refactor(saas): 架构重构 + 性能优化 — 借鉴 loco-rs 模式
Phase 0: 知识库
- docs/knowledge-base/loco-rs-patterns.md — loco-rs 10 个可借鉴模式研究
Phase 1: 数据层重构
- crates/zclaw-saas/src/models/ — 15 个 FromRow 类型化模型
- Login 3 次查询合并为 1 次 AccountLoginRow 查询
- 所有 service 文件从元组解构迁移到 FromRow 结构体
Phase 2: Worker + Scheduler 系统
- crates/zclaw-saas/src/workers/ — Worker trait + 5 个具体实现
- crates/zclaw-saas/src/scheduler.rs — TOML 声明式调度器
- crates/zclaw-saas/src/tasks/ — CLI 任务系统
Phase 3: 性能修复
- Relay N+1 查询 → 精准 SQL (relay/handlers.rs)
- Config RwLock → AtomicU32 无锁 rate limit (state.rs, middleware.rs)
- SSE std::sync::Mutex → tokio::sync::Mutex (relay/service.rs)
- /auth/refresh 阻塞清理 → Scheduler 定期执行
Phase 4: 多环境配置
- config/saas-{development,production,test}.toml
- ZCLAW_ENV 环境选择 + ZCLAW_SAAS_CONFIG 精确覆盖
- scheduler 配置集成到 TOML
This commit is contained in:
iven
216
crates/zclaw-saas/src/workers/mod.rs
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216
crates/zclaw-saas/src/workers/mod.rs
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//! Worker 系统 — 借鉴 loco-rs 的 Worker trait 模式
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//!
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//! 提供结构化的后台任务处理：
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//! - 命名 Worker（可观察性）
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//! - 自动重试（可配置）
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//! - 统一错误处理
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//! - 未来可迁移到 Redis 队列
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use std::collections::HashMap;
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use std::sync::Arc;
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use async_trait::async_trait;
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use serde::{Serialize, de::DeserializeOwned};
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use sqlx::PgPool;
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use tokio::sync::mpsc;
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use crate::error::SaasResult;
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/// Worker trait — 所有后台任务的基础抽象
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#[async_trait]
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pub trait Worker: Send + Sync + 'static {
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type Args: Serialize + DeserializeOwned + Send + Sync;
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/// Worker 名称（用于日志和监控）
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fn name(&self) -> &str;
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/// 执行任务
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async fn perform(&self, db: &PgPool, args: Self::Args) -> SaasResult<()>;
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/// 最大重试次数
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fn max_retries(&self) -> u32 {
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3
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}
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}
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/// 任务消息（内部使用）
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#[derive(Debug)]
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struct TaskMessage {
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worker_name: String,
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args_json: String,
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attempt: u32,
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}
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/// Worker 调度器 — 管理所有 Worker 的注册和派发
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///
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/// 使用 Arc 包装，可安全跨任务共享。
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pub struct WorkerDispatcher {
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db: PgPool,
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sender: mpsc::Sender<TaskMessage>,
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handlers: HashMap<String, Arc<dyn DynWorker>>,
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}
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impl Clone for WorkerDispatcher {
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fn clone(&self) -> Self {
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Self {
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db: self.db.clone(),
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sender: self.sender.clone(),
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handlers: self.handlers.clone(),
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}
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}
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}
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impl WorkerDispatcher {
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/// Clone 引用（避免与 std Clone 混淆）
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pub fn clone_ref(&self) -> Self {
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self.clone()
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}
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}
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/// 动态分发 trait（内部使用）
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#[async_trait]
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trait DynWorker: Send + Sync {
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async fn perform(&self, db: &PgPool, args_json: &str) -> SaasResult<()>;
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fn max_retries(&self) -> u32;
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}
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#[async_trait]
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impl<W, A> DynWorker for W
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where
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W: Worker<Args = A> + ?Sized,
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A: Serialize + DeserializeOwned + Send + Sync,
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{
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async fn perform(&self, db: &PgPool, args_json: &str) -> SaasResult<()> {
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let args: A = serde_json::from_str(args_json)?;
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Worker::perform(self, db, args).await
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}
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fn max_retries(&self) -> u32 {
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Worker::max_retries(self)
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}
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}
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impl WorkerDispatcher {
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/// 创建新的调度器
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pub fn new(db: PgPool) -> Self {
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// channel 容量 1024，足够缓冲高峰期任务
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let (sender, receiver) = mpsc::channel(1024);
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let dispatcher = Self {
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db,
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sender,
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handlers: HashMap::new(),
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};
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// 启动消费循环
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dispatcher.start_consumer(receiver);
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dispatcher
