Initial commit: Pipeline Database
This commit is contained in:
9
examples/data-analytics/go.mod
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9
examples/data-analytics/go.mod
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module data-analytics
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go 1.24.0
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replace code.tczkiot.com/wlw/pipelinedb => ../../
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require code.tczkiot.com/wlw/pipelinedb v0.0.0-00010101000000-000000000000
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require github.com/google/btree v1.1.3 // indirect
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2
examples/data-analytics/go.sum
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2
examples/data-analytics/go.sum
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github.com/google/btree v1.1.3 h1:CVpQJjYgC4VbzxeGVHfvZrv1ctoYCAI8vbl07Fcxlyg=
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github.com/google/btree v1.1.3/go.mod h1:qOPhT0dTNdNzV6Z/lhRX0YXUafgPLFUh+gZMl761Gm4=
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304
examples/data-analytics/main.go
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304
examples/data-analytics/main.go
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// 演示数据分析和报告功能
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package main
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import (
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"encoding/json"
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"fmt"
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"log"
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"math/rand"
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"os"
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"sort"
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"time"
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"code.tczkiot.com/wlw/pipelinedb"
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"code.tczkiot.com/wlw/pipelinedb/examples/common"
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)
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// UserEvent 用户事件结构
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type UserEvent struct {
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UserID string `json:"user_id"`
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Action string `json:"action"`
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Page string `json:"page"`
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Timestamp time.Time `json:"timestamp"`
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Value float64 `json:"value,omitempty"`
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}
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// AnalyticsReport 分析报告
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type AnalyticsReport struct {
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TotalEvents int `json:"total_events"`
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UniqueUsers int `json:"unique_users"`
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TopActions []ActionCount `json:"top_actions"`
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TopPages []PageCount `json:"top_pages"`
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UserActivity map[string]int `json:"user_activity"`
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HourlyActivity map[int]int `json:"hourly_activity"`
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TotalValue float64 `json:"total_value"`
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}
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type ActionCount struct {
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Action string `json:"action"`
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Count int `json:"count"`
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}
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type PageCount struct {
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Page string `json:"page"`
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Count int `json:"count"`
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}
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func main() {
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// 创建临时数据库文件
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dbFile := "analytics_example.db"
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defer os.Remove(dbFile)
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// 确保文件可以创建
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if _, err := os.Create(dbFile); err != nil {
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log.Fatalf("创建数据库文件失败: %v", err)
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}
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fmt.Println("🚀 数据分析示例")
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fmt.Println("================")
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// 配置数据库
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fmt.Println("\n📂 步骤1: 配置数据库")
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config := &pipelinedb.Config{
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CacheSize: 100,
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}
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// 创建处理器
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handler := common.NewExampleHandler("数据分析")
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pdb, err := pipelinedb.Open(pipelinedb.Options{
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Filename: dbFile,
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Config: config,
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Handler: handler,
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})
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if err != nil {
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log.Fatalf("打开数据库失败: %v", err)
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}
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defer pdb.Stop()
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fmt.Println("✅ 数据库已配置")
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// 生成模拟用户行为数据
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fmt.Println("\n📊 步骤2: 生成模拟用户行为数据")
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users := []string{"user001", "user002", "user003", "user004", "user005"}
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actions := []string{"页面访问", "按钮点击", "表单提交", "文件下载", "搜索"}
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pages := []string{"/home", "/products", "/about", "/contact", "/login", "/checkout"}
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// 生成1000个随机事件
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events := make([]UserEvent, 1000)
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baseTime := time.Now().Add(-24 * time.Hour) // 从24小时前开始
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for i := 0; i < 1000; i++ {
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event := UserEvent{
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UserID: users[rand.Intn(len(users))],
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Action: actions[rand.Intn(len(actions))],
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Page: pages[rand.Intn(len(pages))],
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Timestamp: baseTime.Add(time.Duration(i) * time.Minute),
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}
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// 为某些动作添加价值
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if event.Action == "表单提交" || event.Action == "文件下载" {
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event.Value = rand.Float64() * 100
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}
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events[i] = event
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}
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fmt.Printf("✅ 生成了 %d 个用户事件\n", len(events))
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// 将事件存储到数据库
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fmt.Println("\n💾 步骤3: 存储事件数据")
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for i, event := range events {
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// 序列化事件数据
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eventData, err := json.Marshal(event)
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if err != nil {
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log.Fatalf("序列化事件失败: %v", err)
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}
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// 创建元数据
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metadata := fmt.Sprintf(`{"user_id": "%s", "action": "%s", "page": "%s"}`,
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event.UserID, event.Action, event.Page)
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// 根据动作类型分组
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group := "用户行为"
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if event.Action == "搜索" {
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group = "搜索行为"
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} else if event.Value > 0 {
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group = "有价值行为"
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}
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recordID, err := pdb.AcceptData(group, eventData, metadata)
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if err != nil {
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log.Fatalf("存储事件失败: %v", err)
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}
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if (i+1)%200 == 0 {
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fmt.Printf(" 📝 已存储 %d/%d 个事件,最新ID: %d\n", i+1, len(events), recordID)
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}
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}
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// 数据分析
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fmt.Println("\n🔍 步骤4: 执行数据分析")
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report := &AnalyticsReport{
