lru | A simple LRU cache | Caching library

I don't think it's so easy to adapt the existing lru_cache, and I don't think that linked method is very clear.

Instead I implemented a timed lru cache from scratch. See the docstring at the top for usage.

It stores a key based on the args and kwargs of the inputs, and manages two structures:

• A mapping of key => (expiry, result)
• A list of recently used, where the first item is the least recently used

Every time you try to get an item, the key is looked up in the "recently used" list. If it isn't there, it gets added to the list and the mapping. If it is there, we check if the expiry is in the past. If it is, we recalculate the result, and update. Otherwise we can just return whatever is in the mapping.

Redis Labs announced their new "RedisCDC" solution at RedisConf 2021 which seamlessly migrates data from heterogeneous data sources to Redis and Redis Modules. Its configurable and extendable, so you can easily create a custom stage that invalidates Redis keys when there is an update or delete on the source side.

There are two topologies in which you can use Hazelcast: Embedded and Client-Server. Your Java Spring configuration configures Hazelcast Client, however your hazelcast.yaml is dedicated for the Embedded mode.

Try to either use your hazelcast.yaml configuration in your Hazelcast server. Or configure your cache in the Hazelcast client, for example, like this:

Image clearing can be done in onViewRecycled, f.e. Glide.with(context).clear(imageView). Plus in the case of Glide, it will be useful to check caching strategies and choose what you need. And as size optimization, when a loaded image can be smaller then the ImageView will be usefull to use Glide.with(context).load(image).centerInside()...

In C[i] = B[i] + A[i]; the compiler may load A[i] first or B[i] first. The C standard does not impose any requirement on this ordering.

With G[i] = x*F[i]; coming after that, the compiler must load F[i] after storing C[i] unless it can determine that F[i] is not the same object as C[i]. If it can determine that, then it may load A[i], B[i], and F[i] in any order.

Similarly, if it can determine that G[i] does not overlap C[i], it may store C[i] and G[i] in either order.

If this code appears in a loop, this permissive reordering extends to elements between iterations of the loop: If the compiler can determine that it will not affect the defined results, it can load B[i] from a “future” iteration before it loads A[i] for the current iteration, for example. It could load four elements from B, four elements from A, four elements from F, and do all the arithmetic before it stores any elements to C or G. (Often the compiler does not have the necessary information that the arrays overlap, so it will not do this reordering unless you give it that information in some way, as by declaring the pointers with restrict or use special pragmas or compiler built-ins to tell it these things.)

Generally, the C standard is permissive about how actual operations are ordered. It only mandates that the observable behavior it specifies be satisfied. You should not expect that any particular elements are loaded first based on standard C code alone.

In Java, LRU caches are usually implemented with LinkedHashMap. This is a hashmap with an internal ordering among nodes.

For a segmented LRU cache, you'll need to make a cache class that includes two of these maps.

For the protected map, use the constructor with accessOrder = true, so that every time you access an entry, it will move it to the end of the internal ordering.

You should create subclasses that override the removeEldestEntry method to automatically expire entries and move them from the protected to probationary segment when necessary.

Moving cache hits from the probationary map to the protected map will have to be done by your cache class.

Figured it out.

What works:

I changed:

By the code and documentation you should use ttl_cache from func.py: