As a consequence, the optimizer usually makes sub-optimal decisions, leading to poor performance.
因此,优化器常常作出非最优决策,从而导致低劣的性能。
Consequently, if the statistics are inaccurate, outdated, or conflicting, the optimizer will create inaccurate estimates for the costs of the steps in a query plan, leading to poor performance.
因此,如果统计数据不准确或者过期,或者冲突,优化器会对查询计划中各步骤的成本评估不准确,从而导致糟糕的性能。
The impact of these antipatterns can be significant, leading to delivery delays, poor performance, and lack of reuse.
这些反模式的影响是巨大的,导致交付延迟、性能降低和缺乏重用。
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