hit ratio

As a rule of thumb, you can increase the size of the buffer pools as long as you get a corresponding increase of the bufferpool hit ratio.

dbrun. snap - This script provides the hit ratio for the data and index pages of every buffer pool.

Check that the cache size is sufficiently large and that the cache hit ratio is high for each of the dynamic SQL statements being executed.

Another method of determining your caching effectiveness is to take a look at your cache hit ratio.

If necessary, you can separate data and index into two different buffer pools to help ensure a good index buffer pool hit ratio.

Bigger is still better, but at some point you'll experience diminishing returns as the buffer pool hit ratio moves to the 98 % range.

The hit ratio is a function of the cache size, the amount of underlying data, and the data access pattern.

If the hit ratio is low, increasing the number of buffer pool pages may improve performance.

The buffer pool hit ratio is now showing excellent results.

It realizes data caching among groups, which makes the caching data more reasonable and enhances the hit ratio of cache.

What is the cache hit ratio, what impact does it have on performance of an Oracle database and what is involved in tuning it?

Cache API Hit Ratio The cache hit-to-miss ratio when accessed through the external cache APIs.

When you wish your miss ratio was reversed with your hit ratio.

Use one buffer pool, but increase its size until the index hit ratio stops increasing.

Additionally, more rows fit in the storage engine cache, potentially improving the hit ratio.

A desirable goal for your buffer pool hit ratio is 80% or higher for data, and 90% or higher for index.

The fewer pages would mean that the TLB process would have a higher hit ratio and therefore improved performance.

Figure 3 shows the hit ratio highlighted in red, which indicates a performance problem.

dbrun. snap - This script provides the hit ratio for the catalog cache.

dbrun. snap - This script provides the hit ratio for the package cache.

Because of its locality-aware nature, ADSB achieves very high cache hit ratio.

The quality model whose hit ratio of 5% deviation reach 0. 508 is established by applying the technology of basic artificial neural network.

With the buffer pool size of 250 pages, the application test run experienced very poor buffer pool hit ratio of 48. 69%.

Overall hit ratio for all protocol caches.

In general, a buffer pool hit ratio above 80% is considered good.

In additon, it returns the time intervals when the low hit ratio occurred.

Lower bounded indicators are identified as unhealthy as they decrease in value (for example, the cache hit ratio indicator).

Indexes in particular should have a high hit ratio to ensure good performance.

Pay close attention to your overall buffer pool hit ratio.

The above example shows a good buffer pool hit ratio of 98. 4%.

Generally, you can increase the buffer cache hit ratio by increasing the amount of memory available to SQL Server.

Buffer pool hit ratio is very important to monitor.

A well-tuned system can easily have a hit ratio well above 90%.

For example, a low ratio of XDA physical reads to XDA logical reads indicates a high buffer pool hit ratio for XML data, which is desirable.

Research on the Hit Ratio Forecast of Terminal-sensitive Projectiles based on Support Vector Machine

Compare application hit ratio of databases

The package cache hit ratio can be calculated using the following formula

Compare application hit ratio of buffer pools

Test and Estimation of Missiles'Mean Hit Ratio Unsimple Random Samples

Catalog cache hit ratio can be calculated by using the following formula

A Streaming Media Proxy Cache Layout Method Based on Quality Hit Ratio

Package and catalog caches, and workspaces (for example, package cache hit ratio)