Cache life cycle in Java caching technology

Java caching technology is one of the important means to improve software performance and response speed. It reads data from memory to reduce disk IO, network requests and other resource-consuming operations, thereby making the program more efficient. When using cache technology, we need to consider the impact of the cache life cycle on program operation. This article will start with the four stages of the cache life cycle, namely storage, access, update and invalidation to introduce cache-related knowledge.

First Phase: Storage

The first phase of the cache life cycle is storage. In this stage, the program needs to cache the data that needs to be read into memory. Normally, you can use caching frameworks, such as Ehcache, Redis, etc., to cache data in memory, or you can also implement it by handwriting caching tool classes. When storing data, we need to consider the following issues:

1. Cache size: The cache framework usually stipulates the cache size, because caching all the data into the memory will occupy a large amount of memory and cause system resources wasteful, and more likely to cause OOM exceptions.
2. Cache strategy: The cache strategy can choose time eviction, space eviction, FIFO and LRU strategies. Temporal eviction refers to removing data from the cache based on how long it has not been used. Space eviction is based on the percentage of cache size occupied by cached data. FIFO is a first-in-first-out strategy, and LRU is an algorithm based on least recently used replacement data.
3. Cache key value: The cache system needs to store and read data based on key value. When using cache, we need to consider choosing the appropriate key value type so that cache key values ​​will not conflict between different application modules.

Second Phase: Access

The second phase of the cache life cycle is access. When the program starts, there is no data in the cache, so when it needs to read the data, the program will query the data from the database and store it in the cache. When the same data is needed next time, the program will read directly from the cache. If the data in the cache is within the validity period, it will return directly. Otherwise, the data will be re-queried from the database and stored in the cache.

When accessing cached data, we need to consider the following issues:

1. Cache validity period: Cache data cannot always be valid, and the cache validity period needs to be considered. When data expires, the program should re-fetch the data from the data source and update it.
2. Cache consistency: The data obtained by the program from the cache may be inconsistent with the data in the data source. The solution to this problem is usually to use distributed locks to prevent data inconsistencies caused by multiple threads reading data from the data source and storing it in the cache at the same time.

The third phase: update

The third phase of the cache life cycle is update. When the data in the data source changes, the program needs to update the data in the cache, otherwise the program will read the old data from the cache. When the data source changes, the program can choose the following strategies:

1. Based on timestamp: Use the timestamp or version number in the data source to update the data in the cache. Every time the data source is updated, the timestamp or version number is updated at the same time. When the program reads data from the cache, it checks whether the timestamp or version number is equal. If not, it needs to read the data from the data source again and update the cache. .

2. Based on the publish-subscribe model: The publish-subscribe model means that when the data in the data source changes, the cache system is triggered to update the data in the cache.

The fourth stage: invalidation

The last stage of the cache life cycle is invalidation. The data in the cache may become invalid due to the following reasons:

1. Cache data expiration: The data in the cache has an expiration date.
2. Cache data was cleared: The cache framework cleared the cache data.
3. Program error: The program has an error while using cache.

The invalid cache will be removed, and the program needs to requery the database the next time it is accessed.

When using caching technology, we need to understand the life cycle of the cache and master the stages of cache storage, access, update and invalidation. In addition, we need to reasonably choose cache size, cache strategy, cache key type, etc., and try to optimize program performance when using caching technology, thereby improving program response speed and user experience.

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