标签：framework img ash [] 初始化 add 执行 png redis
现在用redis来做数据缓存的越来越多了，很多项目都有初始化redis数据的过程，由于初始化的数据比较大，那么该过程越快越好。这里我们以HashSet方法为例，
这里我们推荐用HashEntry[] hashFields方法传入多个fields，应为它发送的HMSET指令即批量插入数据，另一个方法发送的HSET指令。
在阅读StackExchange.Redis里面我确实没有找到pipe指令，后来发现该指令的实现是：通过CreateBatch方法实现的。源码的单元测试例子是：
using System; using System.Collections.Generic; using System.Threading.Tasks; using NUnit.Framework; namespace Tests { [TestFixture] public class Batches { [Test] public void TestBatchNotSent() { using (var muxer = Config.GetUnsecuredConnection()) { var conn = muxer.GetDatabase(0); conn.KeyDeleteAsync("batch"); conn.StringSetAsync("batch", "batch-not-sent"); var tasks = new List<Task>(); var batch = conn.CreateBatch(); tasks.Add(batch.KeyDeleteAsync("batch")); tasks.Add(batch.SetAddAsync("batch", "a")); tasks.Add(batch.SetAddAsync("batch", "b")); tasks.Add(batch.SetAddAsync("batch", "c")); Assert.AreEqual("batch-not-sent", (string)conn.StringGet("batch")); } } [Test] public void TestBatchSent() { using (var muxer = Config.GetUnsecuredConnection()) { var conn = muxer.GetDatabase(0); conn.KeyDeleteAsync("batch"); conn.StringSetAsync("batch", "batch-sent"); var tasks = new List<Task>(); var batch = conn.CreateBatch(); tasks.Add(batch.KeyDeleteAsync("batch")); tasks.Add(batch.SetAddAsync("batch", "a")); tasks.Add(batch.SetAddAsync("batch", "b")); tasks.Add(batch.SetAddAsync("batch", "c")); batch.Execute(); var result = conn.SetMembersAsync("batch"); tasks.Add(result); Task.WhenAll(tasks.ToArray()); var arr = result.Result; Array.Sort(arr, (x, y) => string.Compare(x, y)); Assert.AreEqual(3, arr.Length); Assert.AreEqual("a", (string)arr[0]); Assert.AreEqual("b", (string)arr[1]); Assert.AreEqual("c", (string)arr[2]); } } } }
var batch = conn.CreateBatch();这里的batch实际就是管道。真正的执行需要调用 batch.Execute()方法。网上也有类似的文章 redis大幅性能提升之使用管道（PipeLine）和批量（Batch）操作
StackExchange.Redis 管道 批量 高性能插入数据
标签：framework img ash [] 初始化 add 执行 png redis
原文地址：http://www.cnblogs.com/majiang/p/6442291.html
