q.histCounts.Update(atomic.LoadInt64(&q.nowCount))
}

// XferStats has transfer stats for replication
type XferStats struct {
	Curr    float64          `json:"currRate" msg:"cr"`
	Avg     float64          `json:"avgRate" msg:"av"`
	Peak    float64          `json:"peakRate" msg:"p"`
	N       int64            `json:"n" msg:"n"`
	measure *rateMeasurement `json:"-"`
	sma     *SMA             `json:"-"`
}

			}
			for rm, x := range v.XferStats {
				x2, ok := v2.XferStats[replication.MetricName(rm)]
				if !ok {
					x2 = replication.XferStats{}
				}
				x2.AvgRate += x.Avg
				x2.CurrRate += x.Curr
				if x.Peak > x2.PeakRate {
					x2.PeakRate = x.Peak
				}
				v2.XferStats[replication.MetricName(rm)] = x2
			}
			sm.Metrics[dID] = v2
		}
	}

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		Value:          rm.Current,
		VariableLabels: cloneMSS(rm.Labels),
	})

	if requireAvgMax {
		avgName := MetricName(fmt.Sprintf("%s_avg", name))
		avgHelp := fmt.Sprintf("%s (avg)", help)
		metrics = append(metrics, MetricV2{
			Description:    getResourceMetricDescription(subSys, avgName, avgHelp),
			Value:          math.Round(rm.Avg*100) / 100,
			VariableLabels: cloneMSS(rm.Labels),
		})

		{Name: "subquery_having_2", Age: 20},
		{Name: "subquery_having_3", Age: 30},
		{Name: "subquery_having_4", Age: 40},
	}
	DB.Create(&users)

	var results []User
	DB.Select("AVG(age) as avgage").Where("name LIKE ?", "subquery_having%").Group("name").Having("AVG(age) > (?)", DB.
		Select("AVG(age)").Where("name LIKE ?", "subquery_having%").Table("users")).Find(&results)

	if len(results) != 2 {