如何使用 azure 存储表实现每秒 10 次以上的插入

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问题描述

我编写了简单的 WorkerRole，将测试数据添加到表中.插入的代码是这样的.

I write simple WorkerRole that add test data in to table. The code of inserts is like this.

var TableClient = this.StorageAccount.CreateCloudTableClient();
TableClient.CreateTableIfNotExist(TableName);
var Context = TableClient.GetDataServiceContext();

this.Context.AddObject(TableName, obj);
this.Context.SaveChanges();

此代码针对每个客户端请求运行.我使用 1-30 个客户端线程进行测试.我对各种大小的实例进行了多次尝试.我不知道我做错了什么，但每秒插入次数达不到 10 次.如果有人知道如何提高速度，请告诉我.谢谢

This code runs for each client requests. I do test with 1-30 client threads.I have many trys with various count of instances of various sizes. I don't know what I do wrong but I can't reach more 10 inserts per second.If someone know how to increase speed please advise me.Thanks

更新

删除 CreateTableIfNotExist 对我的插入测试没有影响.
切换模式为expect100Continue="false" useNagleAlgorithm="false" 在插入速率跳到30-40 ips 时产生短时间效果.但是，30 秒后插入率下降到 6 ips，超时 50%.

推荐答案

为了加快处理速度，您应该使用批处理事务(实体组事务)，允许您在单个请求中提交多达 100 个项目:

To speed things up you should use batch transactions (Entity Group Transactions), allowing you to commit up to 100 items within a single request:

foreach (var item in myItemsToAdd)
{
    this.Context.AddObject(TableName, item);
}
this.Context.SaveChanges(SaveChangesOptions.Batch);

您可以将此与 Partitioner.Create 结合使用 (+ AsParallel) 在每批 100 个项目的不同线程/核心上发送多个请求，使事情变得非常快.

You can combine this with Partitioner.Create (+ AsParallel) to send multiple requests on different threads/cores per batch of 100 items to make things really fast.

但在执行所有这些操作之前，阅读限制使用批处理事务(100 个项目，每个事务 1 个分区，......).

But before doing all of this, read through the limitations of using batch transactions (100 items, 1 partition per transaction, ...).

更新:

由于您不能使用事务，这里有一些其他提示.看看这个 MSDN 线程关于在使用表存储时提高性能.我写了一些代码来告诉你区别:

Since you can't use transactions here are some other tips. Take a look at this MSDN thread about improving performance when using table storage. I wrote some code to show you the difference:

    private static void SequentialInserts(CloudTableClient client)
    {
        var context = client.GetDataServiceContext();
        Trace.WriteLine("Starting sequential inserts.");

        var stopwatch = new Stopwatch();
        stopwatch.Start();

        for (int i = 0; i < 1000; i++)
        {
            Trace.WriteLine(String.Format("Adding item {0}. Thread ID: {1}", i, Thread.CurrentThread.ManagedThreadId));
            context.AddObject(TABLENAME, new MyEntity()
            {
                Date = DateTime.UtcNow,
                PartitionKey = "Test",
                RowKey = Guid.NewGuid().ToString(),
                Text = String.Format("Item {0} - {1}", i, Guid.NewGuid().ToString())
            });
            context.SaveChanges();
        }

        stopwatch.Stop();
        Trace.WriteLine("Done in: " + stopwatch.Elapsed.ToString());
    }

所以，我第一次运行时得到以下输出:

So, the first time I run this I get the following output:

Starting sequential inserts.
Adding item 0. Thread ID: 10
Adding item 1. Thread ID: 10
..
Adding item 999. Thread ID: 10
Done in: 00:03:39.9675521

添加 1000 个项目需要 3 多分钟.现在，我根据 MSDN 论坛上的提示更改了 app.config(maxconnection 应为 12 * CPU 核数):

It takes more than 3 minutes to add 1000 items. Now, I changed the app.config based on the tips on the MSDN forum (maxconnection should be 12 * number of CPU cores):

  <system.net>
    <settings>
      <servicePointManager expect100Continue="false" useNagleAlgorithm="false"/>
    </settings>
    <connectionManagement>
      <add address = "*" maxconnection = "48" />
    </connectionManagement>
  </system.net>

再次运行应用程序后，我得到以下输出:

And after running the application again I get this output:

Starting sequential inserts.
Adding item 0. Thread ID: 10
Adding item 1. Thread ID: 10
..
Adding item 999. Thread ID: 10
Done in: 00:00:18.9342480

从超过 3 分钟到 18 秒.有什么不同！但我们还可以做得更好.下面是一些使用 Partitioner 插入所有项目的代码(插入将并行发生):

From over 3 minutes to 18 seconds. What a difference! But we can do even better. Here is some code inserts all items using a Partitioner (inserts will happen in parallel):

    private static void ParallelInserts(CloudTableClient client)
    {
        Trace.WriteLine("Starting parallel inserts.");

        var stopwatch = new Stopwatch();
        stopwatch.Start();

        var partitioner = Partitioner.Create(0, 1000, 10);
        var options = new ParallelOptions { MaxDegreeOfParallelism = 8 };

        Parallel.ForEach(partitioner, options, range =>
        {
            var context = client.GetDataServiceContext();
            for (int i = range.Item1; i < range.Item2; i++)
            {
                Trace.WriteLine(String.Format("Adding item {0}. Thread ID: {1}", i, Thread.CurrentThread.ManagedThreadId));
                context.AddObject(TABLENAME, new MyEntity()
                {
                    Date = DateTime.UtcNow,
                    PartitionKey = "Test",
                    RowKey = Guid.NewGuid().ToString(),
                    Text = String.Format("Item {0} - {1}", i, Guid.NewGuid().ToString())
                });
                context.SaveChanges();
            }
        });

        stopwatch.Stop();
        Trace.WriteLine("Done in: " + stopwatch.Elapsed.ToString());
    }

结果:

Starting parallel inserts.
Adding item 0. Thread ID: 10
Adding item 10. Thread ID: 18
Adding item 999. Thread ID: 16
..
Done in: 00:00:04.6041978

瞧，我们从 3 分 39 秒降到了 18 秒，现在我们甚至降到了 4 秒.

Voila, from 3m39s we dropped to 18s and now we even dropped to 4s.

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