AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |
Back to Blog
Large amount of private cache1/26/2024 ![]() Now, when next the same request is made, the browser retrieves the response right from its cache without a trip to the server. When a network request for a page or XHR is made the document is gotten from the server and the browser caches the document. The browser caches the response of the network request in its internal storage. In HTTP cache, we have browser cache, proxy cache, gateway caches, CDN, reverse proxy caches, and load balancers.īrowser cache is a private HTTP cache. Just like how we improved performance in our JS app by caching our function, we can use HTTP cache to reduce latency and network traffic in our website. We saw caching function calls, here HTTP cache involves caching our HTTP requests to the server. If there is no match, the action is performed and the result is stored in the cache so in the future the result is returned from the cache. The uniqueness is what is stored in the cache key, and they are compared against each other when a match is met the value is returned from the cache value. So for us to know when an action has been performed we use the cache key to match against what is coming in, So every action has a uniqueness. ![]() In the cache, the results are stored in a key-value pair. The question here is: How do we know when we are performing the same action? How do we identify the uniqueness? The place where the results are stored is called cache. An action is performed and the result of the action is stored, now when the same action is to be performed again, the previously stored result is retrieved and returned without performing the action. It entails not performing the same action twice. It is relevant we know that so we can understand fully what caching in GraphQL entails.Ĭaching is a long-term optimization trick used in different fields. Let's start by understanding what caching generally is. Let’s call it Cache, and make it a generic over any Hashable key type, and any value type.Learn how caching can be used to cache GraphQL requests to prevent excessive and unnecessary requests. ![]() The first thing we’ll do is to declare our new cache type. However, by writing a thin wrapper around NSCache, we can create a much more flexible Swift caching API - that enables us to store structs and other value types, and lets us use any Hashable key type - without requiring us to rewrite all of the underlying logic that powers NSCache. that are subclasses of NSObject: let cache = NSCache() NSString here, since NSCache is only compatible with keys However, using it does come with a few caveats, as it’s still an Objective-C class on Apple’s own platforms - which means that it can only store class instances, and it’s only compatible with NSObject-based keys: // To be able to use strings as caching keys, we have to use Thankfully, Apple has already solved many of those problems for us through the built-in NSCache class. Not only do we have to efficiently store and load values, we also need to decide when to evict entries in order to keep our memory footprint low, invalidate stale data, and much more. Part of the systemĬaching is one of those tasks that at first might seem much simpler than it actually is. This week - let’s take a look at how caching can be an incredibly powerful tool in those kind of situations, how to build an efficient and elegant caching API in Swift, and how strategically caching various values and objects can have a big impact on the overall performance of an app. It could be multiple features loading duplicate copies of the same model, or a view’s data being reloaded every time that it reappears on the screen. One very common source of such unnecessary work is when we end up reloading the exact same data multiple times. Making an app feel fast and responsive isn’t only about tweaking the way its UI is rendered, or improving the sheer execution speed of its operations and algorithms - it’s often just as much about efficiently managing its data and avoiding unnecessary work.
0 Comments
Read More
Leave a Reply. |