Abstract
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Highlights
The need for federated database services has increased dramatically in recent years
Stonebraker. 2001.)—first finding the best query plan for a single machine and scheduling it across the federation based on run time conditions — works very well in the presence of fluctuations in the loads on the underlying data sources and the communication costs, as long as the physical database design is known to the optimizer
We present a preliminary analysis explaining this surprising success of the two-phase optimizer for our cost model and experimental settings later in the paper (Section 4.3)
Summary
The need for federated database services has increased dramatically in recent years. Within enterprises, IT infrastructures are often decentralized as a result of mergers, acquisitions, and specialized corporate applications, resulting in deployment of large federated databases. Knight), whose business hinges on federating thou-sands of decentralized catalogs and other databases. These decouplings are often forced by administrative constraints, since federations typically span organizational boundaries; decoupling is motivated by the need to scale the administration and performance of a system across thousands of sites. We present minimum-communication decoupled variants of various well-known optimization techniques. We have implemented these algorithms in the Cohera federated database system 2001.)—first finding the best query plan for a single machine and scheduling it across the federation based on run time conditions — works very well in the presence of fluctuations in the loads on the underlying data sources and the communication costs, as long as the physical database design is known to the optimizer. Our analysis suggests that this behavior may not merely be a peculiarity of our experimental settings, but may hold true in general
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