Mariposa: A Wide-Area Distributed Database System.

@article{DBLP:journals/vldb/StonebrakerALPSSSY96,
  author    = {Michael Stonebraker and
               Paul M. Aoki and
               Witold Litwin and
               Avi Pfeffer and
               Adam Sah and
               Jeff Sidell and
               Carl Staelin and
               Andrew Yu},
  title     = {Mariposa: A Wide-Area Distributed Database System},
  journal   = {VLDB J.},
  volume    = {5},
  number    = {1},
  year      = {1996},
  pages     = {48-63},
  ee        = {db/journals/vldb/StonebrakerALPSSSY96.html},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

The requirements of wide-area distributed database systems differ dramatically from those of local-area network systems. In a wide-area network (WAN) configuration, individual sites usually report to different system administrators, have different access and charging algorithms, install site-specific data type extensions, and have different constraints on servicing remote requests. Typical of the last point are production transaction environments, which are fully engaged during normal business hours, and cannot take on additional load. Finally, there may be many sites participating in a WAN distributed DBMS.

In this world, a single program performing global query optimization using a cost-based optimizer will not work well. Cost-based optimization does not respond well to site-specific type extension, access constraints, charging algorithms, and time-of-day constraints. Furthermore, traditional cost-based distributed optimizers do not scale well to a large number of possible processing sites. Since traditional distributed DBMSs have all used cost-based optimizers, they are not appropriate in a WAN environment, and a new architecture is required.

We have proposed and implemented an economic paradigm as the solution to these issues in a new distributed DBMS called Mariposa. In this paper, we present the architecture and implementation of Mariposa and discuss early feedback on its operating characteristics.

Key Words

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Referenced by

1. Natalija Krivokapic, Alfons Kemper, Ehud Gudes: Deadlock Detection in Distributed Database Systems: A New Algorithm and a Comparative Performance Analysis. VLDB J. 8(2): 79-100(1999)
2. Joseph M. Hellerstein, Michael Stonebraker, Rick Caccia: Independent, Open Enterprise Data Integration. IEEE Data Eng. Bull. 22(1): 43-49(1999)
3. Zachary G. Ives, Daniela Florescu, Marc Friedman, Alon Y. Levy, Daniel S. Weld: An Adaptive Query Execution System for Data Integration. SIGMOD Conference 1999: 299-310
4. Xun Cheng, Guozhu Dong, Tzekwan Lau, Jianwen Su: Data Integration by Describing Sources with Constraint Databases. ICDE 1999: 374-381
5. Peter Scheuermann, Gerhard Weikum, Peter Zabback: Data Partitioning and Load Balancing in Parallel Disk Systems. VLDB J. 7(1): 48-66(1998)
6. Laurent Amsaleg, Philippe Bonnet, Michael J. Franklin, Anthony Tomasic, Tolga Urhan: Improving Responsiveness for Wide-Area Data Access. IEEE Data Eng. Bull. 20(3): 3-11(1997)
7. Richard Hull: Managing Semantic Heterogeneity in Databases: A Theoretical Perspective. PODS 1997: 51-61
8. Sunita Sarawagi, Michael Stonebraker: Reordering Query Execution in Tertiary Memory Databases. VLDB 1996: 156-167