C# Linq延迟查询的执行实例代码
C# Linq延迟查询
在定义linq查询表达式时,查询是不会执行,查询会在迭代数据项时运行。它使用yield return 语句返回谓词为true的元素。
var names = new List<string> { "Nino", "Alberto", "Juan", "Mike", "Phil" }; var namesWithJ = from n in names where n.StartsWith("J") orderby n select n; Console.WriteLine("First iteration"); foreach (string name in namesWithJ) { Console.WriteLine(name); } Console.WriteLine(); names.Add("John"); names.Add("Jim"); names.Add("Jack"); names.Add("Denny"); Console.WriteLine("Second iteration"); foreach (string name in namesWithJ) { Console.WriteLine(name); }
运行结果为
First iteration
JuanSecond iteration
Jack
Jim
John
Juan
从执行结果可以看出,当在定义namesWithJ时并不会执行,而是在执行每个foreach语句时进行,所以后面增加的“John”、“Jim”、“Jack”和“Denny”在第二次迭代时也会参与进来。
ToArray()、ToList()等方法可以改变这个操作,把namesWithJ的定义语句修改为
var namesWithJ = (from n in names where n.StartsWith("J") orderby n select n).ToList();
运行结果为
First iteration
JuanSecond iteration
Juan
在日常工作中,我们常会使用 datas.Where(x=>x.XX == XXX).FirstOrDefault() 和 datas.FirstOrDefault(x=>x.XX == XXX),其实这两种写法性能是等效的,如果真的要在性能上分个高低,请见下面
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 { 【文章出处:http://www.1234xp.com/tbm.html转载请保留出处】 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
(100, 5000000)
(1000, 5000000)
(10000, 5000000)
(50000, 5000)
(500000, 5000)
应避免错误写法是 datas.Where(x=>x.XX == XXX).ToList()[0]
。
总结
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