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Why do we need a LRU cache in Java?
A couple of years ago I implemented an LRU cache to lookup keyword IDs for keywords. The data structure turned out to be an interesting one because the required throughput was high enough to eliminate heavy use of locks and the synchronized keyword — the application was implemented in Java.
How to use LinkedHashMap as a LRU cache?
LinkedHashMap is often used as LRU cache. You have two spaces between class and LRUCache. In professional Java programming, it is customary to have a single space before and after each binary operator. public V getElement (K key) { readLock.lock (); try { } Looks strange to me. Why not have instead the following:
How is the threshold set in LRU caching?
In this particular implementation, the threshold is set at a low multiple of the concurrency level above the cache capacity. Eviction occurs in small batches, not one entry at a time; and multiple threads may participate in eviction until the size falls to the cache capacity.
Why do we need LRU order in Java?
The data structure turned out to be an interesting one because the required throughput was high enough to eliminate heavy use of locks and the synchronized keyword — the application was implemented in Java. It occurred to me that a sequence of atomic reference assignments would be sufficient to keep LRU order around a ConcurrentHashMap.
Is there a sample code for unordered map?
One has to supply a hasher, a equality operator, and an allocator. There is no sample code anywhere, even in the official Intel docs. Not recommended. If you don’t need all of the functionality of unordered_map, then this solution should work for you. It uses mutex to control access to the internal unordered_map.
Where can I find thread safety in CPP?
For container thread safety see: http://en.cppreference.com/w/cpp/container#Thread_safety. “All const member functions can be called concurrently by different threads on the same container.
What is the eviction rate for thread safe caching?
With more than 3 threads per core, throughput starts to deteriorate. The eviction rate for this test, which depends heavily on the frequency distribution of the lookup keys, comes in at around 5%. After some experimenting, I can say that cache performance is quite sensitive to the way purge operates.
What happens when two threads compete in LRU?
As you can see, two or more threads may compete in putting an entry into the map, but only one will win and thus invoke offer. After offering a node at the tail of the LRU list we check to see whether the size of the cache has reached a threshold above which we trigger batch eviction.