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@@ -0,0 +1,383 @@
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+package models
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+
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+import (
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+ "errors"
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+ "fmt"
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+ "github.com/beego/beego/v2/client/orm"
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+ "github.com/shopspring/decimal"
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+ "hongze/hongze_edb_lib/utils"
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+ "strconv"
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+ "strings"
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+ "time"
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+)
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+
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+// SavePredictCalculateBp 变频
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+func SavePredictCalculateBp(req *EdbInfoCalculateBatchSaveReq, fromEdbInfo *EdbInfo, edbCode, uniqueCode string, sysUserId int, sysUserRealName string) (edbInfo *EdbInfo, latestDateStr string, latestValue float64, err error) {
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+ o := orm.NewOrm()
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+ to, err := o.Begin()
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+ if err != nil {
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+ return
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+ }
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+ defer func() {
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+ if err != nil {
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+ fmt.Println("AddPredictCalculateBp,Err:" + err.Error())
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+ _ = to.Rollback()
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+ } else {
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+ _ = to.Commit()
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+ }
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+ }()
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+ if req.EdbInfoId <= 0 {
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+ edbInfo = new(EdbInfo)
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+ edbInfo.EdbInfoType = 1
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+ edbInfo.Source = utils.DATA_SOURCE_PREDICT_CALCULATE_BP
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+ edbInfo.SourceName = "预测变频"
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+ edbInfo.EdbCode = edbCode
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+ edbInfo.EdbName = req.EdbName
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+ edbInfo.EdbNameSource = req.EdbName
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+ edbInfo.Frequency = req.Frequency
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+ edbInfo.Unit = req.Unit
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+ edbInfo.ClassifyId = req.ClassifyId
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+ edbInfo.SysUserId = sysUserId
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+ edbInfo.SysUserRealName = sysUserRealName
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+ edbInfo.CreateTime = time.Now()
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+ edbInfo.ModifyTime = time.Now()
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+ edbInfo.UniqueCode = uniqueCode
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+ edbInfo.CalculateFormula = req.Formula
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+ edbInfo.EdbType = 2
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+ newEdbInfoId, tmpErr := to.Insert(edbInfo)
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+ if tmpErr != nil {
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+ err = tmpErr
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+ return
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+ }
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+ edbInfo.EdbInfoId = int(newEdbInfoId)
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+ //关联关系
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+ {
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+ calculateMappingItem := new(EdbInfoCalculateMapping)
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+ calculateMappingItem.CreateTime = time.Now()
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+ calculateMappingItem.ModifyTime = time.Now()
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+ calculateMappingItem.Sort = 1
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+ calculateMappingItem.EdbCode = edbCode
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+ calculateMappingItem.EdbInfoId = edbInfo.EdbInfoId
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+ calculateMappingItem.FromEdbInfoId = fromEdbInfo.EdbInfoId
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+ calculateMappingItem.FromEdbCode = fromEdbInfo.EdbCode
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+ calculateMappingItem.FromEdbName = fromEdbInfo.EdbName
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+ calculateMappingItem.FromSource = fromEdbInfo.Source
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+ calculateMappingItem.FromSourceName = fromEdbInfo.SourceName
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+ calculateMappingItem.FromTag = ""
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+ calculateMappingItem.Source = edbInfo.Source
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+ calculateMappingItem.SourceName = edbInfo.SourceName
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+ _, err = to.Insert(calculateMappingItem)
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+ if err != nil {
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+ return
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+ }
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+ }
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+ } else {
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+ edbInfo, err = GetEdbInfoById(req.EdbInfoId)
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+ if err != nil {
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+ return
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+ }
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+ //修改指标信息
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+ edbInfo.EdbName = req.EdbName
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+ edbInfo.EdbNameSource = req.EdbName
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+ edbInfo.Frequency = req.Frequency
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+ edbInfo.Unit = req.Unit
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+ edbInfo.ClassifyId = req.ClassifyId
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+ edbInfo.ModifyTime = time.Now()
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+ _, err = to.Update(edbInfo, "EdbName", "EdbNameSource", "Frequency", "Unit", "ClassifyId", "ModifyTime")
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+ if err != nil {
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+ return
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+ }
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+
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+ //判断计算指标是否被更换
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+ var existCondition string
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+ var existPars []interface{}
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+ existCondition += " AND edb_info_id=? AND from_edb_info_id=? "
