最小期望成本查询优化：实用性练习
Least expected cost query optimization: an exercise in utility
摘要：
我们确定了两个不合理的，虽然标准的，数据库查询优化，可能会对所选择的评估计划的质量产生不利影响的假设。一个假设是，对于预期的情况进行优化就足够了--也就是说，各种参数（如可用内存）采用其预期值的情况。另一个假设是参数在整个查询执行过程中是恒定的。我们提出了一个算法的基础上的“R系统”式的查询优化算法，不依赖于这些假设。我们提出的算法选择最小期望成本的计划，而不是最低成本的计划给定的一些固定值的参数。在表现出高度可变性的执行环境中，我们的技术应该会带来更好的性能。
英文摘要：
We identify two unreasonable, though standard, assumptions made by database query optimizers that can adversely affect the quality of the chosen evaluation plans. One assumption is that it is enough to optimize for the expected case---that is, the case where various parameters (like available memory) take on their expected value. The other assumption is that the parameters are constant throughout the execution of the query. We present an algorithm based on the ``System R''-style query optimization algorithm that does not rely on these assumptions. The algorithm we present chooses the plan of the least expected cost instead of the plan of least cost given some fixed value of the parameters. In execution environments that exhibit a high degree of variability, our techniques should result in better performance.
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