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.NET分布式Orleans - 6 - 事件溯源

时间:2024-03-28 10:47:35浏览次数:32  
标签:Orleans Task Balance options 事件 NET 分布式 public 溯源

基本概念

事件溯源(Event Sourcing)是一种设计模式,它记录并存储了应用程序状态变化的所有事件。

其核心思想是将系统中的每次状态变化都视为一个事件,并将这些事件以时间顺序的方式持久化存储。

这样,通过重放这些事件,我们可以重建系统在任何特定时间点的状态。

每个事件通常都包含了描述状态变化的必要信息,以及发生状态变化的原因和时间戳。

工作原理

工作原理方面,事件溯源主要依赖于两个关键部分:事件生成和事件存储。

当系统中发生状态变化时,会生成一个或多个事件,这些事件随后被存储到事件存储中。

事件存储需要设计成高可用、高一致且可伸缩的,以支持大规模的系统操作。

之后,当需要重建系统状态时,只需从事件存储中按顺序读取事件,并依次应用这些事件到系统状态即可。

使用场景

在Orleans7中,事件溯源主要应用在以下几个场景:

  1. 分布式系统状态同步:在分布式系统中,各个节点之间的状态同步是一个重要问题。通过事件溯源,每个节点都可以记录并发送自己的状态变化事件,其他节点则可以通过订阅这些事件来同步自己的状态。

  2. 历史数据追踪和审计:在某些业务场景下,需要追踪系统的历史操作记录,以进行审计或分析。事件溯源提供了完整的操作历史,可以方便地查询和回放历史事件。

  3. 容错和恢复:当系统发生故障时,通过事件溯源可以方便地恢复到故障发生前的状态,或者根据事件日志进行故障排查。

优势

事件溯源在Orleans7中带来了以下优势:

  1. 数据完整性和一致性:由于事件溯源记录了所有状态变化的历史,因此可以确保数据的完整性和一致性。

  2. 灵活性和可扩展性:事件溯源的设计使得系统可以很容易地添加新的状态变化事件,同时也支持大规模的系统扩展。

  3. 容错和恢复能力:通过事件溯源,可以轻松地恢复到系统的任何历史状态,大大提高了系统的容错和恢复能力。

  4. 清晰的业务逻辑:每个事件都代表了一个具体的业务操作,因此通过查看事件日志,可以清晰地了解系统的业务逻辑和操作流程。

总的来说,事件溯源是一种强大而灵活的设计模式,它在Orleans7中的应用为分布式系统带来了诸多优势。对于软件开发者来说,理解和掌握事件溯源机制,将有助于构建更加健壮、可靠和可扩展的分布式系统。

示例

下面使用事件溯源,来跟踪一个账户的变更记录。

首先需要安装必须的nuget包

<PackageReference Include="Microsoft.Orleans.EventSourcing" Version="8.0.0" />
<PackageReference Include="Microsoft.Orleans.Clustering.AdoNet" Version="8.0.0" />
<PackageReference Include="Microsoft.Orleans.Persistence.AdoNet" Version="8.0.0" />
<PackageReference Include="Microsoft.Orleans.Server" Version="8.0.0" />

然后设置Orleans,除了Orleans的常规设置外,还需要 siloHostBuilder.AddLogStorageBasedLogConsistencyProvider("LogStorage") 来设置LogConsistencyProvider

builder.Host.UseOrleans(static siloHostBuilder =>
{
    var invariant = "System.Data.SqlClient";

    var connectionString = "Data Source=localhost\\SQLEXPRESS;Initial Catalog=orleanstest;User Id=sa;Password=12334;";

    siloHostBuilder.AddLogStorageBasedLogConsistencyProvider("LogStorage");

    // Use ADO.NET for clustering
    siloHostBuilder.UseAdoNetClustering(options =>
    {
        options.Invariant = invariant;
        options.ConnectionString = connectionString;
    }).ConfigureLogging(logging => logging.AddConsole());

    siloHostBuilder.Configure<ClusterOptions>(options =>
    {
        options.ClusterId = "my-first-cluster";
        options.ServiceId = "SampleApp";
    });

    // Use ADO.NET for persistence
    siloHostBuilder.AddAdoNetGrainStorage("GrainStorageForTest", options =>
    {
        options.Invariant = invariant;
        options.ConnectionString = connectionString;
        //options.GrainStorageSerializer = new JsonGrainStorageSerializer()
     
    });
});

定义账户的存储和提取事件类

// the classes below represent events/transactions on the account
// all fields are user-defined (none have a special meaning),
// so these can be any type of object you like, as long as they are serializable
// (so they can be sent over the wire and persisted in a log).

