本篇介紹在C#中，把一個大集合，或大數組分成若干個區來執行。Demo中是把一組字符串放在list中，然后并行生成MD5串，返回回來。

using?System; using System.Collections.Generic; using System.Reflection; using System.Threading.Tasks; using System.Linq; using System.Collections.Concurrent;public class Program {public static async Task Main(string[] args){await PartitionerDemoAsync();}public static string ToMD5Hash(string str){if (string.IsNullOrEmpty(str)){return null;}var bytes = Encoding.ASCII.GetBytes(str);if (bytes == null || bytes.Length == 0){return null;}using (var md5 = MD5.Create()){return string.Join("", md5.ComputeHash(bytes).Select(x => x.ToString("X2")));}}static async Task<List<string>> PartitionA(IEnumerator<string> partition){using (partition){var list = new List<string>();while (partition.MoveNext()){list.Add(ToMD5Hash(partition.Current));}Console.WriteLine($"======={list.Count}========");return await Task.FromResult(list);}}static async Task PartitionerDemoAsync(){while (true){Console.ReadLine();var source = new List<string>();for (var i = 0; i < 80000; i++){source.Add($"{i}{DateTime.Now.ToString("yyyyMMddHHmmssfffffff")}");}var list = Partitioner.Create(source).GetPartitions(12).AsParallel().Select(PartitionA);var count = 0;foreach (var item in list){count++;foreach (var t in await item){Console.WriteLine($"---{count}---{t}-----");}}}} }

我電腦是配置是8核。

這是把區分成8個后，80000個元素，三次分配的結果。元素越多，相對分配置比較均勻。

當把分區設置成12時，會發現三次分區中，總是有四個分不到的，說明.GetPartitions(12)會查看本機的cpu核心數，把分區的上限限制在核心數上，可以少于等于這個值，可以理解，多了沒有cpu去運算，也沒有意義了。

最后，用Benchmark跑一下用分區的和不分區的狀態下生成80000個md5結果：

using BenchmarkDotNet.Attributes; using BenchmarkDotNet.Running; using System; using System.Collections.Concurrent; using System.Collections.Generic; using System.Linq; using System.Security.Cryptography; using System.Text; using System.Threading.Tasks;namespace Demo01 {public class ParallelDemo2 : IDemo{public void Run(){BenchmarkRunner.Run<TestParallelDemo2>();}}public class TestParallelDemo2{[Benchmark]public void DemoAsync(){var list = new List<string>();for (var i = 0; i < 80000; i++){list.Add(ToMD5Hash($"{i}{DateTime.Now.ToString("yyyyMMddHHmmssfffffff")}"));}foreach (var item in list){// Console.WriteLine($"-----{item}-----");}}[Benchmark]public async Task PartitionerDemoAsync(){var source = new List<string>();for (var i = 0; i < 80000; i++){source.Add($"{i}{DateTime.Now.ToString("yyyyMMddHHmmssfffffff")}");}var list = Partitioner.Create(source).GetPartitions(12).AsParallel().Select(PartitionA);foreach (var item in list){foreach (var t in await item){// Console.WriteLine($"-----{t}-----");}}}string ToMD5Hash(string str){if (string.IsNullOrEmpty(str)){return null;}var bytes = Encoding.ASCII.GetBytes(str);if (bytes == null || bytes.Length == 0){return null;}using (var md5 = MD5.Create()){return string.Join("", md5.ComputeHash(bytes).Select(x => x.ToString("X2")));}}async Task<List<string>> PartitionA(IEnumerator<string> partition){using (partition){var list = new List<string>();while (partition.MoveNext()){list.Add(ToMD5Hash(partition.Current));}//Console.WriteLine($"======={list.Count}========");return await Task.FromResult(list);}}} }

分區明顯要優于普通方式，數據越多，優勢越明顯。

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