Mariposa: a wide-area distributed database system

  • Authors:

  • Michael Stonebraker;Paul M. Aoki;Witold Litwin;Avi Pfeffer;Adam Sah;Jeff Sidell;Carl Staelin;Andrew Yu

  • Affiliations:

  • Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1776, USA;Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1776, USA;Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1776, USA;Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1776, USA;Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1776, USA;Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1776, USA;Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1776, USA;Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1776, USA

  • Venue:
  • The VLDB Journal — The International Journal on Very Large Data Bases
  • Year:
  • 1996

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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.