Merge branch 'main-v2' into lite-ba
This commit is contained in:
TsMask
@@ -280,3 +280,222 @@ func (r KpiReport) UPFTodayFlowLoad(day int) {
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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,
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"topFourHoursBHCC": topFourBHCC,
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"totalHours": len(data),
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}
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}
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// 辅助函数：获取前四个最高值的TrafficData
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func getTopFourTrafficData(data []TrafficData) []TrafficData {
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if len(data) == 0 {
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return []TrafficData{}
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}
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// 最多取前四个值
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maxCount := 4
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if len(data) < maxCount {
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maxCount = len(data)
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}
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return data[:maxCount]
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}
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// 辅助函数：计算TrafficData的平均值
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func calculateTrafficDataAverage(data []TrafficData) float64 {
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if len(data) == 0 {
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return 0
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}
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var sum float64 = 0
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for _, v := range data {
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sum += v.Value
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}
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return sum / float64(len(data))
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}
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