Whirlcache Performance Term: Optimize the cache hit rate in the Java class library

Whirlcache Performance Term: Optimize the cache hit rate in the Java class library Abstract: Caches is one of the common technologies to improve application performance.Whirlycache is a powerful Java cache library, but it may encounter a problem of low cache hit rate during use.This article will introduce some techniques to optimize Whirllycache's cache hit rate to improve the performance of the application. 1. Determine the appropriate cache strategy: The cache strategy is the rule that determines how long the object is retained in the cache.It is important to choose the appropriate cache strategy according to the needs of the application.Common cache strategies include advanced first -out (FIFO) and minimal use (LRU).When using whitecache, you can adjust the performance of the cache strategy by setting the appropriate value. For example, you can set the maximum number of objects and objects in the cache through the following code:: Cache myCache = new Cache("myCache", 100, true, false, 3600, 1800); The above code creates a cache called "MyCache". The maximum number of objects is 100, the survival time of the object is 3600 seconds, and the object of the object is 1800 seconds.Adjust these values according to actual needs to meet the requirements of the application. 2. Use the appropriate cache key: The cache key is used to identify the unique value of the object in the cache.Use the unique and suitable cache key to increase the hit rate of the cache.When using WHIRLYCACHE, you can choose to use a custom cache key to replace the default key. For example, if you want to cache the name of the user, you can use the user's unique logo as the cache key: String userId = "12345"; String name = myCache.get(userId); if (name == null) { // Get the user name from the database or other data sources name = getUserFromDatabase(userId); myCache.put(userId, name); } In the above code, use the user's unique identification as a cache key, and first try to obtain the user's name from the cache.If there is no existence in the cache, obtain the user name from the database or other data sources and save it into the cache for follow -up use. 3. Preheat data: When the application starts, if some commonly used data can be loaded into the cache in advance, the cache hit rate can be increased.By warm -up, a large number of cache fails when the application is just started, thereby reducing the response time. For example, some commonly used data can be loaded in the application stage during the initialization stage of the application: for (String userId : commonlyUsedUserIds) { String name = getUserFromDatabase(userId); myCache.put(userId, name); } In the above code, the unique logo of commonly used users is traversed to obtain the user name from the database, and it is stored in the cache.In this way, after the application is started, these commonly used data have been loaded into the cache in advance, increasing the subsequent cache hit rate. 4. Monitoring and adjustment: The hit rate and effect of monitoring cache are very important.Using the monitoring function provided by Whirlycache, such as hit rate statistics, you can find performance problems in time and adjust.According to the monitoring results, the configuration parameters and strategies of the cache can be adjusted to further optimize the cache's hit rate and performance. For example, you can use the WHIRLYCACHE's monitoring function to get the cache hit rate: CacheStatistics stats = myCache.getStatistics(); double hitRate = stats.getHitRate(); In the above code, obtain the cache statistics through the `GetStatistics ()` method, and obtain the cache hit rate through the `GetHitrate ()" method. in conclusion: Through the appropriate cache strategy, the selection of cache keys, the preheating and monitoring adjustment of the data, it can optimize the cache hit rate in the WhirlCache and improve the application performance.When using WHIRLYCACHE, adjust the cache parameters and strategies reasonably according to actual needs, and monitor and optimize at the same time to obtain better cache performance.