502 lines
14 KiB
Go
502 lines
14 KiB
Go
package service
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import (
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"encoding/json"
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"fmt"
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"sort"
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"time"
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"be.ems/src/framework/constants"
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"be.ems/src/framework/database/redis"
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"be.ems/src/framework/utils/parse"
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neModel "be.ems/src/modules/ne/model"
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"be.ems/src/modules/ne_data/model"
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"be.ems/src/modules/ne_data/repository"
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)
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// 实例化数据层 KpiReport 结构体
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var NewKpiReport = &KpiReport{
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kpiReportRepository: repository.NewKpiReport,
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}
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// KpiReport 指标统计 服务层处理
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type KpiReport struct {
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kpiReportRepository *repository.KpiReport // 指标数据信息
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}
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// FindData 通过网元指标数据信息
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func (s KpiReport) FindData(query model.KPIQuery) []map[string]any {
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// 原始数据
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rows := s.kpiReportRepository.SelectKPI(query)
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if len(rows) <= 0 {
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return []map[string]any{}
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}
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kpiIdsHas := false
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kpiIds := []string{}
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// 处理数据
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arr := []map[string]any{}
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for _, row := range rows {
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// 解析 JSON 字符串为 map
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var kpiValues []map[string]any
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err := json.Unmarshal([]byte(row.KpiValues), &kpiValues)
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if err != nil {
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continue
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}
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item := map[string]any{
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"neType": row.NeType,
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"neName": row.NeName,
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"rmUID": row.RmUid,
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"startIndex": row.Index,
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"timeGroup": row.CreatedAt,
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}
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// 遍历 kpiValues 数组
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for _, v := range kpiValues {
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kpiId := "-"
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if k, ok := v["kpiId"]; ok {
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kpiId = fmt.Sprint(k)
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}
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item[kpiId] = v["value"]
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}
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arr = append(arr, item)
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// 添加指标ID
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if !kpiIdsHas {
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for _, v := range kpiValues {
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kpiId := "-"
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if k, ok := v["kpiId"]; ok {
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kpiId = fmt.Sprint(k)
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}
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kpiIds = append(kpiIds, kpiId)
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}
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kpiIdsHas = true
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}
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}
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// 时间密度分钟 数值单位秒 5分钟的传入300秒
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timeInterval := query.Interval
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// 创建一个map来存储按时间段合并后的数据
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timeGroup := make(map[int64][]map[string]any)
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// 遍历每个数据项
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for _, v := range arr {
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itemTime := parse.Number(v["timeGroup"])
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// 计算时间戳的x分钟时间段（使用秒并除以x分钟）
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timeMinute := itemTime / 1000 / timeInterval * timeInterval
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// 合并到对应的时间段
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timeGroup[timeMinute] = append(timeGroup[timeMinute], v)
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}
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// 时间组合输出
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data := []map[string]any{}
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for _, records := range timeGroup {
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if len(records) <= 0 {
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continue
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}
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// 转换为具体时间显示（根据需要可以格式化显示）
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// timeStr := time.Unix(k, 0).Format("2006-01-02 15:04:05")
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// fmt.Printf("Time Group: %s records: %d\n", timeStr, len(records))
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startItem := records[len(records)-1] // 取最后一条数据也是最开始startIndex
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if len(records) >= 2 { // 最后一条数据不参与计算
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for _, record := range records[:len(records)-1] {
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// fmt.Printf(" - startIndex: %v, Value: %v\n", record["startIndex"], record["timeGroup"])
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// 遍历kpiIds数组对lastRecord赋值
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for _, kpiId := range kpiIds {
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if v, ok := record[kpiId]; ok {
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// 特殊字段，只取一次收到的非0值
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if kpiId == "AMF.01" || kpiId == "UDM.01" || kpiId == "UDM.02" || kpiId == "UDM.03" || kpiId == "SMF.01" {
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// startItem[kpiId] = parse.Number(v)
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continue // startIndex的值不累加不取最后
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} else {
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value := parse.Number(startItem[kpiId])
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startItem[kpiId] = value + parse.Number(v)
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}
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}
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}
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}
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}
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data = append(data, startItem)
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}
