What to use for golang cache

Golang is an efficient, reliable, and easy-to-use programming language that supports a variety of caching strategies. When using golang cache, you must make a choice based on the actual application scenario. According to different application scenarios and requirements, choosing a suitable caching strategy can improve the performance and concurrent processing capabilities of the application under high load conditions.

1. Golang’s cache strategy

1. Local cache

Golang uses map to implement internal local cache, which can greatly improve the speed of cache reading and reduce cache queries. burden. When using local cache, the memory space and cache expiration time should be controlled to avoid cache memory overflow and cache data being too stale.

2.redis cache

Redis is a high-performance distributed cache that can achieve high-concurrency caching and data storage. In golang, you can use the redigo library to implement operations such as connection to the redis cache server, data reading, writing and management.

3.memcache cache

Memcache is another commonly used high-concurrency cache, which can effectively reduce the read and write burden of the database. In golang, you can use the golang-memcached library to operate the Memcache cache server.

4. Local file cache

For larger caches that frequently operate md5 values, it is recommended to use files for cache management. The io/ioutil library provided by golang can easily read, write and manage files, and you can customize the file storage path and name.

5. Lock-free cache

In high-concurrency application scenarios, the cost of locking operations will affect concurrency performance. In this case, you can consider using lock-free cache. Golang officially provides the sync/atomic library, which can realize lock-free cache data reading, writing and management.

2. Golang caching practice

1. Use local cache

Go language map is automatically expanded, commonly known as go map gray wolf, has concurrency security, is simple to use, and has A small optimization tip. The larger the bucket index, the more triggers for expansion and the faster the expansion speed. This can optimize memory fragmentation. When using local cache, you need to consider the endurance of your own memory and ensure memory usage efficiency by regularly deleting old and expired data.

2. Use redis cache

Redis is a high-performance caching solution that can be used in key-value structure storage systems placed in memory. And Redis supports all the data types you can access quickly: strings, hash structures, lists, sets, and sorted sets, allowing you to store intelligent scenes in memory. When using redis cache, you need to pay attention to using the Redis basic API, redis-py and the officially recommended Redis client.

3. Use memcache cache

Memcached is a simple, easy-to-use and very fast distributed caching system, and is one of the NoSQL databases. Flexible, supports any data structure and any code type, fast, and customizable cache size. When using memcache cache, you need to pay attention to data expiration time and cache hit rate.

4. Use local file cache

For static data or data that is read less frequently, you can consider using local file cache. When using local file caching, you need to understand the file path and name settings, cached data read and write operation methods and other related details.

5. Use lock-free cache

When high concurrency performance and maximum utilization of system resources are required, lock-free cache can be used. When using lock-free cache, you need to understand related concurrency control issues, data structure design, algorithm principles and other techniques.

3. Advantages and Disadvantages of Caching

Advantages:

1. Improve application performance and processing capabilities.

2. Reduce the reading and writing burden on the database and protect the security of the database.

3. It can shorten the query time and response time and improve the user experience.

Disadvantages:

1. The cache memory occupies a large amount, and the cache needs to be cleaned regularly, which increases the management cost of the application.

2. Caching may cause cache avalanche, cache penetration, cache breakdown and other problems, which require corresponding technical processing.

3. The cached data may be inconsistent with the database data, and cache and database synchronization are required.

4. Caching application scenarios

1. In high concurrent reading and writing scenarios, local cache and lock-free cache can be used to improve performance and processing capabilities.

2. In scenarios with a large amount of data calculation, you can use local cache, redis cache or memcache cache to cache data to reduce the burden on the database.

3. In the scenario of static data, local file caching can be used to cache, read and write local data.

4. In the scenario of small and medium-sized business systems, local cache, redis cache or memcache cache can be used for cache management and processing.

5. Summary

golang provides a variety of caching strategies and technical practice methods. According to different application scenarios and requirements, suitable caching methods can be flexibly selected to improve application performance and processing. ability. When using cache, you need to consider memory usage, data expiration, cache updates, concurrency control and other related issues to achieve the best cache effect and application performance optimization.

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