![]() ![]() Private Memor圜ache _cache = new Memor圜ache( new Memor圜acheOptions() NET Core’s dependency injection mechanism. As per Microsoft’s recommendation, prefer using because it integrates better with Asp. Microsoft has 2 solutions 2 different NuGet packages for caching. I’ll show you Microsoft’s solution, how to effectively use it, and then how to improve it in some scenarios. This deprived me the pleasure of creating a similar implementation myself, but at least I have less work writing this blog post. ![]() To my great dismay as a blogger, Microsoft already created a wonderful cache implementation. Now that we know what we need, let’s continue on to better solutions. Size Limit policy will limit the cache memory size.Once I don’t use it for longer than a minute, the item is evicted. So if I set the expiration to 1 minute, the item will keep staying in cache as long as I use it every 30 seconds. Sliding Expiration policy will remove an item from cache if it wasn’t accessed in a fixed amound of time.Absolute Expiration policy will remove an item from cache after a fixed amount of time, no matter what.These are rules to have items removed from cache according to some logic. To handle these problems, cache frameworks have Eviction policies (aka Removal policies). Our caching infrastructure should support that ability. Cache might need to be refreshed if the data changes.In this state, the garbage collector works more than it should, hurting performance. High memory consumption can lead to GC Pressure (aka Memory Pressure).Cache can take up a lot of memory, eventually leading to an out-of-memory exceptions and crashes. ![]() Here’s why we should be removing items from Cache: Besides that, cached items will stay in memory forever, which is actually very bad. Exceptions can occur when used from multiple threads. For one thing, this implementation is not thread-safe. The above solution is not good for a number of reasons. All following requests for the avatar will be pulled from memory, saving time and resources.īut, as most things in programming, nothing is so simple. The avatar data ( byte) is then saved in process memory. To get a user’s avatar, only the first request will actually perform a trip to the database. This simple code solves a crucial problem. Var myAvatar = _avatarCache.GetOrCreate(userId, () => _database.GetAvatar(userId)) Let’s create a very simple cache implementation in C#: We’re going to talk just about in-process cache. This means if one server saved a cache item, other servers can use it as well. With a distributed cache, it is stored in an external service. Distributed Cache is when you want to have shared cache for several machines.Best used when getting the cached item is expensive, and your process tends to restart a lot. This is more difficult, but if your process is restarted, the cache is not lost. Persistent in-process Cache is when you back up your cache outside of process memory.If you’re running the same process on several servers, you will have a separate cache for each server. When the process dies, the cache dies with it. In-Memory Cache is used for when you want to implement cache in a single process.In-process Cache, Persistant in-process Cache, and Distributed Cache Data that constantly changes, like the current machine’s time shouldn’t be cached or you will get wrong results. Instead of performing that trip every time, we will save that Avatar in the cache, pulling it from memory every time you need it.Ĭaching works great for data that changes infrequently. The next time that we need that result, we will pull it from the cache container, instead of performing the heavy operation again.įor example, to get a person’s Avatar you might need a trip to the database. When performing a heavy operation, we will save the result in our cache container. It’s a simple, but a very effective concept. One of the most commonly used patterns in software development is Caching. ![]()
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