Cache ID mapping in Java caching technology

In Java caching technology, especially in the field of distributed caching, cache ID mapping is a very critical issue. Cache ID refers to the unique identifier used to identify an object in the cache, that is, the cache key. Cache ID mapping refers to the process of mapping cache keys to actual cache server addresses.

Why do you need to cache ID mapping?

In distributed cache, there are usually multiple cache servers, and each server will store a portion of the cache data. When a client requests a cache object, it needs to know the address of the cache server where the object resides in order to send the request and obtain the data. Therefore, caching ID mapping becomes essential.

So, how to perform cache ID mapping? There are generally two implementations: client hashing and server hashing.

Client-side hash

Client-side hashing refers to hash calculation on the client side and maps the cache key to a specific cache server. The specific implementation can be to calculate the hash value of the cache key, and then modulo the hash value and the total number of servers to obtain the number of the cache server. The client can directly send a request to the corresponding server based on this number.

Advantages:

1. Simple to implement, easy to understand and maintain. The core logic is implemented on the client, and the server does not need to maintain data structures such as hash tables, reducing server pressure.
2. The load balancing effect is better. When the distribution of cache keys is relatively even, the corresponding cache objects will also be evenly distributed to each cache server.

Disadvantages:

1. It is difficult to change the number of servers. When the number of cache servers changes, hash values ​​need to be recalculated and some cache objects migrated to new servers. This process is relatively cumbersome and requires the support of certain management tools.
2. There is a hash skew problem. When cache keys don't fall evenly across different servers, it causes some servers to have very high loads and others to have very low loads.

Server Hash

Server hashing refers to hash calculation on the server side and maps the cache key to a specific cache server. The specific implementation can be to create a server list on the server side, calculate a hash value for the cache key, and then modulo the hash value and the length of the server list to obtain the corresponding server number.

Advantages:

1. Suitable for situations where the number of servers changes frequently. When the number of cache servers changes, you only need to modify the server list and add the new server to the hash ring.
2. Solved the hash skew problem of client hashing. Server hashing can effectively avoid excessive load on a single server based on the balance of the server list.

Disadvantages:

1. When making changes to the server list, all clients need to be notified. Because the client needs to know the changes in the server list in order to correctly send the cache object to the corresponding server.
2. Server list balance may be affected. If the performance of a certain server in the server list deteriorates or goes down, it may cause uneven distribution of cached objects on the hash ring.

To sum up, client hashing and server hashing have their own advantages and disadvantages. During specific implementation, it is necessary to choose the appropriate method according to the actual situation.

In addition, there are some other cache ID mapping algorithms and schemes, such as consistent hashing, virtual nodes, etc. These solutions can solve the problems of client hashing and server hashing to a certain extent, and improve the scalability and fault tolerance of the system.

In short, cache ID mapping is an inevitable problem in distributed cache. For large-scale distributed systems, the implementation and optimization of cache ID mapping can effectively improve the performance and reliability of the system.

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