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+ existPars = append(existPars, edbInfo.EdbInfoId, req.FromEdbInfoId)
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+
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+ count, e := GetEdbInfoCalculateCountByCondition(existCondition, existPars)
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+ if e != nil {
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+ err = errors.New("判断指标是否改变失败,Err:" + e.Error())
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+ return
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+ }
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+ if count > 0 { // 指标未被替换，无需重新计算
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+ return
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+ }
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+
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+ //删除，计算指标关联的，基础指标的关联关系
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+ sql := ` DELETE FROM edb_info_calculate_mapping WHERE edb_info_id = ? `
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+ _, err = to.Raw(sql, edbInfo.EdbInfoId).Exec()
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+ if err != nil {
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+ err = errors.New("删除计算指标关联关系失败,Err:" + err.Error())
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+ return
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+ }
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+ //清空原有数据
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+ sql = ` DELETE FROM edb_data_predict_calculate_bp WHERE edb_info_id = ? `
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+ _, err = to.Raw(sql, edbInfo.EdbInfoId).Exec()
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+ if err != nil {
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+ return
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+ }
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+ //关联关系
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+ {
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+ calculateMappingItem := &EdbInfoCalculateMapping{
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+ EdbInfoCalculateMappingId: 0,
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+ EdbInfoId: edbInfo.EdbInfoId,
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+ Source: utils.DATA_SOURCE_PREDICT_CALCULATE_BP,
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+ SourceName: "预测变频",
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+ EdbCode: edbInfo.EdbCode,
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+ FromEdbInfoId: fromEdbInfo.EdbInfoId,
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+ FromEdbCode: fromEdbInfo.EdbCode,
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+ FromEdbName: fromEdbInfo.EdbName,
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+ FromSource: fromEdbInfo.Source,
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+ FromSourceName: fromEdbInfo.SourceName,
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+ FromTag: "",
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+ Sort: 1,
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+ CreateTime: time.Now(),
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+ ModifyTime: time.Now(),
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+ }
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+ _, err = to.Insert(calculateMappingItem)
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+ if err != nil {
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+ return
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+ }
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+ }
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+ }
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+
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+ //计算数据
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+ latestDateStr, latestValue, err = refreshAllPredictCalculateBp(to, edbInfo.EdbInfoId, edbInfo.Source, fromEdbInfo, edbInfo.EdbCode, "", "", 0)
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+
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+ return
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+}
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+
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+func RefreshAllPredictCalculateBp(edbInfoId, source int, fromEdbInfo *EdbInfo, edbCode, startDate, endDate string) (latestDateStr string, latestValue float64, err error) {
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+ o := orm.NewOrm()
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+ to, err := o.Begin()
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+ if err != nil {
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+ return
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+ }
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+ defer func() {
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+ if err != nil {
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+ fmt.Println("RefreshAllPredictCalculateBp,Err:" + err.Error())
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+ _ = to.Rollback()
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+ } else {
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+ _ = to.Commit()
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+ }
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+ }()
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+
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+ // 计算数据
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+ latestDateStr, latestValue, err = refreshAllPredictCalculateBp(to, edbInfoId, source, fromEdbInfo, edbCode, startDate, endDate, 1)
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+ return
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+}
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+
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+// refreshAllPredictCalculateBp 刷新变频数据
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+func refreshAllPredictCalculateBp(to orm.TxOrmer, edbInfoId, source int, fromEdbInfo *EdbInfo, edbCode, startDate, endDate string, order int) (latestDateStr string, latestValue float64, err error) {
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+ edbInfoIdStr := strconv.Itoa(edbInfoId)
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+ // 获取关联指标数据
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+ dataList, err := GetPredictEdbDataListAllByStartDate(fromEdbInfo, order, "")
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+ if err != nil {
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+ return
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+ }
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+ latestDateStr = fromEdbInfo.LatestDate
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+
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+ var dateArr []string
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+ dataMap := make(map[string]*EdbInfoSearchData)
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+ fromDataMap := make(map[string]float64)
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+ //来源指指标数据
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+ for _, v := range dataList {
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+ dateArr = append(dateArr, v.DataTime)
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+ dataMap[v.DataTime] = v
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+ fromDataMap[v.DataTime] = v.Value
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+ }
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+ fmt.Println("source:", source)