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UserActivity: make(map[string]int),
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HourlyActivity: make(map[int]int),
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}
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// 获取所有组的数据
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groups := []string{"用户行为", "搜索行为", "有价值行为"}
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allEvents := []UserEvent{}
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for _, group := range groups {
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fmt.Printf("📋 分析组: %s\n", group)
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pageReq := &pipelinedb.PageRequest{
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Page: 1,
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PageSize: 1000, // 获取所有数据
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}
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response, err := pdb.GetRecordsByGroup(group, pageReq)
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if err != nil {
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fmt.Printf(" ❌ 查询组失败: %v\n", err)
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continue
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}
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fmt.Printf(" 📊 找到 %d 条记录\n", len(response.Records))
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// 解析事件数据
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for _, record := range response.Records {
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var event UserEvent
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if err := json.Unmarshal(record.Data, &event); err != nil {
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continue
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}
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allEvents = append(allEvents, event)
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}
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}
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// 分析数据
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fmt.Println("\n📈 步骤5: 生成分析报告")
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report.TotalEvents = len(allEvents)
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// 统计唯一用户
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uniqueUsers := make(map[string]bool)
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actionCounts := make(map[string]int)
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pageCounts := make(map[string]int)
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for _, event := range allEvents {
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// 唯一用户
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uniqueUsers[event.UserID] = true
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// 用户活跃度
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report.UserActivity[event.UserID]++
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// 动作统计
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actionCounts[event.Action]++
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// 页面统计
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pageCounts[event.Page]++
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// 小时活跃度
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hour := event.Timestamp.Hour()
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report.HourlyActivity[hour]++
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// 总价值
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report.TotalValue += event.Value
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}
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report.UniqueUsers = len(uniqueUsers)
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// 排序Top动作
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for action, count := range actionCounts {
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report.TopActions = append(report.TopActions, ActionCount{
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Action: action,
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Count: count,
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})
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}
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sort.Slice(report.TopActions, func(i, j int) bool {
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return report.TopActions[i].Count > report.TopActions[j].Count
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})
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// 排序Top页面
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for page, count := range pageCounts {
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report.TopPages = append(report.TopPages, PageCount{
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Page: page,
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Count: count,
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})
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}
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sort.Slice(report.TopPages, func(i, j int) bool {
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return report.TopPages[i].Count > report.TopPages[j].Count
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})
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// 显示报告
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fmt.Println("\n📋 数据分析报告")
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fmt.Println("================")
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fmt.Printf("📊 总体统计:\n")
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fmt.Printf(" 总事件数: %d\n", report.TotalEvents)
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fmt.Printf(" 唯一用户数: %d\n", report.UniqueUsers)
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fmt.Printf(" 总价值: %.2f\n", report.TotalValue)
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fmt.Printf(" 平均每用户事件: %.1f\n", float64(report.TotalEvents)/float64(report.UniqueUsers))
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fmt.Printf("\n🔥 热门动作 (Top 5):\n")
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for i, action := range report.TopActions {
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if i >= 5 {
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break
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}
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percentage := float64(action.Count) / float64(report.TotalEvents) * 100
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fmt.Printf(" %d. %s: %d 次 (%.1f%%)\n",
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i+1, action.Action, action.Count, percentage)
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}
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fmt.Printf("\n📄 热门页面 (Top 5):\n")
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for i, page := range report.TopPages {
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if i >= 5 {
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break
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}
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percentage := float64(page.Count) / float64(report.TotalEvents) * 100
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fmt.Printf(" %d. %s: %d 次 (%.1f%%)\n",
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i+1, page.Page, page.Count, percentage)
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}
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fmt.Printf("\n👥 用户活跃度:\n")
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for userID, count := range report.UserActivity {
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fmt.Printf(" %s: %d 次事件\n", userID, count)
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}
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// 数据库统计
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fmt.Println("\n💾 数据库统计")
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stats, err := pdb.GetStats()
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if err != nil {
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log.Fatalf("获取数据库统计失败: %v", err)
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}
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fmt.Printf("📈 存储统计:\n")
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fmt.Printf(" 数据库总记录: %d\n", stats.TotalRecords)
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fmt.Printf(" 总组数: %d\n", len(stats.GroupStats))
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for group, groupStats := range stats.GroupStats {
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fmt.Printf(" [%s]: 热:%d 温:%d 冷:%d\n",
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group, groupStats.HotRecords, groupStats.WarmRecords, groupStats.ColdRecords)
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}
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// 导出报告
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fmt.Println("\n📤 步骤6: 导出分析报告")
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reportJSON, err := json.MarshalIndent(report, "", " ")
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if err != nil {
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log.Fatalf("序列化报告失败: %v", err)
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}
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reportFile := "analytics_report.json"
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err = os.WriteFile(reportFile, reportJSON, 0644)
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if err != nil {
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log.Fatalf("写入报告文件失败: %v", err)
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}
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fmt.Printf("✅ 分析报告已导出到: %s\n", reportFile)
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defer os.Remove(reportFile) // 清理示例文件
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fmt.Println("\n🎉 数据分析示例完成!")
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fmt.Println("💡 提示: 这个示例展示了如何使用Pipeline Database进行复杂的数据分析")
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}
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