import org.opensearch.search.aggregations.bucket.histogram.Histogram;
import org.opensearch.search.aggregations.bucket.terms.Terms;
import org.opensearch.search.aggregations.metrics.Avg;
import org.opensearch.search.aggregations.metrics.Cardinality;

import jakarta.annotation.Resource;

public class SearchLogService {

    private static final String YYYY_MM_DD_HH_MM = "yyyy-MM-dd HH:mm";

		dur = 0
	}
	a.Total += int64(dur)
	a.N++
}

// Merge b into a.
func (a *AccElem) merge(b AccElem) {
	a.N += b.N
	a.Total += b.Total
	a.Size += b.Size
}

// Avg returns average time spent.
func (a AccElem) avg() time.Duration {
	if a.N >= 1 && a.Total > 0 {
		return time.Duration(a.Total / a.N)
	}
	return 0
}

// asTimedAction returns the element as a madmin.TimedAction.

// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package sql

import (
	"errors"
	"fmt"
)

// Aggregation Function name constants
const (
	aggFnAvg   FuncName = "AVG"
	aggFnCount FuncName = "COUNT"
	aggFnMax   FuncName = "MAX"
	aggFnMin   FuncName = "MIN"
	aggFnSum   FuncName = "SUM"
)

var (
	errNonNumericArg = func(fnStr FuncName) error {

			metric.TotalDowntime = epHealth.offlineDuration
			metric.LastOnline = epHealth.lastOnline
			metric.Online = epHealth.Online
			metric.Latency = madmin.LatencyStat{
				Curr: epHealth.latency.curr,
				Avg:  epHealth.latency.avg,
				Max:  epHealth.latency.peak,
			}
		}
		m[dID] = metric
	}
	return m
}

func (srs *SRStatus) updateXferRate(sz int64, duration time.Duration) {
	if sz > minLargeObjSize {

		// Return empty metrics when not configured.
		return Metrics{}
	}
	o.serviceMetrics.Lock()
	defer o.serviceMetrics.Unlock()
	l := &o.serviceMetrics.lastFullMinute
	var avg float64
	if l.successRequestCount > 0 {
		avg = l.rttMsSum / float64(l.successRequestCount)
	}
	now := time.Now().UTC()
	return Metrics{
		LastReachableSecs:   now.Sub(o.serviceMetrics.LastCheckSuccess).Seconds(),

at\":\"HH:mm\",\"bounds\":{\"min\":\"2019-07-28T11:33:01.690Z\",\"max\":\"2019-07-30T11:33:01.690Z\"}},\"aggType\":\"date_histogram\"},\"y\":[{\"accessor\":1,\"format\":{\"id\":\"number\"},\"params\":{},\"aggType\":\"avg\"}]}},\"aggs\":[{\"id\":\"1\",\"enabled\":true,\"type\":\"avg\",\"schema\":\"metric\",\"params\":{\"field\":\"responseTime\"}},{\"id\":\"2\",\"enabled\":true,\"type\":\"date_histogram\",\"schema\":\"segment\",\"params\":{\"field\":\"requestedAt\",\"timeRange\":{\"from\":\"now-2d...

          "interval": "1m",
          "intervalFactor": 2,
          "legendFormat": "{{server}}",
          "refId": "A"
        }
      ],
      "title": "Avg. Active Workers",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "fieldConfig": {
        "defaults": {

	// Used during evaluation for aggregation funcs
	aggregate *aggVal
}

// SimpleArgFunc represents functions with simple expression
// arguments.
type SimpleArgFunc struct {
	FunctionName string `parser:" @(\"AVG\" | \"MAX\" | \"MIN\" | \"SUM\" |  \"COALESCE\" | \"NULLIF\" | \"TO_STRING\" | \"TO_TIMESTAMP\" | \"UTCNOW\" | \"CHAR_LENGTH\" | \"CHARACTER_LENGTH\" | \"LOWER\" | \"UPPER\") "`

// row. They have an output for each input row.
//
// Some types of a queries are not valid. For example, an aggregation
// function combined with a row function is meaningless ("AVG(s.Age) +
// s.Salary"). Analysis determines if such a scenario exists so an
// error can be returned.

var (
	// Fatal error for query processing.
	errNestedAggregation      = errors.New("Cannot nest aggregations")

	if r == nil {
		return ActiveWorkerStat{}
	}
	r.wlock.RLock()
	defer r.wlock.RUnlock()
	w := r.workers.get()
	return ActiveWorkerStat{
		Curr: w.Curr,
		Max:  w.Max,
		Avg:  w.Avg,
	}
}

func (r *ReplicationStats) collectWorkerMetrics(ctx context.Context) {
	if r == nil {
		return
	}
	for {
		select {
		case <-ctx.Done():
			return
		case <-r.wTimer.C: