10.5555/1926129.1926141guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedings
ARTICLE

Scalable transactions in the cloud: partitioning revisited

ABSTRACT

Cloud computing is becoming one of the most used paradigms to deploy highly available and scalable systems. These systems usually demand the management of huge amounts of data, which cannot be solved with traditional nor replicated database systems as we know them. Recent solutions store data in special key-value structures, in an approach that commonly lacks the consistency provided by transactional guarantees, as it is traded for high scalability and availability. In order to ensure consistent access to the information, the use of transactions is required. However, it is well-known that traditional replication protocols do not scale well for a cloud environment. Here we take a look at current proposals to deploy transactional systems in the cloud and we propose a new system aiming at being a step forward in achieving this goal. We proceed to focus on data partitioning and describe the key role it plays in achieving high scalability.

References

  1. Gray, J., Helland, P., O'Neil, P.E., Shasha, D.: The dangers of replication and a solution. In: Jagadish, H.V., Mumick, I.S. (eds.) SIGMOD Conference, pp. 173- 182. ACM Press, New York (1996). Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Brewer, E.A.: Towards robust distributed systems (abstract). In: Proceedings of the Nineteenth Annual ACM Symposium on Principles of Distributed Computing, PODC 2000, p. 7. ACM, New York (2000). Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Gilbert, S., Lynch, N.A.: Brewer's conjecture and the feasibility of consistent, available, partition-tolerant web services. SIGACT News 33(2), 51-59 (2002). Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. von Eicken, T.: Right scale blog: Animoto's facebook scale-up (2010), http://blog.rightscale.com/2008/04/23/animoto-facebook-scale-up/Google ScholarGoogle Scholar
  5. Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: A distributed storage system for structured data. ACM Trans. Comput. Syst. 26(2) (2008). Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. DeCandia, G., Hastorun, D., Jampani, M., Kakulapati, G., Lakshman, A., Pilchin, A., Sivasubramanian, S., Vosshall, P., Vogels, W.: Dynamo: amazon's highly available key-value store. In: Bressoud, T.C., Kaashoek, M.F. (eds.) SOSP, pp. 205-220. ACM, New York (2007). Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Cooper, B.F., Ramakrishnan, R., Srivastava, U., Silberstein, A., Bohannon, P., Jacobsen, H.A., Puz, N., Weaver, D., Yerneni, R.: Pnuts: Yahoo!'s hosted data serving platform. PVLDB 1(2), 1277-1288 (2008). Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Aguilera, M.K., Merchant, A., Shah, M.A., Veitch, A.C., Karamanolis, C.T.: Sinfonia: A new paradigm for building scalable distributed systems. ACM Trans. Comput. Syst. 27(3) (2009). Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Das, S., Agrawal, D., Abbadi, A.E.: Elastras: An elastic transactional data store in the cloud. In: HotCloud 2009 Workshop at USENIX (2009). Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Das, S., Agarwal, S., Agrawal, D., Abbadi, A.E.: Elastras: An elastic, scalable, and self managing transactional database for the cloud. Technical Report UCSB-CS- 2010-04, University of California, Santa Barbara (2010).Google ScholarGoogle Scholar
  11. Jones, E.P.C., Abadi, D.J., Madden, S.: Low overhead concurrency control for partitioned main memory databases. In: Elmagarmid, A.K., Agrawal, D. (eds.) SIGMOD Conference, pp. 603-614. ACM, New York (2010). Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Pandis, I., Johnson, R., Hardavellas, N., Ailamaki, A.: Data-oriented transaction execution. Technical Report CMU-CS-10-101, Carnegie Mellon University (2010).Google ScholarGoogle Scholar
  13. Burrows, M.: The chubby lock service for loosely-coupled distributed systems. In: OSDI, USENIX Association, pp. 335-350 (2006). Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Lamport, L.: The part-time parliament. ACM Trans. Comput. Syst. 16(2), 133-169 (1998). Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Pedone, F.: The Database State Machine and Group Communication Issues. PhD thesis, École Polytechnique Fédérale de Lausanne, Switzerland (1999).Google ScholarGoogle Scholar
  16. Schneider, F.B.: Implementing fault-tolerant services using the state machine approach: A tutorial. ACM Comput. Surv. 22(4), 299-319 (1990). Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Gray, J., Reuter, A.: Transaction Processing: Concepts and Techniques. Morgan Kaufmann, San Francisco (1993). Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Bernstein, P.A., Hadzilacos, V., Goodman, N.: Concurrency Control and Recovery in Database Systems. Addison-Wesley, Reading (1987). Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Lin, Y., Kemme, B., Jiménez-Peris, R., Patiñno-Martínez, M., Armendáriz-Iñnigo, J.E.: Snapshot isolation and integrity constraints in replicated databases. ACM Trans. Database Syst. 34(2) (2009). Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Berenson, H., Bernstein, P.A., Gray, J., Melton, J., O'Neil, E.J., O'Neil, P.E.: A critique of ANSI SQL isolation levels. In: Carey, M.J., Schneider, D.A. (eds.) SIGMOD Conference, pp. 1-10. ACM Press, New York (1995). Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Plattner, C., Alonso, G., Özsu, M.T.: Extending DBMSs with satellite databases. VLDB J. 17(4), 657-682 (2008). Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Lin, Y., Kemme, B., Patiñno-Martínez, M., Jiménez-Peris, R.: Middleware based data replication providing snapshot isolation. In: Özcan, F. (ed.) SIGMOD Conference, pp. 419-430. ACM, New York (2005). Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Elnikety, S., Zwaenepoel, W., Pedone, F.: Database replication using generalized snapshot isolation. In: SRDS, pp. 73-84. IEEE Computer Society, Los Alamitos (2005). Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Chockler, G., Keidar, I., Vitenberg, R.: Group communication specifications: a comprehensive study. ACM Comput. Surv. 33(4), 427-469 (2001). Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Jiménez-Peris, R., Patiño-Martínez, M., Alonso, G., Kemme, B.: Are quorums an alternative for data replication? ACM Trans. Database Syst. 28(3), 257-294 (2003). Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Serrano, D., Patiño-Martínez, M., Jiménez-Peris, R., Kemme, B.: Boosting database replication scalability through partial replication and 1-copy-snapshot-isolation. In: PRDC, pp. 290-297. IEEE Computer Society, Los Alamitos (2007). Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Vogels, W.: Eventually consistent. Commun. ACM 52(1), 40-44 (2009). Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Sobel, W., Subramanyam, S., Sucharitakul, A., Nguyen, J., Wong, H., Patil, S., Fox, A., Patterson, D.: Cloudstone: Multi-platform, multi-language benchmark and measurement tools for web 2.0. In: 1st Workshop on Cloud Computing (CCA 2008) (2008).Google ScholarGoogle Scholar
  29. Gartner: Gartner identifies top ten disruptive technologies for 2008 to 2012 (2010), http://www.gartner.com/it/page.jsp?id=681107Google ScholarGoogle Scholar

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0

    Other Metrics

About Cookies On This Site

We use cookies to ensure that we give you the best experience on our website.

Learn more

Got it!