[Serializable]
[GenerateSerializer]
public abstract class Transaction
{
    /// <summary> A unique identifier for this transaction  </summary>
    [Id(0)]
    public Guid Guid { get; set; }

    /// <summary> A description for this transaction  </summary>
    [Id(1)]
    public string Description { get; set; }

    /// <summary> time on which the request entered the system  </summary>
    [Id(2)]
    public DateTime IssueTime { get; set; }
}

[Serializable]
[GenerateSerializer]
public class DepositTransaction : Transaction
{
    [Id(0)]
    public uint DepositAmount { get; set; }
}

[Serializable]
[GenerateSerializer]
public class WithdrawalTransaction : Transaction
{
    [Id(0)]
    public uint WithdrawalAmount { get; set; }
}

再定义账户的Grain,其中有存钱,取钱,获取余额,与变更记录操作

Grain类必须具有 LogConsistencyProviderAttribute 才能指定日志一致性提供程序。 还需要 StorageProviderAttribute设置存储。

/// <summary>
/// An example of a journaled grain that models a bank account.
/// 
/// Configured to use the default storage provider.
/// Configured to use the LogStorage consistency provider.
/// 
/// This provider persists all events, and allows us to retrieve them all.
/// </summary>

/// <summary>
/// A grain that models a bank account
/// </summary>
public interface IAccountGrain : IGrainWithStringKey
{
    Task<uint> Balance();

    Task Deposit(uint amount, Guid guid, string desc);

    Task<bool> Withdraw(uint amount, Guid guid, string desc);

    Task<IReadOnlyList<Transaction>> GetTransactionLog();
}

[StorageProvider(ProviderName = "GrainStorageForTest")]
[LogConsistencyProvider(ProviderName = "LogStorage")]

public class AccountGrain : JournaledGrain<AccountGrain.GrainState, Transaction>, IAccountGrain
{
    /// <summary>
    /// The state of this grain is just the current balance.
    /// </summary>
    [Serializable]
    [Orleans.GenerateSerializer]
    public class GrainState
    {
        [Orleans.Id(0)]
        public uint Balance { get; set; }

        public void Apply(DepositTransaction d)
        {
            Balance = Balance + d.DepositAmount;
        }

        public void Apply(WithdrawalTransaction d)
        {
            if (d.WithdrawalAmount > Balance)
                throw new InvalidOperationException("we make sure this never happens");

            Balance = Balance - d.WithdrawalAmount;
        }
    }

    public Task<uint> Balance()
    {
        return Task.FromResult(State.Balance);
    }

    public Task Deposit(uint amount, Guid guid, string description)
    {
        RaiseEvent(new DepositTransaction()
        {
            Guid = guid,
            IssueTime = DateTime.UtcNow,
            DepositAmount = amount,
            Description = description
        });

        // we wait for storage ack
        return ConfirmEvents();
    }

    public Task<bool> Withdraw(uint amount, Guid guid, string description)
    {
        // if the balance is too low, can't withdraw
        // reject it immediately
        if (State.Balance < amount)
            return Task.FromResult(false);

        // use a conditional event for withdrawal
        // (conditional events commit only if the version hasn't already changed in the meantime)
        // this is important so we can guarantee that we never overdraw
        // even if racing with other clusters, of in transient duplicate grain situations
        return RaiseConditionalEvent(new WithdrawalTransaction()
        {
            Guid = guid,
            IssueTime = DateTime.UtcNow,
            WithdrawalAmount = amount,
            Description = description
        });
    }

    public Task<IReadOnlyList<Transaction>> GetTransactionLog()
    {
        return RetrieveConfirmedEvents(0, Version);
    }
}

最后即可通过client生成grain,并获取账户变动记录

var palyer = client.GetGrain<IAccountGrain>("zhangsan");
await palyer.Deposit(1000, Guid.NewGuid(), "aaa");
var logs = await palyer.GetTransactionLog();
return Results.Ok(logs);

 

标签:Orleans,Task,Balance,options,事件,NET,分布式,public,溯源
From: https://www.cnblogs.com/chenyishi/p/18099103

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