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+
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+ //获取变频指标所有数据
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+ existDataList, err := GetAllEdbDataListByTo(to, edbInfoId, source)
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+ if err != nil {
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+ return
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+ }
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+ //计算指标的map
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+ existDataMap := make(map[string]*EdbData, 0)
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+
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+ addSql := ` INSERT INTO edb_data_predict_calculate_bp(edb_info_id,edb_code,data_time,value,create_time,modify_time,data_timestamp) values `
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+ var isAdd bool
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+
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+ var lastValue float64 //最后数据的值(float64)
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+ var lastValueStr string //最后数据的值(string)
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+ //待删除的日期
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+ removeDateList := make([]string, 0)
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+ if len(existDataList) > 0 {
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+ //第一个已经入库的日期
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+ firstExistDataTimeStr := existDataList[0].DataTime //计算指标数据第一条的日期字符串
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+ if len(dateArr) > 0 {
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+ firstFromDataTimeStr := dateArr[0] //来源数据第一条的日期字符串
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+ firstExistDataTime, _ := time.Parse(utils.FormatDate, firstExistDataTimeStr) //计算指标数据第一条的日期（time类型）
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+ firstFromDataTime, _ := time.Parse(utils.FormatDate, firstFromDataTimeStr) //来源数据第一条的日期（time类型）
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+ nowDateStr := time.Now().Format(utils.FormatDate) //当天日期字符串
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+ nowDate, _ := time.ParseInLocation(utils.FormatDate, nowDateStr, firstFromDataTime.Location()) //当天日期（time类型）
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+
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+ lastValue = fromDataMap[firstFromDataTimeStr]
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+ lastValueStr = decimal.NewFromFloat(lastValue).String()
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+ //第一步： 判断来源指标的开始时间与计算指标的开始时间是否相等，相等的话，那么就不需要对两个时间之间的数据做处理
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+ if firstExistDataTimeStr != firstFromDataTimeStr {
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+ if firstExistDataTime.Before(firstFromDataTime) { //如果计算指标第一条数据的开始时间 早于 来源指标的第一条开始时间，那么需要对两个时间之间的计算指标数据做 删除处理
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+ for _, v := range existDataList {
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+ if v.DataTime == firstFromDataTimeStr {
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+ if tmpLastValue, ok := fromDataMap[firstFromDataTimeStr]; ok { //来源指标当天的数据
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+ lastValue = tmpLastValue
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+ lastValueStr = decimal.NewFromFloat(lastValue).String()
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+ }
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+ break
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+ }
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+ removeDateList = append(removeDateList, v.DataTime)
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+ }
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+ } else {
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+ for _, v := range dateArr { //如果计算指标第一条数据的开始时间 晚于 来源指标的第一条开始时间，那么需要对两个时间之间的计算指标数据做 新增处理
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+ vDataTime, _ := time.Parse(utils.FormatDate, v) //当前日期（time类型）
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+ if firstExistDataTime.Equal(vDataTime) || firstExistDataTime.Before(vDataTime) {
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+ if tmpLastValue, ok := fromDataMap[v]; ok { //来源指标当天的数据
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+ lastValue = tmpLastValue
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+ lastValueStr = decimal.NewFromFloat(lastValue).String()
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+ }
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+ break
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+ }
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+
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+ currentDate, _ := time.Parse(utils.FormatDate, v)
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+ timestamp := currentDate.UnixNano() / 1e6
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+ timestampStr := fmt.Sprintf("%d", timestamp)
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+ addSql += GetAddSql(edbInfoIdStr, edbCode, v, timestampStr, lastValueStr)
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+ // 实际数据的值
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+ if fromEdbInfo.LatestDate == v {
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+ latestValue = lastValue
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+ }
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+ isAdd = true
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+ }
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+ }
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+ }
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+
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+ //第二步 剩余数据每天修改
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+
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+ day := int(nowDate.Sub(firstExistDataTime).Hours() / float64(24))
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+
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+ //第三步： 已经入库的数据处理
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+ for _, v := range existDataList {
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+ existDataMap[v.DataTime] = v
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+ }
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+
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+ for k := day; k >= 0; k-- {
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+ needDay := nowDate.AddDate(0, 0, -k)
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+ needDayStr := needDay.Format(utils.FormatDate)
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+ tmpExistData, ok := existDataMap[needDayStr]
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+ if ok {
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+ if tmpLastValue, ok := fromDataMap[tmpExistData.DataTime]; ok { //来源指标当天的数据
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+ lastValue = tmpLastValue
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+ //lastValueStr = decimal.NewFromFloat(lastValue).String()
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+ lastValueStr = fmt.Sprintf("%.4f", lastValue)
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+ }
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+ if fromEdbInfo.LatestDate == tmpExistData.DataTime {
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+ latestValue = lastValue
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+ }
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+ //如果对应的值不匹配
