I\'m doing a document viewer for some document format. To make it easier, let\'s say this is a PDF viewer, a Desktop application. One requirement for the s
The .NET Framework has always had the ability to keep weak references to objects.
Basically, weak references are references to objects that the runtime considers "unimportant" and that may be removed by a garbage collection run at any point in time. This can be used, for example, to cache things, but you'd have no control over what gets colected and what not.
On the other hand, it's very simple to use and it may just be what you need.
Dave
I wrote an LRU Cache and some test cases, feel free to use it.
You can read through the source on my blog.
For the lazy (here it is minus the test cases):
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
namespace LRUCache {
public class IndexedLinkedList<T> {
LinkedList<T> data = new LinkedList<T>();
Dictionary<T, LinkedListNode<T>> index = new Dictionary<T, LinkedListNode<T>>();
public void Add(T value) {
index[value] = data.AddLast(value);
}
public void RemoveFirst() {
index.Remove(data.First.Value);
data.RemoveFirst();
}
public void Remove(T value) {
LinkedListNode<T> node;
if (index.TryGetValue(value, out node)) {
data.Remove(node);
index.Remove(value);
}
}
public int Count {
get {
return data.Count;
}
}
public void Clear() {
data.Clear();
index.Clear();
}
public T First {
get {
return data.First.Value;
}
}
}
}
LRUCache
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
namespace LRUCache {
public class LRUCache<TKey, TValue> : IDictionary<TKey, TValue> {
object sync = new object();
Dictionary<TKey, TValue> data;
IndexedLinkedList<TKey> lruList = new IndexedLinkedList<TKey>();
ICollection<KeyValuePair<TKey, TValue>> dataAsCollection;
int capacity;
public LRUCache(int capacity) {
if (capacity <= 0) {
throw new ArgumentException("capacity should always be bigger than 0");
}
data = new Dictionary<TKey, TValue>(capacity);
dataAsCollection = data;
this.capacity = capacity;
}
public void Add(TKey key, TValue value) {
if (!ContainsKey(key)) {
this[key] = value;
} else {
throw new ArgumentException("An attempt was made to insert a duplicate key in the cache.");
}
}
public bool ContainsKey(TKey key) {
return data.ContainsKey(key);
}
public ICollection<TKey> Keys {
get {
return data.Keys;
}
}
public bool Remove(TKey key) {
bool existed = data.Remove(key);
lruList.Remove(key);
return existed;
}
public bool TryGetValue(TKey key, out TValue value) {
return data.TryGetValue(key, out value);
}
public ICollection<TValue> Values {
get { return data.Values; }
}
public TValue this[TKey key] {
get {
var value = data[key];
lruList.Remove(key);
lruList.Add(key);
return value;
}
set {
data[key] = value;
lruList.Remove(key);
lruList.Add(key);
if (data.Count > capacity) {
data.Remove(lruList.First);
lruList.RemoveFirst();
}
}
}
public void Add(KeyValuePair<TKey, TValue> item) {
Add(item.Key, item.Value);
}
public void Clear() {
data.Clear();
lruList.Clear();
}
public bool Contains(KeyValuePair<TKey, TValue> item) {
return dataAsCollection.Contains(item);
}
public void CopyTo(KeyValuePair<TKey, TValue>[] array, int arrayIndex) {
dataAsCollection.CopyTo(array, arrayIndex);
}
public int Count {
get { return data.Count; }
}
public bool IsReadOnly {
get { return false; }
}
public bool Remove(KeyValuePair<TKey, TValue> item) {
bool removed = dataAsCollection.Remove(item);
if (removed) {
lruList.Remove(item.Key);
}
return removed;
}
public IEnumerator<KeyValuePair<TKey, TValue>> GetEnumerator() {
return dataAsCollection.GetEnumerator();
}
System.Collections.IEnumerator System.Collections.IEnumerable.GetEnumerator() {
return ((System.Collections.IEnumerable)data).GetEnumerator();
}
}
}
Caching application block and ASP.NET cache are both options however, although they do LRU, the only kind of disk utilization that happens is by memory paging. I think there are ways you can optimize this that are more specific to your goal to get a better output. Here are some thoughts:
I'd certainly avoid using a plain hash table though.