本章将和大家分享.NET中的本地缓存。
本章将和大家分享如何使用数据分拆+lock锁的方式来实现本地缓存。
系统性能优化的第一步,就是使用缓存。缓存包括:客户端缓存---CDN缓存---反向代理缓存---本地缓存。

下面我们直接通过代码来看下本地缓存的基本原理:
using System;using System.Collections.Generic;using System.Threading;using System.Threading.Tasks;namespace MyCache{ /// <summary> /// 第三方数据存储和获取的地方 ///  /// 过期策略: ///  永久有效 ///  绝对过期---有个时间点,超过就过期 ///  滑动过期---多久之后过期,如果期间更新/查询/检查存在,就再次延长 ///  /// 主动清理+被动清理,保证过期数据不会被查询;过期数据也不会滞留太久 ///  /// 多线程操作非线程安全的容器,会造成冲突,那有什么解决方案呢? ///  1、使用线程安全容器ConcurrentDictionary ///  2、用lock---Add/Remove/遍历 解决问题了,但是性能怎么办呢? ///  怎么降低影响,提升性能呢? --- 数据分拆,多个数据容器,多个锁,容器之间可以并发。 /// </summary> public class CustomCache {  #region 字段和属性  /// <summary>  /// 模拟获取系统的CPU数  /// </summary>  private static int _cpuNumer = 0;  /// <summary>  /// 动态初始化多个容器  /// </summary>  private static List<Dictionary<string, object>> _dictionaryList = new List<Dictionary<string, object>>();  /// <summary>  /// 动态初始化多个锁  /// </summary>  private static List<object> _lockList = new List<object>();  #endregion 字段和属性  #region 静态构造函数  /// <summary>  /// 静态构造函数  /// </summary>  static CustomCache()  {   _cpuNumer = 4;   for (int i = 0; i < _cpuNumer; i++)   {    _dictionaryList.Add(new Dictionary<string, object>());    _lockList.Add(new object());   }   //主动清理缓存   Task.Run(() =>   {    while (true)    {     Thread.Sleep(1000 * 60 * 10);     try     {      for (int i = 0; i < _cpuNumer; i++)      {       List<string> keyList = new List<string>();       lock (_lockList[i]) //数据分拆,减少锁的影响范围       {        foreach (var key in _dictionaryList[i].Keys)        {         DataModel model = (DataModel)_dictionaryList[i][key];         if (model.ObsloteType != ObsloteType.Never && model.DeadLine < DateTime.Now)         {          keyList.Add(key);         }        }        keyList.ForEach(s => _dictionaryList[i].Remove(s));       }      }     }     catch (Exception ex)     {      Console.WriteLine(ex.ToString());      continue;     }    }   });  }  #endregion 静态构造函数  /// <summary>  /// 获取容器索引  /// </summary>  /// <param name="key">缓存键</param>  /// <returns>索引值</returns>  public static int GetHashCodeIndex(string key)  {   int hash = Math.Abs(key.GetHashCode()); //相对均匀而且稳定   return hash % _cpuNumer;  }  /// <summary>  /// 添加  /// </summary>  /// <param name="key">缓存键</param>  /// <param name="oValue">缓存值</param>  public static void Add(string key, object oValue)  {   int index = GetHashCodeIndex(key);   lock (_lockList[index])   {    _dictionaryList[index].Add(key, new DataModel()    {     Value = oValue,     ObsloteType = ObsloteType.Never    });   }  }  /// <summary>  /// 绝对过期  /// </summary>  /// <param name="key">缓存键</param>  /// <param name="oVaule">缓存值</param>  /// <param name="timeOutSecond">过期时间</param>  public static void Add(string key, object oVaule, int timeOutSecond)  {   int index = GetHashCodeIndex(key);   lock (_lockList[index])   {    _dictionaryList[index].Add(key, new DataModel()    {     Value = oVaule,     ObsloteType = ObsloteType.Absolutely,     DeadLine = DateTime.Now.AddSeconds(timeOutSecond)    });   }  }  /// <summary>  /// 相对过期  /// </summary>  /// <param name="key">缓存键</param>  /// <param name="oVaule">缓存值</param>  /// <param name="duration">过期时间</param>  public static void Add(string key, object oVaule, TimeSpan duration)  {   int index = GetHashCodeIndex(key);   lock (_lockList[index])   {    _dictionaryList[index].Add(key, new DataModel()    {     Value = oVaule,     ObsloteType = ObsloteType.Relative,     DeadLine = DateTime.Now.Add(duration),     Duration = duration    });   }  }  /// <summary>  /// 获取数据(要求在Get前做Exists检测)  /// </summary>  /// <typeparam name="T">类型</typeparam>  /// <param name="key">缓存键</param>  /// <returns>缓存值</returns>  public static T Get<T>(string key)  {   int index = GetHashCodeIndex(key);   return (T)((DataModel)_dictionaryList[index][key]).Value;  }.........
 
  
  
  
 
 
  
 
 
 