Abstract
In wide-area database systems, which may be running on unpredictable and volatile environments (such as computational grids), it is difficult to produce efficient database query plans based on information available solely at compile time. A solution to this problem is to exploit information that becomes available at query runtime and adapt the query plan to changing conditions during execution. This paper presents a survey on adaptive query processing techniques, examining the opportunities they offer to modify a plan dynamically and classifying them into categories according to the problem they focus on, their objectives, the nature of feedback they collect from the environment, the frequency at which they can adapt, their implementation environment and which component is responsible for taking the adaptation decisions.
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