Estimating Costs of Path Expression Evaluation in Distributed Object Databases

Ruberg, Gabriela; Baião, Fernanda; Mattoso, Marta

doi:10.1007/3-540-46146-9_35

Cited by 3 publications

(1 citation statement)

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“…There are several works on estimating database statistics and query costs for specific database models, such as in [3], [7], [11], [21], [27], and [32]. These techniques are complementary to the DIG proposal, and they can be implemented in DIG collectors to improve their capabilities of information acquisition.…”

Section: Related Workmentioning

confidence: 99%

Digging Database Statistics and Costs Parameters for Distributed Query Processing

Ruberg¹,

Ruberg²,

Mattoso³

2003

On the Move to Meaningful Internet Systems 2003: CoopIS, DOA, and ODBASE

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Abstract. Cost parameters and database statistics are the basis of query optimization techniques. However, in distributed and heterogeneous database systems, acquiring and treating information in order to help the optimization process are often tasks of a global query processor, which adapts its functionalities to a specific system architecture. Moreover, this acquisition process involves a large number of parameters and requires customized methods to retrieve data from specific sources. DIG (Distributed Information Gatherer) is a provider of data statistics and query costs that, through an independent and flexible service, aims to support global query optimization processing in distributed and heterogeneous database systems over autonomous data sources. We have developed a DIG prototype and experimented it with specific wrappers for a query middleware on both semi-structured data sources and an object DBMS.

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