AI 集成的智能 Profiling 实践：从性能分析到优化闭环

go tool pprof -text <profile_data.pb.gz> > profiling.txt

      flat  flat%   sum%        cum   cum%
      50ms  6.41%  6.41%       50ms  6.41%  internal/runtime/syscall.Syscall6
      30ms  3.85% 10.26%      130ms 16.67%  runtime.scanobject
      20ms  2.56% 30.77%      100ms 12.82%  runtime.mallocgc

def build_prompt(pprof_content, code_snippet):
    messages = [
        {
            "role": "system",
            "content": "You are a professional Go performance optimization expert skilled in analyzing pprof data to identify bottlenecks and provide actionable solutions."
        },
        {
            "role": "user",
            "content": f"""
            Please help me analyze the following Go program's CPU profiling report and identify the performance bottlenecks. 
            Below is the CPU profiling data generated by the go tool pprof:
            {pprof_content}
            """
        }
    ]
    if code_snippet:
        messages.append({
            "role": "user",
            "content": f"""
            **Here is the Go program code.**  
            Please do the following:
            - Identify the problematic code segments based on the profiling report and code snippet.
            - Clearly correlate each performance issue with the profiling result (e.g., function name, time percentage).
            - Provide optimization suggestions with explanations.
            - If possible, show an optimized code snippet with a brief explanation of why it improves performance.
            **Code:**
            ```go
            {code_snippet}

        """
    })
return messages

      flat   flat%   sum%      cum   cum%
     1.50s  13.33%  13.33%   1.50s  13.33%  runtime/internal/syscall.Syscall6
     0.44s   3.91%  17.24%   1.54s  13.69%  runtime.mallocgc
     0.41s   3.64%  24.71%   1.01s   8.98%  runtime.scanobject
     0.18s   1.60%  29.87%   0.43s   3.82%  runtime.mapassign_faststr
     0.07s   0.62%  49.16%   1.38s  12.27%  runtime.gcDrain
     0.02s   0.18%  60.98%   1.10s   9.78%  example.com/bio.(*SubItemBIO).setSubItemBasicInfo
     0.01s  0.089%  63.11%   1.59s  14.13%  database/sql.(*DB).queryDC
     0.01s  0.089%  63.56%  1.07s  9.51%  database/sql.withLock
         0      0%  67.47%   1.62s  14.40%  database/sql.(*DB).QueryContext
         0      0%  67.47%   1.62s  14.40%  database/sql.(*DB).query
         0      0%  67.47%   0.69s   6.13%  example.com/bio.(*SubItemBIO).getSubItemAlertInfos
         0      0%  67.47%   0.65s   5.78%  example.com/bio.(*SubItemBIO).getSubItemAlertInfos.func1

func (o *SubItemBIO) setSubItemBasicInfo(records ...)
{
  subItems := make([]*SubItem, 0)
  for _, subItem := range records {
      alertInfos, err := o.getSubItemAlertInfos(subItem)
      if err != nil {
          return nil, err
      }
      subItem.AlertInfos = alertInfos
      subItems = append(subItems, modelToSubItem(subItem))
  }
  ...
}
func (o *SubItemBIO) getSubItemAlertInfos(subItem) {
    result := make(map[string]string) 
    getAlertInfos := func(subItemID, subItem.ProductID, subItem.VariantID int64, alertType string) error {
        luAlertInfoQuery := NewQueryBuilder().Build()
        // fetch lu alert info
        luAlertInfos, err := o.LuAlertInfoApi.FindAll(ctx, luAlertInfoQuery)
        luAlertInfoIds := getLuAlertInfoIDs(luAlertInfos)
        entityID := getEntityID(subItem.ProductID, subItem.VariantID, alertType)
        alertInfoQuery := NewQueryBuilder(subItemID, luAlertInfoIds,entityID).Build()
        // fetch alerts
        alerts, err := o.AlertInfoApi.FindAll(ctx, alertInfoQuery)
        luAlertIDToName := getLuAlertIDToName(luAlertInfos)
        for _, alert := range alerts {
            alertName := luAlertIDToName[alert.LuAlertID]
            result[alertName] = alert
        }
    }
   // Prduct alert infos
   if err := getAlertInfos(subItemID, subItem.ProductID, subItem.VariantID, "Product"); err != nil {
        ... 
    }
    // Variant alert infos
    if err := getAlertInfos(subItemID, subItem.ProductID, subItem.VariantID, "Variant"); err != nil {
        ...
    }
}

      flat  flat%   sum%        cum   cum%
      50ms  6.41%  6.41%       50ms  6.41%  internal/runtime/syscall.Syscall6
      30ms  3.85% 10.26%      130ms 16.67%  runtime.scanobject
      20ms  2.56% 30.77%      100ms 12.82%  runtime.mallocgc
      10ms  1.28% 53.85%      300ms 38.46%  example.com/internal/proto/client.(*subItemClient).ListByItemID
      10ms  1.28% 79.49%      140ms 17.95%  runtime.gcDrain
         0     0%   100%      110ms 14.10%  runtime.schedule

// FetchOrderData 加载主订单数据并处理其下的任务结构
func FetchOrderData(ctx context.Context, req RequestInput) error {
    data, _ := OrderService.GetByExternalID(ctx, req)
    return loadTasksConcurrently(ctx, data.ID)
}
// loadTasksConcurrently 并发加载所有任务及其下属条目
func loadTasksConcurrently(ctx context.Context, orderID int64) error {
    tasks, _ := TaskService.ListByOrderID(ctx, orderID)
    for _, task := range tasks {
        go func(t Task) {
            loadItemsConcurrently(ctx, t.ID)
        }(task)
    }
    return nil
}
// loadItemsConcurrently 并发加载条目并处理其子项信息
func loadItemsConcurrently(ctx context.Context, taskID int64) {
    items, _ := ItemService.ListByTaskID(ctx, taskID)
    for _, item := range items {
        go func(it Item) {
            _ = SubItemService.ListByItemID(ctx, it.ID)
        }(item)
    }
}