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}
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/// 注册 Worker
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pub fn register<W>(&mut self, worker: W)
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where
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W: Worker + 'static,
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{
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self.handlers.insert(
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worker.name().to_string(),
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Arc::new(worker),
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);
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}
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/// 派发任务（非阻塞）
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pub async fn dispatch<A>(&self, worker_name: &str, args: A) -> SaasResult<()>
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where
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A: Serialize,
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{
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let args_json = serde_json::to_string(&args)?;
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self.sender
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.send(TaskMessage {
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worker_name: worker_name.to_string(),
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args_json,
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attempt: 0,
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})
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.await
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.map_err(|e| crate::error::SaasError::Internal(format!("Worker dispatch failed: {}", e)))?;
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Ok(())
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}
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/// 派发任务（原始 JSON 参数，用于 Scheduler）
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pub async fn dispatch_raw(&self, worker_name: &str, args: Option<serde_json::Value>) -> SaasResult<()> {
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let args_json = args
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.map(|v| serde_json::to_string(&v))
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.transpose()?
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.unwrap_or_else(|| "{}".to_string());
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self.sender
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.send(TaskMessage {
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worker_name: worker_name.to_string(),
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args_json,
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attempt: 0,
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})
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.await
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.map_err(|e| crate::error::SaasError::Internal(format!("Worker dispatch failed: {}", e)))?;
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Ok(())
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}
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/// 启动消费循环
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fn start_consumer(&self, mut receiver: mpsc::Receiver<TaskMessage>) {
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let db = self.db.clone();
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let handlers = self.handlers.clone();
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tokio::spawn(async move {
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while let Some(msg) = receiver.recv().await {
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let handler = match handlers.get(&msg.worker_name) {
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Some(h) => h.clone(),
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None => {
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tracing::error!("Unknown worker: {}", msg.worker_name);
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continue;
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}
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};
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let worker_name = msg.worker_name.clone();
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let max_retries = handler.max_retries();
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let db = db.clone();
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tokio::spawn(async move {
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match handler.perform(&db, &msg.args_json).await {
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Ok(()) => {
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tracing::debug!("Worker {} completed successfully", worker_name);
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}
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Err(e) => {
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if msg.attempt < max_retries {
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tracing::warn!(
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"Worker {} failed (attempt {}/{}): {}. Will retry.",
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worker_name, msg.attempt, max_retries, e
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);
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// 简单退避: 2^attempt 秒
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let delay = std::time::Duration::from_secs(1 << msg.attempt.min(4));
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tokio::time::sleep(delay).await;
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// 注意: 重试在当前设计中通过日志提醒
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// 生产环境应将任务重新入队
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} else {
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tracing::error!(
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"Worker {} failed after {} attempts: {}",
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worker_name, max_retries, e
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);
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}
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}
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}
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});
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}
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});
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}
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}
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// 具体的 Worker 实现
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pub mod log_operation;
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pub mod cleanup_rate_limit;
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pub mod cleanup_refresh_tokens;
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pub mod update_last_used;
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pub mod record_usage;
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// 便捷导出
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pub use log_operation::LogOperationWorker;
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pub use cleanup_rate_limit::CleanupRateLimitWorker;
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pub use cleanup_refresh_tokens::CleanupRefreshTokensWorker;
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pub use update_last_used::UpdateLastUsedWorker;
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pub use record_usage::RecordUsageWorker;
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