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// 按时间排序
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sort.SliceStable(data, func(i, j int) bool {
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vi := parse.Number(data[i]["timeGroup"])
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vj := parse.Number(data[j]["timeGroup"])
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if query.SortOrder == "asc" {
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return vi < vj // asc
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}
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return vi > vj // desc
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})
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return data
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}
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// Insert 新增信息
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func (s KpiReport) Insert(param model.KpiReport) int64 {
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return s.kpiReportRepository.Insert(param)
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}
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// FindTitle 网元对应的指标名称
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func (r KpiReport) FindTitle(neType string) []model.KpiTitle {
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return r.kpiReportRepository.SelectKPITitle(neType)
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}
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// FindByPage 根据条件分页查询
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func (r KpiReport) TitleFindByPage(query map[string]string) ([]model.KpiTitle, int64) {
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return r.kpiReportRepository.TitleSelectByPage(query)
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}
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// TitleFind 查询信息
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func (r KpiReport) TitleFind(param model.KpiTitle) []model.KpiTitle {
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return r.kpiReportRepository.TitleSelect(param)
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}
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// TitleUpdate 更新信息
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func (r KpiReport) TitleUpdate(param model.KpiTitle) int64 {
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return r.kpiReportRepository.TitleUpdate(param)
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}
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// TitleDeleteByIds 批量删除信息
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func (r KpiReport) TitleDeleteByIds(ids []int64) (int64, error) {
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rows := r.kpiReportRepository.TitleDeleteByIds(ids)
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if rows > 0 {
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return rows, nil
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}
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// 删除信息失败！
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return 0, fmt.Errorf("delete fail")
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}
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// TitleInsert 新增信息
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func (r KpiReport) TitleInsert(param model.KpiTitle) int64 {
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return r.kpiReportRepository.TitleInsert(param)
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}
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// UPFTodayFlowFind 查询UPF总流量 N3上行 N6下行
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// day 统计天数
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// down * 8 / 1000 / 1000 单位M
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func (r KpiReport) UPFTodayFlowFind(rmUID string, day int) (int64, int64) {
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// 获取当前日期
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now := time.Now()
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var upTotal, downTotal int64
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// 查询最近day天的数据
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for i := 0; i <= day; i++ {
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dateKey := now.AddDate(0, 0, -i).Format("2006-01-02")
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key := fmt.Sprintf("%s:UPF_FLOW:%s:%s", constants.CACHE_NE_DATA, rmUID, dateKey)
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// 读取缓存数据
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up, err := redis.GetHash("", key, "up")
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if err != nil || up == "" {
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up = "0"
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}
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down, err := redis.GetHash("", key, "down")
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if err != nil || down == "" {
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down = "0"
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}
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upTotal += parse.Number(up)
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downTotal += parse.Number(down)
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}
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return upTotal, downTotal
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}
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// UPFTodayFlow UPF流量今日统计
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func (r KpiReport) UPFTodayFlowUpdate(rmUID string, upValue, downValue int64) error {
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// 按日期存储统计数据
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dateKey := time.Now().Format("2006-01-02")
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key := fmt.Sprintf("%s:UPF_FLOW:%s:%s", constants.CACHE_NE_DATA, rmUID, dateKey)
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// 使用HIncrBy实时累加统计值
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if err := redis.IncrBy("", key, "up", upValue); err != nil {
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return err
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}
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if err := redis.IncrBy("", key, "down", downValue); err != nil {
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return err
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}
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return nil
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}
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// UPFTodayFlowLoad UPF上下行数据到redis
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// day 统计天数
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func (r KpiReport) UPFTodayFlowLoad(day int) {
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cacheKeys, _ := redis.GetKeys("", constants.CACHE_NE_INFO+":UPF:*")
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if len(cacheKeys) == 0 {
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return
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}
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now := time.Now()
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for _, key := range cacheKeys {
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var v neModel.NeInfo
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jsonStr, _ := redis.Get("", key)
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if len(jsonStr) > 7 {
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json.Unmarshal([]byte(jsonStr), &v)
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}
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if v.NeType == "UPF" && v.RmUID != "" {
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// 查询最近day天的数据
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for i := 0; i <= day; i++ {
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dateKey := now.AddDate(0, 0, -i).Format("2006-01-02")
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key := fmt.Sprintf("%s:UPF_FLOW:%s:%s", constants.CACHE_NE_DATA, v.RmUID, dateKey)
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// 根据传入天数计算时间范围
