概述
基于哈希表实现集合
class HashST1Set<Key> : ISet<Key>
{
private HashST1<Key> hashST1;
public int Count { get { return hashST1.Count; } }
public bool IsEmpty { get { return hashST1.IsEmpty; } }
public HashST1Set(int M)
{
hashST1 = new HashST1<Key>(M);
}
public HashST1Set()
{
hashST1 = new HashST1<Key>();
}
public void Add(Key key)
{
hashST1.Add(key);
}
public void Remove(Key key)
{
hashST1.Remove(key);
}
public bool Contains(Key key)
{
return hashST1.Contains(key);
}
}
基于红黑树实现集合与基于哈希表实现的集合对比测试:
class Program
{
private static long TestSet(ISet<string> set, List<string> words)
{
Stopwatch t = new Stopwatch();
t.Start();
foreach (string word in words)
set.Add(word);
t.Stop();
return t.ElapsedMilliseconds;
}
static void Main(string[] args)
{
Console.WriteLine("双城记");
List<string> words = TestHelper.ReadFile("测试文件1/双城记.txt");
Console.WriteLine("词汇量总数:" + words.Count);
Console.WriteLine();
Console.WriteLine("(基于红黑树实现)集合");
RBT1Set<string> rbt1Set = new RBT1Set<string>();
long t1 = TestSet(rbt1Set, words);
Console.WriteLine("不同单词的总数:" + rbt1Set.Count);
Console.WriteLine("运行时间:" + t1 + "ms");
Console.WriteLine();
Console.WriteLine("(基于哈希表实现)集合");
HashST1Set<string> hashST1Set = new HashST1Set<string>();
long t2 = TestSet(hashST1Set, words);
Console.WriteLine("不同单词的总数:" + hashST1Set.Count);
Console.WriteLine("运行时间:" + t2 + "ms");
Console.WriteLine();
Console.Read();
}
}
哈希表对于无序的数据计算更快。
基于哈希表实现映射
哈希表映射底层代码:
class HashST2<Key, Value>
{
private LinkedList3<Key, Value>[] hashtable; //每个位置都指向一条链表,将冲突的元素都存在链表中
private int M;
private int N;
public HashST2(int M)
{
this.M = M;
N = 0;
hashtable = new LinkedList3<Key, Value>[M];
for (int i = 0; i < M; i++)
hashtable[i] = new LinkedList3<Key, Value>();
}
public HashST2() : this(97) { }
public int Count { get { return N; } }
public bool IsEmpty { get { return N == 0; } }
//将键转化为数组的索引
private int Hash(Key key)
{
return (key.GetHashCode() & 0x7fffffff) % M;
}
public void Add(Key key, Value value)
{
LinkedList3<Key, Value> list = hashtable[Hash(key)];
if (list.Contains(key))
list.Set(key, value);
else
{
list.Add(key, value);
N++;
}
}
public void Remove(Key key)
{
LinkedList3<Key, Value> list = hashtable[Hash(key)];
if (list.Contains(key))
{
list.Remove(key);
N--;
}
}
public bool Contains(Key key)
{
LinkedList3<Key, Value> list = hashtable[Hash(key)];
return list.Contains(key);
}
public Value Get(Key key)
{
LinkedList3<Key, Value> list = hashtable[Hash(key)];
return list.Get(key);
}
public void Set(Key key, Value newValue)
{
LinkedList3<Key, Value> list = hashtable[Hash(key)];
list.Set(key, newValue);
}
}
基于哈希表实现映射:
class HashST2Dictionary<Key,Value> :IDictionary<Key,Value>
{
private HashST2<Key, Value> hashST2;
public int Count { get { return hashST2.Count; } }
public bool IsEmpty { get { return hashST2.IsEmpty; } }
public HashST2Dictionary(int M)
{
hashST2 = new HashST2<Key, Value>(M);
}
public HashST2Dictionary()
{
hashST2 = new HashST2<Key, Value>();
}
public void Add(Key key, Value value)
{
hashST2.Add(key, value);
}
public void Remove(Key key)
{
hashST2.Remove(key);
}
public bool ContainsKey(Key key)
{
return hashST2.Contains(key);
}
public Value Get(Key key)
{
return hashST2.Get(key);
}
public void Set(Key key, Value newValue)
{
hashST2.Set(key, newValue);
}
}
基于红黑树实现字典与基于哈希表实现字典对比测试:
class Program
{
private static long TestDictionary(IDictionary<string,int> dic, List<string> words)
{
Stopwatch t = new Stopwatch();
t.Start();
foreach (var word in words)
{
if (!dic.ContainsKey(word))
dic.Add(word, 1);
else
dic.Set(word, dic.Get(word) + 1);
}
t.Stop();
return t.ElapsedMilliseconds;
}
static void Main(string[] args)
{
Console.WriteLine("双城记");
List<string> words = TestHelper.ReadFile("测试文件1/双城记.txt");
Console.WriteLine("词汇量总数:" + words.Count);
Console.WriteLine();
Console.WriteLine("(基于红黑树实现)字典");
RBT2Dictionary<string, int> dic1 = new RBT2Dictionary<string, int>();
long t1 = TestDictionary(dic1, words);
Console.WriteLine("不同单词的总数:" + dic1.Count);
Console.WriteLine("city出现的频次:"+dic1.Get("city"));
Console.WriteLine("运行时间:" + t1 + "ms");
Console.WriteLine();
Console.WriteLine("(基于哈希表实现)字典");
//统计只有一万个数据左右,传入997可以保证平均每条链表的长度为10左右,提升性能
HashST2Dictionary<string, int> dic2 = new HashST2Dictionary<string, int>(997);
long t2 = TestDictionary(dic2, words);
Console.WriteLine("不同单词的总数:" + dic2.Count);
Console.WriteLine("city出现的频次:"+dic2.Get("city"));
Console.WriteLine("运行时间:" + t2 + "ms");
Console.WriteLine();
Console.Read();
}
}
最后
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