Mariposa: a wide-area distributed database system

Abstract

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 sitespecific 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.

Comprehensive Optimization of Declarative Sensor Network Queries

“…For execution over multiple nodes in robust networks, the second phase is comparatively simple: one step partitions the PAF into fragments and another step allocates them to suitably resourced sites, as in, e.g., [22]. One approach to achieving this is to map the physical-algebraic form of a query to a distributed one in which EXCHANGE operators [23] define boundaries between fragments.…”

“…In classical DQP, the optimizer does not have to consider the network topology, as this is abstracted away by the network protocols. As such, the corresponding focus of where-scheduling in DQP tends to be on finding sites with adequate resources (e.g., memory and bandwidth) available to provide the best response time (e.g., Mariposa [22]). …”

Efficient Processing of Client Transactions in Real-Time

“…Application of an economic model to adaptive query processing and dynamic load-balancing in a non real-time context was proposed in [50]. Load-balancing heuristics for use in a distributed real-time system are described in [49].…”

Peer‐To‐Peer Grid Databases for Web Service Discovery

“…A node can accept queries over an XML view and internally translate the query into SQL [44,45]. An early attempt towards a WAN distributed DBMS was Mariposa [46], designed for scalability to many cooperating sites, data mobility, no global synchronization and local autonomy. It used an economic model and bidding for adaptive query processing, data placement and replication.…”