lru

问题 new to stack-overflow so please dont mind my noob way of asking this. I'm trying to implement LRU caching using a linked list, I've seen other implementations here using linkedHashMap and other data structures but for this case i'm trying to create the best optimized version using linked lists as i was asked during a technical round. I've limited the cache size here to 3 Is there any way to better optimize this LRU implementation ? Also what will be the time complexity for this implementation

问题 I have some C++ code where I need to implement cache replacement using LRU technique. So far I know two methods to implement LRU cache replacement: Using timeStamp for each time the cached data is accessed and finally comparing the timeStamps at time of replacement. Using a stack of cached items and moving them to the top if they are accessed recently, so finally the bottom will contain the LRU Candidate. So, which of these is better to be used in production code? Are their any other better

问题 I want to limit the size of the BlockingCollection. If I want to add another item and the collection is full, the oldest must be removed. Is there some Class specific to this task or my solution is ok? BlockingCollection<string> collection = new BlockingCollection<string>(10); string newString = ""; //Not an elegant solution? if (collection.Count == collection.BoundedCapacity) { string dummy; collection.TryTake(out dummy); } collection.Add(newString); EDIT1: Similar question here: ThreadSafe

问题 Why is Least Recently Used better than FIFO in relation to page files? 回答1: If you mean in terms of offloading memory pages to disk - if your process is frequently accessing a page, you really don't want it to be paged to disk, even if it was the very first one you accessed. On the other hand, if you haven't accessed a memory page for several days, it's unlikely that you'll do so in the near future. If that's not what you mean, please edit your question to give more details. 回答2: There is no

问题 I have around 6,00,000 entries in MongoDB in the following format: feature:category:count where feature could be any word, category is positive or negative, and count tells how many times a feature occurred in a document for that category. I want to cache the top 1000 tuples, let's say so as not to query database each time. How does one build an LRU cache in Python? Or are there any known solutions to this? 回答1: The LRU cache in Python3.3 has O(1) insertion, deletion, and search. The design

问题 I'd like to work with a dict in python, but limit the number of key/value pairs to X. In other words, if the dict is currently storing X key/value pairs and I perform an insertion, I would like one of the existing pairs to be dropped. It would be nice if it was the least recently inserted/accesses key but that's not completely necessary. If this exists in the standard library please save me some time and point it out! 回答1: Python 2.7 and 3.1 have OrderedDict and there are pure-Python

问题 Using the LRU Cache decorator found here: http://code.activestate.com/recipes/578078-py26-and-py30-backport-of-python-33s-lru-cache/ from lru_cache import lru_cache class Test: @lru_cache(maxsize=16) def cached_method(self, x): return x + 5 I can create a decorated class method with this but it ends up creating a global cache that applies to all instances of class Test. However, my intent was to create a per instance cache. So if I were to instantiate 3 Tests, I would have 3 LRU caches rather

问题 Please don't say EHCache or OSCache, etc. Assume for purposes of this question that I want to implement my own using just the SDK (learning by doing). Given that the cache will be used in a multithreaded environment, which datastructures would you use? I've already implemented one using LinkedHashMap and Collections#synchronizedMap, but I'm curious if any of the new concurrent collections would be better candidates. UPDATE: I was just reading through Yegge's latest when I found this nugget:

问题 I am loading data(20 elements) to another file on load...here I want to sort these 20 elements according to timestamp I am using in list element. import json from collections import OrderedDict import datetime import os if os.path.exists("qwerty.json"): record = json.load(open("qwerty.json", "r"), object_pairs_hook=OrderedDict) else: record = OrderedDict({}) fo = open("foo.txt", "wb") abc = list(record.items())[:20] print(abc) command = "" while command != 'exit': command = input('Enter a

问题 I am working on implementing a MRU(Most Recently Used) cache in my project using C#. I googled some conceptions and implementations about MRU, and its contrary, LRU(Least Recently Used), and found this article http://www.informit.com/guides/content.aspx?g=dotnet&seqNum=626 that describes the implementation of MRU collection in C#. To confuse me is that I think this implementation is LRU rather than MRU. Could anyone help me to confirm this collection class is MRU or not? Following code block