Sprint: a middleware for high-performance transaction processing

ABSTRACT

Sprint is a middleware infrastructure for high performance and high availability data management. It extends the functionality of a standalone in-memory database (IMDB) server to a cluster of commodity shared-nothing servers. Applications accessing an IMDB are typically limited by the memory capacity of the machine running the IMDB. Sprint partitions and replicates the database into segments and stores them in several data servers. Applications are then limited by the aggregated memory of the machines in the cluster. Transaction synchronization and commitment rely on total-order multicast. Differently from previous approaches, Sprint does not require accurate failure detection to ensure strong consistency, allowing fast reaction to failures. Experiments conducted on a cluster with 32 data servers using TPC-C and a micro-benchmark showed that Sprint can provide very good performance and scalability.

REFERENCES

• 1: Divyakant Agrawal , Gustavo Alonso , Amr El Abbadi , Ioana Stanoi, Exploiting Atomic Broadcast in Replicated Databases (Extended Abstract), Proceedings of the Third International Euro-Par Conference on Parallel Processing, p.496-503, August 26-29, 1997
• 2: Yair Amir , Ciprian Tutu, From Total Order to Database Replication, Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02), p.494, July 02-05, 2002
• 3: Philip A. Bernstein , Vassco Hadzilacos , Nathan Goodman, Concurrency control and recovery in database systems, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1987
• 4: Tushar Deepak Chandra , Sam Toueg, Unreliable failure detectors for reliable distributed systems, Journal of the ACM (JACM), v.43 n.2, p.225-267, March 1996 [doi>10.1145/226643.226647]
• 5: Sameh Elnikety , Steven Dropsho , Fernando Pedone, Tashkent: uniting durability with transaction ordering for high-performance scalable database replication, Proceedings of the ACM SIGOPS/EuroSys European Conference on Computer Systems 2006, April 18-21, 2006, Leuven, Belgium
• 6: Sameh Elnikety , Willy Zwaenepoel , Fernando Pedone, Database Replication Using Generalized Snapshot Isolation, Proceedings of the 24th IEEE Symposium on Reliable Distributed Systems (SRDS'05), p.73-84, October 26-28, 2005 [doi>10.1109/RELDIS.2005.14]
• 7: FirstSQL Inc. The FirstSQL/J in-memory database system. http://www.firstsql.com.
• 8: H. Garcia-Molina , K. Salem, Main Memory Database Systems: An Overview, IEEE Transactions on Knowledge and Data Engineering, v.4 n.6, p.509-516, December 1992 [doi>10.1109/69.180602]
• 9: Jim Gray , Leslie Lamport, Consensus on transaction commit, ACM Transactions on Database Systems (TODS), v.31 n.1, p.133-160, March 2006 [doi>10.1145/1132863.1132867]
• 10: Jim Gray , Pat Helland , Patrick O'Neil , Dennis Shasha, The dangers of replication and a solution, Proceedings of the 1996 ACM SIGMOD international conference on Management of data, p.173-182, June 04-06, 1996, Montreal, Quebec, Canada
• 11: Jim Gray , Andreas Reuter, Transaction Processing: Concepts and Techniques, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1992
• 12: Vassos Hadzilacos , Sam Toueg, Fault-tolerant broadcasts and related problems, Distributed systems (2nd Ed.), ACM Press/Addison-Wesley Publishing Co., New York, NY, 1993
• 13: Minwen Ji, Affinity-based management of main memory database clusters, ACM Transactions on Internet Technology (TOIT), v.2 n.4, p.307-339, November 2002 [doi>10.1145/604596.604599]
• 14: Bettina Kemme , Gustavo Alonso, Don't Be Lazy, Be Consistent: Postgres-R, A New Way to Implement Database Replication, Proceedings of the 26th International Conference on Very Large Data Bases, p.134-143, September 10-14, 2000
• 15: Bettina Kemme , Gustavo Alonso, A new approach to developing and implementing eager database replication protocols, ACM Transactions on Database Systems (TODS), v.25 n.3, p.333-379, Sept. 2000 [doi>10.1145/363951.363955]
• 16: Donald Kossmann, The state of the art in distributed query processing, ACM Computing Surveys (CSUR), v.32 n.4, p.422-469, Dec. 2000 [doi>10.1145/371578.371598]
