As you've seen in the steps above, the optimizer selects the optimal access plan based on available statistics.
您可以从以上步骤看到，这个优化器基于可用的统计信息选择了最优的存取计划。
Accurate index information and statistics are fundamental to cost-based decisions in the query optimizer.
准确的索引信息和统计信息是查询优化器中基于成本的决策的基础。
The optimizer calculates its cardinality estimate — that is, the estimated number of rows returned by the query — based on the statistics available.
优化器根据可用的统计信息计算基数的估计值，即预计查询返回的行数。
If current statistics are not available, the optimizer may choose an inefficient access plan based on inaccurate default statistics.
如果无法获得当前的统计数据，优化器就可能会基于不准确的默认统计数据选择低效的访问计划。
Focus on problem of statistics of query optimizer on update, we design a statistics method based on partition technique.
并针对传统查询优化器对于大规模海量数据统计信息更新不及时的问题，设计了一种基于分区技术的统计方法。
Only statistics stored in the dictionary itself have an impact on the cost-based optimizer.
只有存储在字典视图中的统计信息，才会被优化器使用。
Only statistics stored in the dictionary itself have an impact on the cost-based optimizer.
只有存储在字典视图中的统计信息，才会被优化器使用。
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