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：
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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。
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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。
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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：
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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。
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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。
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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。
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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);