• 17: Leslie Lamport, The part-time parliament, ACM Transactions on Computer Systems (TOCS), v.16 n.2, p.133-169, May 1998 [doi>10.1145/279227.279229]
• 18: Yi Lin , Bettina Kemme , Marta Patiño-Martínez , Ricardo Jiménez-Peris, Middleware based data replication providing snapshot isolation, Proceedings of the 2005 ACM SIGMOD international conference on Management of data, June 14-16, 2005, Baltimore, Maryland [doi>10.1145/1066157.1066205]
• 19: D. Morse. In-memory database web server. Dedicated Systems Magazine, (4):12--14, 2000.
• 20: Oracle parallel server for windows NT clusters. Online White Paper.
• 21: M. Tamer Özsu , Patrick Valduriez, Principles of distributed database systems (2nd ed.), Prentice-Hall, Inc., Upper Saddle River, NJ, 1999
• 22: Marta Patiño-Martínez , Ricardo Jiménez-Peris , Bettina Kemme , Gustavo Alonso, Scalable Replication in Database Clusters, Proceedings of the 14th International Conference on Distributed Computing, p.315-329, October 04-06, 2000
• 23: Marta Patiño-Martinez , Ricardo Jiménez-Peris , Bettina Kemme , Gustavo Alonso, MIDDLE-R: Consistent database replication at the middleware level, ACM Transactions on Computer Systems (TOCS), v.23 n.4, p.375-423, November 2005 [doi>10.1145/1113574.1113576]
• 24: Fernando Pedone Svend Frlund, Pronto: A Fast Failover Protocol for Off-the-Shelf Commercial Databases, Proceedings of the 19th IEEE Symposium on Reliable Distributed Systems (SRDS'00), p.176, October 16-18, 2000
• 25: Fernando Pedone , Rachid Guerraoui , Andre Schiper, Transaction Reordering in Replicated Databases, Proceedings of the 16th Symposium on Reliable Distributed Systems (SRDS '97), p.175, October 22-24, 1997
• 26: Christian Plattner , Gustavo Alonso, Ganymed: scalable replication for transactional web applications, Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware, October 18-22, 2004, Toronto, Canada
• 27: L. Rodrigues, H. Miranda, R. Almeida, J. Martins, and P. Vicente. Strong replication in the GLOBDATA middleware. In Workshop on Dependable Middleware-Based Systems, 2002.
• 28: M. Ronström and L. Thalmann. Mysql cluster architecture overview. MySQL Technical White Paper, 2004.
• 29: Ralf Schenkel , Gerhard Weikum , Norbert Weißenberg , Xuequn Wu, Federated Transaction Management with Snapshot Isolation, Selected papers from the Eight International Workshop on Foundations of Models and Languages for Data and Objects, Transactions and Database Dynamics, p.1-25, September 27-30, 1999
• 30: Rodrigo Schmidt , Fernando Pedone, Consistent Main-Memory Database Federations under Deferred Disk Writes, Proceedings of the 24th IEEE Symposium on Reliable Distributed Systems (SRDS'05), p.85-94, October 26-28, 2005 [doi>10.1109/RELDIS.2005.13]
• 31: T. Shetler. In-memory databases: The catalyst behind real-time trading systems. http://www.timesten.com/library/.
• 32: Brian White , Jay Lepreau , Leigh Stoller , Robert Ricci , Shashi Guruprasad , Mac Newbold , Mike Hibler , Chad Barb , Abhijeet Joglekar, An integrated experimental environment for distributed systems and networks, Proceedings of the 5th symposium on Operating systems design and implementation

  Due to copyright restrictions we are not able to make the PDFs for this conference available for downloading

  , December 09-11, 2002, Boston, Massachusetts [doi>10.1145/1060289.1060313]
• 33: Shuqing Wu , Bettina Kemme, Postgres-R(SI): Combining Replica Control with Concurrency Control Based on Snapshot Isolation, Proceedings of the 21st International Conference on Data Engineering (ICDE'05), p.422-433, April 05-08, 2005 [doi>10.1109/ICDE.2005.108]
• 34: Informix extended parallel server 8.3. Online White-Paper.
• 35: Clement T. Yu , Weiyi Meng, Principles of database query processing for advanced applications, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1998
• 36: Y. Zhou, P. Chen, and K. Li. Fast cluster failover using virtual memory-mapped communication. Technical Report TR-591-99. Princeton University, 1999.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.4 Systems

General Terms:
Design, Experimentation, Measurement, Performance

Keywords:
middleware, parallel databases, partitioning, replication