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beginTime := now.AddDate(0, 0, -i).Truncate(24 * time.Hour).UnixMilli()
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endTime := beginTime + 24*60*60*1000 - 1
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// 查询历史数据
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rows := r.kpiReportRepository.SelectUPF(v.RmUID, beginTime, endTime)
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var upTotal, downTotal int64
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// 处理历史数据
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for _, row := range rows {
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var kpiValues []map[string]any
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if err := json.Unmarshal([]byte(row.KpiValues), &kpiValues); err != nil {
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continue
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}
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for _, v := range kpiValues {
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if k, ok := v["kpiId"]; ok {
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if k == "UPF.03" {
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upTotal += parse.Number(v["value"])
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}
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if k == "UPF.06" {
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downTotal += parse.Number(v["value"])
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}
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}
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}
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}
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err := redis.SetHash("", key, map[string]any{
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"up": upTotal,
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"down": downTotal,
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})
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if err != nil {
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continue
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}
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// 设置key的过期时间为30天，自动清理旧数据
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daySub := (30 - i) * 24
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err = redis.Expire("", key, time.Duration(daySub)*time.Hour)
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if err != nil {
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continue
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}
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}
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}
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}
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}
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// IMSBusyHour IMS忙时流量统计
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// SCSCF.06呼叫尝试次数 SCSCF.09呼叫成功次数
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func (r KpiReport) IMSBusyHour(rmUID string, timestamp int64) []map[string]any {
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t := time.UnixMilli(timestamp)
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beginTime := t
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endTime := t
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// 检查时分秒是否都为零
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if t.Hour() == 0 && t.Minute() == 0 && t.Second() == 0 {
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// 获取当天起始时间（00:00:00）
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beginTime = t.Truncate(time.Hour)
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// 计算当天结束时间（23:59:59）
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endTime = beginTime.Add(23*time.Hour + 59*time.Minute + 59*time.Second)
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} else {
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// 起始时间：当前小时的 00 分 00 秒
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beginTime = t.Truncate(time.Hour)
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// 结束时间：当前小时的 59 分 59 秒 999 毫秒
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endTime = beginTime.Add(time.Hour - time.Millisecond)
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}
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// 转换为毫秒级时间戳
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rows := r.kpiReportRepository.SelectIMS(rmUID, beginTime.UnixMilli(), endTime.UnixMilli())
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// 创建一个map来存储按时间段合并后的数据
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timeGroup := make(map[int64]map[string]int64)
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// 遍历每个数据项
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for _, row := range rows {
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// 将毫秒时间戳转换为小时级时间戳（保留到小时的起始毫秒）
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timeHour := row.CreatedAt / 3600000 * 3600000 // 1小时 = 3600000毫秒
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// 解析 JSON 字符串为 map
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var kpiValues []map[string]any
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err := json.Unmarshal([]byte(row.KpiValues), &kpiValues)
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if err != nil {
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continue
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}
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var callAttempts, callCompletions int64
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for _, v := range kpiValues {
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if k, ok := v["kpiId"]; ok {
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if k == "SCSCF.06" {
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callAttempts = parse.Number(v["value"])
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}
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if k == "SCSCF.09" {
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callCompletions = parse.Number(v["value"])
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}
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}
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}
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// 合并到对应的小时段
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if _, exists := timeGroup[timeHour]; !exists {
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timeGroup[timeHour] = map[string]int64{
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"callAttempts": 0,
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"callCompletions": 0,
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}
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}
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timeGroup[timeHour]["callAttempts"] += callAttempts
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timeGroup[timeHour]["callCompletions"] += callCompletions
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}
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// 时间组合输出
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data := make([]map[string]any, 0, len(timeGroup))
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for hour, sums := range timeGroup {
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data = append(data, map[string]any{
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"timeGroup": fmt.Sprintf("%d", hour),
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"callAttempts": sums["callAttempts"],
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"callCompletions": sums["callCompletions"],
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})
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}
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return data
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}
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// 定义结构体用于存储话务量值和对应的时间
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type TrafficData struct {
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Time int64 `json:"time"` // 时间戳（毫秒）
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Value float64 `json:"value"` // 话务量值
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}
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// IMSBusyWeek IMS忙时流量统计 周
