With the continuous development and widespread application of Internet technology, the amount of data and the frequency of data access are increasing exponentially. This makes the performance of application systems accessing databases and network services a bottleneck, causing problems. Therefore, caching is widely used in application development as a technology to improve application performance. Golang is an efficient application development language, and caching strategy is also one of the important optimization methods of Golang. This article will introduce the implementation strategy of caching in Golang and solutions to common problems.
1. Cache types in Golang
Memory cache refers to caching data in the application memory to reduce the impact on the hard disk and other external data sources. The access speed of the memory cache is very fast, and the data is read quickly. The more common memory caches in Golang include: map and sync.Map.
Map is a very basic data structure that provides fast search, add, and delete operations. Since map is not thread-safe, locks should be used to ensure thread safety when accessed by multiple threads.
sync.Map is a thread-safe map structure newly introduced in Golang version 1.9. It provides methods such as Store, Load, and Delete for data operations.
Redis is an open source in-memory data repository that supports persistence, clustering, and lua scripting. Redis has excellent performance, supports high-speed access and prevents data loss, and is a database that is very suitable as a cache. In Golang, we can implement Redis cache operations by using the third-party library github.com/go-redis/redis.
Memcached is a popular, high-performance in-memory object caching system that reduces post-processing by storing key/value pairs in memory. End database access. In high-concurrency web applications, Memcached can effectively improve application performance. In Golang, we can also use the third-party library github.com/bradfitz/gomemcache to implement Memcached cache operations.
2. Cache implementation strategy
Cache update means that when the data changes, the data in the cache must be updated in time . In order to achieve the immediacy of cache, we can adopt the following strategies:
1) Invalid update strategy
Invalid update means to delete the value in the cache immediately after the data changes. The next request will fetch the new value from the data source and cache the new value in memory again.
2) Delayed update strategy
Delayed update means that after the data changes, the value in the cache is not deleted directly, but waits for a period of time before deleting, so as to ensure that the user During this period, cached data is accessed, which avoids frequent access to the database.
3) Asynchronous update strategy
Asynchronous update means that after the data changes, the value in the cache is not directly deleted, but the changed data is put into a message queue, which is sent by a A dedicated asynchronous task is responsible for updating the cache and caching the new values in memory again.
The size of the cache will continue to increase over time, so a certain recycling strategy needs to be set to avoid memory exhaustion. In Golang, we can recycle memory through the following strategies:
1) Scheduled cleanup strategy
Scheduled cleanup refers to regularly clearing the timed-out data in the cache at a certain time interval or Data that has been marked as invalid to free up memory in the cache.
2) Cleaning strategy by access frequency
Cleaning by access frequency means that when the cache capacity reaches a certain value, some data will be selected for elimination based on the frequency of data use to release the cache. memory space.
3. Solutions to common cache problems
In the use of cache, common problems include cache avalanche, cache penetration and cache concurrent writes. Below we'll explain how to resolve these issues.
Cache avalanche means that during a certain period of time, most of the data in the cache becomes invalid, causing all data requests to only access the data. sources, thereby putting pressure on data sources. Cache avalanches usually occur during server restarts, capacity expansion, network partitions and other emergencies.
To solve the cache avalanche problem, you can adopt the following strategies:
1) Set the randomness of the cache expiration time
When setting the cache expiration time, you can consider the original A random time interval is added to the expiration time to avoid centralized invalidation of all caches.
2) Use hotspot data to preheat
When the system starts, you can preheat some hotspot data into the cache in advance to avoid pressure caused by emergencies.
Cache penetration means that the requested data does not exist in the data source, causing the cache to fail to hit, and a large number of invalid requests will be accessed directly to the data source, thereby affecting system performance. Cache penetration is often caused by an attacker deliberately requesting data that does not exist.
To solve the problem of cache penetration, you can adopt the following strategies:
1) Use Bloom filter
Before caching the request, use Bloom filter to The requested data is verified for validity, and the cache or data source is accessed after passing it.
2) Optimize the data source
Distinguish data that does not hit the cache from legitimate requests. It may be that the data source limits the number of accesses. The architecture of the data source can be optimized to improve system performance.
Cache concurrent write refers to the situation where multiple threads access the same cache area at the same time, resulting in data errors. In Golang, we can use the following strategies to solve the problem of cache concurrency:
1) Locking mechanism
When writing to the cache, we can use the locking mechanism to Ensure the security of concurrent access.
2) Use the singleton mode
to instantiate the cache into a singleton, and only access the same instance in multiple threads to avoid multiple instances existing at the same time, resulting in out-of-synchronization.
Summary:
Caching is an important means to improve application performance. There are also many excellent cache implementation methods and strategies in Golang. When using cache, you need to pay attention to solutions to some common problems to ensure the stability and reliability of the cache system.
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