) The Bw-tree: a B-tree for new hardware platforms. In: ICDE, pp 302–313Google Scholar
  22. Lomet D, Anderson R, Rengarajan TK, Spiro P (1992) How the Rdb/VMS data sharing system became fast. Technical Report CRL-92-4, DECGoogle Scholar
  23. Malviya N, Weisberg A, Madden S, Stonebraker M (2014) Rethinking main memory OLTP recovery. In: ICDE, pp 604–615Google Scholar
  24. Mohan C, Haderle D, Lindsay B, Pirahesh H, Schwarz P (1992) ARIES: a transaction recovery method supporting fine-granularity locking and partial rollbacks using write-ahead logging. ACM TODS 17(1): 94–162CrossRefGoogle Scholar
  25. Moore G (1965) Cramming more components onto integrated circuits. Electronics 38(6):82–85Google Scholar
  26. Narula N, Cutler C, Kohler E, Morris R (2014) Phase reconciliation for contended in-memory transactions. In: OSDI, pp 511–524Google Scholar
  27. Olukotun K, Nayfeh BA, Hammond L, Wilson K, Chang K (1996) The case for a single-chip multiprocessor. In: ASPLOS, pp 2–11Google Scholar
  28. Pandis I, Johnson R, Hardavellas N, Ailamaki A (2010) Data-oriented transaction execution. PVLDB 3(1):928–939Google Scholar
  29. Pandis I, Tözün P, Johnson R, Ailamaki A (2011) PLP: page latch-free shared-everything OLTP. PVLDB 4(10):610–621Google Scholar
  30. Pavlo A, Jones EPC, Zdonik S (2011) On predictive modeling for optimizing transaction execution in parallel OLTP systems. PVLDB 5(2):85–96Google Scholar
  31. Pavlo A, Curino C, Zdonik S (2012) Skew-aware automatic database partitioning in shared-nothing, parallel OLTP systems. In: SIGMOD, pp 61–72Google Scholar
  32. Porobic D, Pandis I, Branco M, Tözün P, Ailamaki A (2012) OLTP on hardware Islands. PVLDB 5(11):1447–1458Google Scholar
  33. Porobic D, Liarou E, Tözün P, Ailamaki A (2014) ATraPos: adaptive transaction processing on hardware Islands. In: ICDE, pp 688–699Google Scholar
  34. Putnam A, Caulfield A, Chung E, Chiou D, Constantinides K, Demme J, Esmaeilzadeh H, Fowers J, Gopal GP, Gray J, Haselman M, Hauck S, Heil S, Hormati A, Kim JY, Lanka S, Larus J, Peterson E, Pope S, Smith A, Thong J, Xiao PY, Burger D (2014) A reconfigurable fabric for accelerating large-scale datacenter services. In: ISCA, pp 13–24Google Scholar
  35. Schall D, Härder T (2015) Dynamic physiological partitioning on a shared-nothing database cluster. In: ICDE, pp 1095–1106Google Scholar
  36. Serafini M, Mansour E, Aboulnaga A, Salem K, Taha R, Minhas UF (2014) Accordion: elastic scalability for database systems supporting distributed transactions. PVLDB 7(12):1035–1046Google Scholar
  37. Sewall J, Chhugani J, Kim C, Satish N, Dubey P (2011) PALM: parallel architecture-friendly latch-free modifications to B+Trees on many-core processors. PVLDB 4(11):795–806Google Scholar
  38. Stonebraker M, Madden S, Abadi DJ, Harizopoulos S, Hachem N, Helland P (2007) The end of an architectural era: (it’s time for a complete rewrite). In: VLDB, pp 1150–1160Google Scholar
  39. Tözün P, Pandis I, Johnson R, Ailamaki A (2013) Scalable and dynamically balanced shared-everything OLTP with physiological partitioning. VLDB J 22(2): 151–175CrossRefGoogle Scholar
  40. Tu S, Zheng W, Kohler E, Liskov B, Madden S (2013) Speedy transactions in multicore in-memory databases. In: SOSP, pp 18–32Google Scholar
  41. Wu L, Lottarini A, Paine TK, Kim MA, Ross KA (2014) Q100: the architecture and design of a database processing unit. In: ASPLOS, pp 255–268Google Scholar
  42. Yu X, Bezerra G, Pavlo A, Devadas S, Stonebraker M (2014) Staring into the abyss: an evaluation of concurrency control with one thousand cores. PVLDB 8(3):209–220Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.IT University of CopenhagenCopenhagenDenmark