C# Linq.FirstOrDefault、Linq.Where、Linq.AsParallel、List.Exists、List.Find、Dictionar.TryGetValue、HashSet.Contains 性能的比较
C# Linq.FirstOrDefault、Linq.Where、Linq.AsParallel、List.Exists、List.Find、Dictionar.TryGetValue、HashSet.Contains 性能的比较
今天我们来比较一下集合检索方法性能更优问题,测试代码
public class Entity { public int Id { get; set; } public int No { get; set; } public string Col1 { get; set; } public string Col2 { get; set; } public string Col3 { get; set; } public string Col4 { get; set; } public string Col5 { get; set; } public string Col6 { get; set; } public string Col7 { get; set; } public string Col8 { get; set; } public string Col9 { get; set; } public string Col10 { get; set; } } static void TestFindVelocity(int totalDataCount, int executeCount) { #region 构造数据 List<Entity> datas = new List<Entity>(); for (int i = 0; i < totalDataCount; i++) { var item = new Entity { No = i + 1, Col1 = Guid.NewGuid().ToString("N"), Col2 = Guid.NewGuid().ToString("N"), Col3 = Guid.NewGuid().ToString("N"), Col4 = Guid.NewGuid().ToString("N"), Col5 = Guid.NewGuid().ToString("N"), Col6 = Guid.NewGuid().ToString("N"), Col7 = Guid.NewGuid().ToString("N"), Col8 = Guid.NewGuid().ToString("N"), Col9 = Guid.NewGuid().ToString("N"), Col10 = Guid.NewGuid().ToString("N"), }; datas.Add(item); } #endregion var dicDatas = datas.ToDictionary(x => x.No); var hashSetDatas = datas.ConvertAll<Tuple<int, int>>(x => new Tuple<int, int>(x.No, x.No + 1000)).ToHashSet(); Stopwatch sw = new Stopwatch(); Random random = new Random(); Entity searchResult = null; bool searchResultBool = false; // 每次查询索引 List<int> indexs = Enumerable.Range(1, executeCount).Select(x => random.Next(1, totalDataCount)).ToList(); sw.Start(); for (int i = 0; i < executeCount; i++) { searchResult = datas.FirstOrDefault(x => x.No == indexs[i]); } sw.Stop(); Console.WriteLine($"list FirstOrDefault 耗时:{sw.ElapsedMilliseconds}"); sw.Restart(); for (int i = 0; i < executeCount; i++) { searchResult = datas.Where(x => x.No == indexs[i]).First(); } sw.Stop(); Console.WriteLine($"list Where+First 耗时:{sw.ElapsedMilliseconds}"); sw.Restart(); for (int i = 0; i < executeCount; i++) { searchResultBool = datas.Exists(x => x.No == indexs[i]); } sw.Stop(); Console.WriteLine($"list Exist 耗时:{sw.ElapsedMilliseconds}"); sw.Restart(); for (int i = 0; i < executeCount; i++) { searchResult = datas.Find(x => x.No == indexs[i]); } sw.Stop(); Console.WriteLine($"list Find 耗时:{sw.ElapsedMilliseconds}"); sw.Restart(); for (int i = 0; i < executeCount; i++) { dicDatas.TryGetValue(indexs[i], out searchResult); } sw.Stop(); Console.WriteLine($"dictionary TryGetValue 耗时:{sw.ElapsedMilliseconds}"); sw.Restart(); for (int i = 0; i < executeCount; i++) { searchResultBool = hashSetDatas.Contains(new Tuple<int, int>(indexs[i], indexs[i] + 1000)); } sw.Stop(); Console.WriteLine($"Hashset contains 耗时:{sw.ElapsedMilliseconds}"); }
结果
(集合数量,测试次数) | Linq.FirstOrDefault | Linq.Where+First |
List.Exists |
List.Find |
Dictionary.TryGetValue |
HashSet.Contains |
(100, 5000000) |
4544 | 3521 | 1992 | 1872 | 66 | 924 |
(1000, 5000000) |
41751 | 29417 | 20631 | 19490 | 70 | 869 |
(10000, 5000000) |
466918 | 397425 | 276409 | 281647 | 85 | 946 |
(50000, 5000) |
6292 | 4602 | 4252 | 3559 | 0 | 2 |
(500000, 5000) |
56988 | 55568 | 48423 | 48395 | 1 | 5 |
漫思