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ITERATIVE MULTI-ATTRIBUTE INDEX SELECTION FOR LARGE DATABASE SYSTEMS
ITERATIVE MULTI-ATTRIBUTE INDEX SELECTION FOR LARGE DATABASE SYSTEMS
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机译:大型数据库系统的迭代多属性索引选择
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摘要
The inventors have implemented in a columnar in-memory database and studied access patterns of a large production enterprise system. To obtain accurate cost estimates for a configuration, the inventors have used the what-if capabilities of modern query optimizers. What-if calls, however, are the major bottleneck for most index selection approaches. Hence, a major constraint is to limit the number of what-if optimizer calls. And even though the inventive approach does not limit the index candidate set, it decreases the number of what-if calls because in each iteration step the number of possible (index) extensions is comparably small which results in a limited number of what-if calls.
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