本篇介绍在C#中，把一个大集合，或大数组分成若干个区来执行。Demo中是把一组字符串放在list中，然后并行生成MD5串，返回回来。
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($"---{count}---{t}-----");}}}}
}
我电脑是配置是8核。
这是把区分成8个后，80000个元素，三次分配的结果。元素越多，相对分配置比较均匀。
当把分区设置成12时，会发现三次分区中，总是有四个分不到的，说明.GetPartitions(12)会查看本机的cpu核心数，把分区的上限限制在核心数上，可以少于等于这个值，可以理解，多了没有cpu去运算，也没有意义了。
最后，用Benchmark跑一下用分区的和不分区的状态下生成80000个md5结果：
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;
using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Linq;
using System.Security.Cryptography;
using System.Text;
using System.Threading.Tasks;namespace Demo01
{public class ParallelDemo2 : IDemo{public void Run(){BenchmarkRunner.Run<TestParallelDemo2>();}}public class TestParallelDemo2{[Benchmark]public void DemoAsync(){var list = new List<string>();for (var i = 0; i < 80000; i++){list.Add(ToMD5Hash($"{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);}}}
}分区明显要优于普通方式，数据越多，优势越明显。
