在并行编程中，经常会遇到多线程间操作共享集合的问题，很多时候大家都很难逃避这个问题做到一种无锁编程状态，你也知道一旦给共享集合套上lock之后，并发和伸缩能力往往会造成很大影响，这篇就来谈谈如何尽可能的减少lock锁次数甚至没有。

一：缘由

1. 业务背景

昨天在review代码的时候，看到以前自己写的这么一段代码，精简后如下：

        private static List<long> ExecuteFilterList(int shopID, List<MemoryCacheTrade> trades, List<FilterConditon> filterItemList, MatrixSearchContext searchContext){var customerIDList = new List<long>();var index = 0;Parallel.ForEach(filterItemList, new ParallelOptions() { MaxDegreeOfParallelism = 4 },(filterItem) =>{var context = new FilterItemContext(){StartTime = searchContext.StartTime,EndTime = searchContext.EndTime,ShopID = shopID,Field = filterItem.Field,FilterType = filterItem.FilterType,ItemList = filterItem.FilterValue,SearchList = trades.ToList()};var smallCustomerIDList = context.Execute();lock (filterItemList){if (index == 0){customerIDList.AddRange(smallCustomerIDList);index++;}else{customerIDList = customerIDList.Intersect(smallCustomerIDList).ToList();}}});return customerIDList;}

这段代码实现的功能是这样的，filterItemList承载着所有原子化的筛选条件，然后用多线程的形式并发执行里面的item，最后将每个item获取的客户人数集合在高层进行整体求交，画个简图就是下面这样。

2. 问题分析

其实这代码存在着一个很大的问题，在Parallel中直接使用lock锁的话，filterItemList有多少个，我的lock就会锁多少次，这对并发和伸缩性是有一定影响的，现在就来想想怎么优化吧！

3. 测试案例

为了方便演示，我模拟了一个小案例，方便大家看到实时结果，修改后的代码如下：

        public static void Main(string[] args){var filterItemList = new List<string>() { "conditon1", "conditon2", "conditon3", "conditon4", "conditon5", "conditon6" };ParallelTest1(filterItemList);}public static void ParallelTest1(List<string> filterItemList){var totalCustomerIDList = new List<int>();bool isfirst = true;Parallel.ForEach(filterItemList, new ParallelOptions() { MaxDegreeOfParallelism = 2 }, (query) =>{var smallCustomerIDList = GetCustomerIDList(query);lock (filterItemList){if (isfirst){totalCustomerIDList.AddRange(smallCustomerIDList);isfirst = false;}else{totalCustomerIDList = totalCustomerIDList.Intersect(smallCustomerIDList).ToList();}Console.WriteLine($"{DateTime.Now} 被锁了");}});Console.WriteLine($"最后交集客户ID:{string.Join(",", totalCustomerIDList)}");}public static List<int> GetCustomerIDList(string query){var dict = new Dictionary<string, List<int>>(){["conditon1"] = new List<int>() { 1, 2, 4, 7 },["conditon2"] = new List<int>() { 1, 4, 6, 7 },["conditon3"] = new List<int>() { 1, 4, 5, 7 },["conditon4"] = new List<int>() { 1, 2, 3, 7 },["conditon5"] = new List<int>() { 1, 2, 4, 5, 7 },["conditon6"] = new List<int>() { 1, 3, 4, 7, 9 },};return dict[query];}------ output ------
2020/04/21 15:53:34 被锁了
2020/04/21 15:53:34 被锁了
2020/04/21 15:53:34 被锁了
2020/04/21 15:53:34 被锁了
2020/04/21 15:53:34 被锁了
2020/04/21 15:53:34 被锁了
最后交集客户ID:1,7

二：第一次优化

从结果中可以看到，filterItemList有6个，锁次数也是6次，那如何降低呢？其实实现Parallel代码的FCL大神也考虑到了这个问题，从底层给了一个很好的重载，如下所示：


public static ParallelLoopResult ForEach<TSource, TLocal>(OrderablePartitioner<TSource> source, ParallelOptions parallelOptions, Func<TLocal> localInit, Func<TSource, ParallelLoopState, long, TLocal, TLocal> body, Action<TLocal> localFinally);

这个重载很特别，多了两个参数localInit和localFinally,过会说一下什么意思，先看修改后的代码体会一下

public static void ParallelTest2(List<string> filterItemList){var totalCustomerIDList = new List<int>();var isfirst = true;Parallel.ForEach<string, List<int>>(filterItemList,new ParallelOptions() { MaxDegreeOfParallelism = 2 },() => { return null; },(query, loop, index, smalllist) =>{var smallCustomerIDList = GetCustomerIDList(query);if (smalllist == null) return smallCustomerIDList;return smalllist.Intersect(smallCustomerIDList).ToList();},(finalllist) =>{lock (filterItemList){if (isfirst){totalCustomerIDList.AddRange(finalllist);isfirst = false;}else{totalCustomerIDList = totalCustomerIDList.Intersect(finalllist).ToList();}Console.WriteLine($"{DateTime.Now} 被锁了");}});Console.WriteLine($"最后交集客户ID:{string.Join(",", totalCustomerIDList)}");}------- output ------
2020/04/21 16:11:46 被锁了
2020/04/21 16:11:46 被锁了
最后交集客户ID:1,7
Press any key to continue . . .

很好，这次优化将lock次数从6次降到了2次，这里我用了 new ParallelOptions() { MaxDegreeOfParallelism = 2 } 设置了并发度为最多2个CPU核，程序跑起来后会开两个线程，将一个大集合划分为2个小集合，相当于1个集合3个条件，第一个线程在执行3个条件的起始处会执行你的localInit函数，在3个条件迭代完之后再执行你的localFinally，第二个线程也是按照同样方式执行自己的3个条件，说的有点晦涩，画一张图说明吧。

三：第二次优化

如果你了解Task\这种带有返回值的Task，这就好办了，多少个filterItemList就可以开多少个Task，反正Task底层是使用线程池承载的，所以不用怕，这样就完美的实现无锁编程。

public static void ParallelTest3(List<string> filterItemList){var totalCustomerIDList = new List<int>();var tasks = new Task<List<int>>[filterItemList.Count];for (int i = 0; i < filterItemList.Count; i++){tasks[i] = Task.Factory.StartNew((query) =>{return GetCustomerIDList(query.ToString());}, filterItemList[i]);}Task.WaitAll(tasks);for (int i = 0; i < tasks.Length; i++){var smallCustomerIDList = tasks[i].Result;if (i == 0){totalCustomerIDList.AddRange(smallCustomerIDList);}else{totalCustomerIDList = totalCustomerIDList.Intersect(smallCustomerIDList).ToList();}}Console.WriteLine($"最后交集客户ID:{string.Join(",", totalCustomerIDList)}");}------ output -------最后交集客户ID:1,7
Press any key to continue . . .