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+ if tmpExistData.Value != lastValueStr {
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+ err = ModifyEdbDataById(source, tmpExistData.EdbDataId, lastValueStr)
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+ if err != nil {
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+ return
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+ }
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+ }
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+ } else {
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+ timestamp := needDay.UnixNano() / 1e6
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+ timestampStr := fmt.Sprintf("%d", timestamp)
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+ addSql += GetAddSql(edbInfoIdStr, edbCode, needDayStr, timestampStr, lastValueStr)
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+ if fromEdbInfo.LatestDate == needDayStr {
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+ latestValue = lastValue
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+ }
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+ isAdd = true
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+ }
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+ }
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+ } else {
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+ //如果没有来源指标数据，那么已经入库的计算指标数据需要全部删除
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+ tableName := GetEdbDataTableName(source)
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+ sql := fmt.Sprintf(` DELETE FROM %s WHERE edb_info_id = ?`, tableName)
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+ _, err = to.Raw(sql, edbInfoId).Exec()
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+ if err != nil {
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+ err = fmt.Errorf("删除所有的变频指标数据失败,Err:" + err.Error())
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+ return
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+ }
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+
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+ //for _, v := range existDataList {
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+ // removeDateList = append(removeDateList, v.DataTime)
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+ //}
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+ }
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+ } else {
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+ existMap := make(map[string]string)
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+ dataLen := len(dataList)
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+
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+ for i := 0; i < dataLen; i++ {
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+ //当期
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+ currentItem := dataList[i]
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+ currentDate, _ := time.Parse(utils.FormatDate, currentItem.DataTime)
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+ var day int
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+ var preItem *EdbInfoSearchData
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+ var preDate time.Time
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+ if i == 0 {
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+ day = int(time.Now().Sub(currentDate).Hours() / float64(24))
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+ preDate = time.Now()
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+ } else {
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+ j := i - 1
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+ if j < dataLen {
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+ preItem = dataList[j]
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+ preDate, _ = time.Parse(utils.FormatDate, preItem.DataTime)
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+ day = int(preDate.Sub(currentDate).Hours() / float64(24))
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+ utils.FileLog.Info("preItem.DataTime:" + preItem.DataTime + ";currentItem.DataTime" + currentItem.DataTime)
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+ }
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+ }
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+ for k := 0; k <= day; k++ {
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+ needDay := preDate.AddDate(0, 0, -k)
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+ needDayStr := needDay.Format(utils.FormatDate)
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+ existKey := edbCode + needDayStr
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+ if _, ok := existMap[existKey]; !ok {
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+ timestamp := needDay.UnixNano() / 1e6
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+ timestampStr := fmt.Sprintf("%d", timestamp)
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+ valStr := decimal.NewFromFloat(currentItem.Value).String()
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+ addSql += GetAddSql(edbInfoIdStr, edbCode, needDayStr, timestampStr, valStr)
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+ if fromEdbInfo.LatestDate == needDayStr {
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+ latestValue = currentItem.Value
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+ }
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+ isAdd = true
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+ }
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+ existMap[existKey] = needDayStr
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+ }
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+ existKey := edbCode + currentItem.DataTime
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+ if _, ok := existMap[existKey]; !ok {
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+ currentDate, _ := time.Parse(utils.FormatDate, currentItem.DataTime)
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+ timestamp := currentDate.UnixNano() / 1e6
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+ timestampStr := fmt.Sprintf("%d", timestamp)
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+ valStr := decimal.NewFromFloat(currentItem.Value).String()
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+ addSql += GetAddSql(edbInfoIdStr, edbCode, currentItem.DataTime, timestampStr, valStr)
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+ if fromEdbInfo.LatestDate == currentItem.DataTime {
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+ latestValue = currentItem.Value
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+ }
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+ isAdd = true
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+ }
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+ existMap[existKey] = currentItem.DataTime
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|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ // 删除不需要的指标数据
|
|
|
+ if len(removeDateList) > 0 {
|
|
|
+ removeDateStr := strings.Join(removeDateList, `","`)
|
|
|
+ removeDateStr = `"` + removeDateStr + `"`
|
|
|
+ //如果拼接指标变更了，那么需要删除所有的指标数据
|
|
|
+ tableName := GetEdbDataTableName(source)
|
|
|
+ sql := fmt.Sprintf(` DELETE FROM %s WHERE edb_info_id = ? and data_time in (%s) `, tableName, removeDateStr)
|
|
|
+
|
|
|
+ _, err = to.Raw(sql, edbInfoId).Exec()
|
|
|
+ if err != nil {
|
|
|
+ err = fmt.Errorf("删除不存在的变频指标数据失败,Err:" + err.Error())
|
|
|
+ return
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ if isAdd {
|
|
|
+ addSql = strings.TrimRight(addSql, ",")
|
|
|
+ _, err = to.Raw(addSql).Exec()
|
|
|
+ }
|
|
|
+ return
|
|
|
+}
|
xiexiaoyuan