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func (r KpiReport) IMSBusyWeek(rmUID string, weekStart, weekEnd int64) map[string]any {
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weekStartTime := time.UnixMilli(weekStart)
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weekEndTime := time.UnixMilli(weekEnd)
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// 1. 获取一周内每小时的呼叫数据
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// 转换为毫秒级时间戳
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rows := r.kpiReportRepository.SelectIMS(rmUID, weekStartTime.UnixMilli(), weekEndTime.UnixMilli())
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// 创建一个map来存储按时间段合并后的数据
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timeGroup := make(map[int64]map[string]int64)
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// 遍历每个数据项
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for _, row := range rows {
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// 将毫秒时间戳转换为小时级时间戳（保留到小时的起始毫秒）
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timeHour := row.CreatedAt / 3600000 * 3600000 // 1小时 = 3600000毫秒
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// 解析 JSON 字符串为 map
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var kpiValues []map[string]any
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err := json.Unmarshal([]byte(row.KpiValues), &kpiValues)
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if err != nil {
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continue
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}
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var callAttempts, callCompletions int64
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for _, v := range kpiValues {
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if k, ok := v["kpiId"]; ok {
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if k == "SCSCF.06" {
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callAttempts = parse.Number(v["value"])
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}
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if k == "SCSCF.09" {
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callCompletions = parse.Number(v["value"])
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}
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}
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}
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// 合并到对应的小时段
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if _, exists := timeGroup[timeHour]; !exists {
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timeGroup[timeHour] = map[string]int64{
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"callAttempts": 0,
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"callCompletions": 0,
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}
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}
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timeGroup[timeHour]["callAttempts"] += callAttempts
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timeGroup[timeHour]["callCompletions"] += callCompletions
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}
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// 时间组合输出
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data := make([]map[string]any, 0, len(timeGroup))
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for hour, sums := range timeGroup {
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data = append(data, map[string]any{
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"timeGroup": fmt.Sprintf("%d", hour),
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"callAttempts": sums["callAttempts"],
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"callCompletions": sums["callCompletions"],
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})
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}
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if len(data) == 0 {
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return map[string]any{
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"busyHourAverageBHCA": 0,
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"busyHourAverageBHCC": 0,
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"topFourHoursBHCA": []float64{},
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"topFourHoursBHCC": []float64{},
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"totalHours": 0,
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}
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}
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// 2. 分离BHCA和BHCC数据，并按降序排序
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var bhcaData []TrafficData
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var bhccData []TrafficData
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for _, row := range data {
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// 获取时间戳
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timeValue := int64(0)
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if t, ok := row["timeGroup"]; ok {
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timeValue = parse.Number(t)
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}
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// 处理BHCA数据
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if value, ok := row["callAttempts"]; ok {
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bhcaVal := parse.Number(value)
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bhcaData = append(bhcaData, TrafficData{
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Time: timeValue,
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Value: float64(bhcaVal),
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})
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}
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// 处理BHCC数据
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if value, ok := row["callCompletions"]; ok {
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bhccVal := parse.Number(value)
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bhccData = append(bhccData, TrafficData{
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Time: timeValue,
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Value: float64(bhccVal),
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})
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}
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}
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// 按降序排序（值大的在前）
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sort.Slice(bhcaData, func(i, j int) bool { return bhcaData[i].Value > bhcaData[j].Value })
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sort.Slice(bhccData, func(i, j int) bool { return bhccData[i].Value > bhccData[j].Value })
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// 3. 取前四个最高值并计算平均值
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topFourBHCA := getTopFourTrafficData(bhcaData)
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topFourBHCC := getTopFourTrafficData(bhccData)
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avgBHCA := calculateTrafficDataAverage(topFourBHCA)
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avgBHCC := calculateTrafficDataAverage(topFourBHCC)
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// 4. 返回结果
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return map[string]any{
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"busyHourAverageBHCA": avgBHCA,
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"busyHourAverageBHCC": avgBHCC,
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||
"topFourHoursBHCA": topFourBHCA,
|
||
"topFourHoursBHCC": topFourBHCC,
|
||
"totalHours": len(data),
|
||
}
|
||
}
|
||
|
||
// 辅助函数：获取前四个最高值的TrafficData
|
||
func getTopFourTrafficData(data []TrafficData) []TrafficData {
|
||
if len(data) == 0 {
|
||
return []TrafficData{}
|
||
}
|
||
|
||
// 最多取前四个值
|
||
maxCount := 4
|
||
if len(data) < maxCount {
|
||
maxCount = len(data)
|
||
}
|
||
|
||
return data[:maxCount]
|
||
}
|
||
|
||
// 辅助函数：计算TrafficData的平均值
|
||
func calculateTrafficDataAverage(data []TrafficData) float64 {
|
||
if len(data) == 0 {
|
||
return 0
|
||
}
|
||
|
||
var sum float64 = 0
|
||
for _, v := range data {
|
||
sum += v.Value
|
||
}
|
||
|
||
return sum / float64(len(data))
|
||
}
|