密切关注您的总体缓冲池命中率。
现在的缓冲池命中率就显示了较好的结果。
获取新的快照，并计算新的缓冲池命中率，如下
Take a new snapshot, and calculate the new bufferpool hit ratio as follows
以上示例显示了98.4%的良好缓冲池命中率。
The above example shows a good buffer pool hit ratio of 98.4%.
一般情况下，缓冲池命中率在80%以上就认为是良好的。
In general, a buffer pool hit ratio above 80% is considered good.
您的缓冲池命中率的理想目标是数据80%或更高，索引90%或更高。
A desirable goal for your buffer pool hit ratio is 80% or higher for data, and 90% or higher for index.
在进行性能测试时，若能看到用户、SQL、缓冲池命中率等，无疑更为有趣。
When doing the performance testing, it becomes much more interesting to see users, SQL, buffer pool hit rates, etc.
您可以使用快照来获得诸如缓冲池命中率、排序堆溢出的次数以及系统工作负载之类的信息。
You can use the snapshot report to derive information such as the buffer pool hit ratio, amount of sort heap overflows, and the system workload.
问题查询：这些查询只返回超过重要性能计数器阈值的行，例如缓冲池命中率不到90%的行。
Problem queries: These queries return only rows that exceed thresholds for important performance counters, for example, rows with buffer pool hit ratio lower than 90%.
显然，随着数据库服务器上物理内存的使用，高缓冲池命中率对于您的数据库性能而言始终比较好。
Obviously, with availability of physical memory on the database server, a high buffer pool hit ratio is always better for your database performance.
因此，相比不压缩，压缩能让内存存储更多的数据，进而提高了缓冲池命中率和可用内存的利用率。
As a result, compression allows more data to be in memory than without compression, which increases the buffer-pool hit ratio and makes higher utilization of the available memory.
识别内存问题，包括较低的缓冲池命中率、较低的目录缓存命中率和较低的包缓存命中率。
Identify problems with memory, including low buffer pool hit ratios, catalog cache hit ratios, and package cache hit ratios.
若使用多个缓冲池，可能要从PWH . BUFFERpool表取得缓冲池命中率和缓冲池名称。
If you use multiple buffer pools, you might take the buffer pool hit ratio together with the buffer pool name from the PWH.BUFFERPOOL table.
通过250个页面的缓冲池大小，应用程序测试运行呈现了48.69%的糟糕的缓冲池命中率。
With the buffer pool size of 250 pages, the application test run experienced very poor buffer pool hit ratio of 48.69%.
如果必要，可以将数据和索引分隔到两个不同的缓冲池中，以帮助确保一个良好的索引缓冲池命中率。
If necessary, you can separate data and index into two different buffer pools to help ensure a good index buffer pool hit ratio.
如果您的系统具有较低的缓冲池命中率，您就可以通过增加缓冲池大小来进一步地取得更好的应用程序性能结果。
If your system has a low buffer pool hit ratio, you can increase the buffer pool size further to achieve better application performance result.
缓冲池命中率 = (1- (1838 +50) / (269482 + 82)) * 100% = 99.29%
The buffer pool hit ratio = (1 - (1838 + 50) / (269482 + 82)) * 100% = 99.29%
缓冲池命中率 = (1- (273548 +52) / (183925 + 82)) * 100% = 48.69%
The buffer pool hit ratio = (1- (273548 + 52) / (183925 + 82)) * 100% = 48.69%
使用一个缓冲池，但是增加其大小直至索引命中率停止增长。
Use one buffer pool, but increase its size until the index hit ratio stops increasing.
如果命中率较低，则可以增加缓冲池页数来提高性能。
If the hit ratio is low, increasing the number of buffer pool pages may improve performance.
该查询只返回命中率低于90%的缓冲池。
The query returns only the buffer pools that have a lower hit ratio than 90%.
比较缓冲池的应用程序命中率。
当多个缓冲池同时在用时，缓冲池快照数据可用于计算每个缓冲池的命中率，来表示每个缓冲池的有效性。
When multiple buffer pools are in use, the buffer pool snapshot data can be used to calculate the buffer pool hit ratio of each pool to indicate the effectiveness of each buffer pool.
perl buffhitratio . pl dbrun. snap——该脚本提供了每个缓冲池的数据和索引页命中率。
Dbrun.snap - This script provides the hit ratio for the data and index pages of every buffer pool.
perl buffhitratio . pl dbrun. snap——该脚本提供了每个缓冲池的数据和索引页命中率。
Dbrun.snap - This script provides the hit ratio for the data and index pages of every buffer pool.
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