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d9fd807375
elasticsearch: backend: sort label-values
756 lines
19 KiB
Go
756 lines
19 KiB
Go
package elasticsearch
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import (
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"errors"
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"regexp"
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"sort"
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"strconv"
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"strings"
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"time"
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"github.com/grafana/grafana-plugin-sdk-go/backend"
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"github.com/grafana/grafana-plugin-sdk-go/data"
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"github.com/grafana/grafana/pkg/components/simplejson"
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es "github.com/grafana/grafana/pkg/tsdb/elasticsearch/client"
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)
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const (
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// Metric types
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countType = "count"
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percentilesType = "percentiles"
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extendedStatsType = "extended_stats"
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topMetricsType = "top_metrics"
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// Bucket types
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dateHistType = "date_histogram"
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nestedType = "nested"
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histogramType = "histogram"
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filtersType = "filters"
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termsType = "terms"
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geohashGridType = "geohash_grid"
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// Document types
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rawDocumentType = "raw_document"
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rawDataType = "raw_data"
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// Logs type
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logsType = "logs"
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)
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func parseResponse(responses []*es.SearchResponse, targets []*Query) (*backend.QueryDataResponse, error) {
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result := backend.QueryDataResponse{
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Responses: backend.Responses{},
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}
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if responses == nil {
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return &result, nil
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}
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for i, res := range responses {
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target := targets[i]
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if res.Error != nil {
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errResult := getErrorFromElasticResponse(res)
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result.Responses[target.RefID] = backend.DataResponse{
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Error: errors.New(errResult),
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}
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continue
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}
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queryRes := backend.DataResponse{}
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props := make(map[string]string)
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err := processBuckets(res.Aggregations, target, &queryRes, props, 0)
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if err != nil {
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return &backend.QueryDataResponse{}, err
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}
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nameFields(queryRes, target)
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trimDatapoints(queryRes, target)
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result.Responses[target.RefID] = queryRes
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}
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return &result, nil
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}
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func processBuckets(aggs map[string]interface{}, target *Query,
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queryResult *backend.DataResponse, props map[string]string, depth int) error {
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var err error
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maxDepth := len(target.BucketAggs) - 1
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aggIDs := make([]string, 0)
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for k := range aggs {
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aggIDs = append(aggIDs, k)
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}
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sort.Strings(aggIDs)
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for _, aggID := range aggIDs {
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v := aggs[aggID]
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aggDef, _ := findAgg(target, aggID)
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esAgg := simplejson.NewFromAny(v)
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if aggDef == nil {
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continue
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}
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if aggDef.Type == nestedType {
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err = processBuckets(esAgg.MustMap(), target, queryResult, props, depth+1)
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if err != nil {
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return err
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}
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continue
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}
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if depth == maxDepth {
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if aggDef.Type == dateHistType {
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err = processMetrics(esAgg, target, queryResult, props)
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} else {
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err = processAggregationDocs(esAgg, aggDef, target, queryResult, props)
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}
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if err != nil {
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return err
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}
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} else {
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for _, b := range esAgg.Get("buckets").MustArray() {
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bucket := simplejson.NewFromAny(b)
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newProps := make(map[string]string)
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for k, v := range props {
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newProps[k] = v
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}
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if key, err := bucket.Get("key").String(); err == nil {
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newProps[aggDef.Field] = key
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} else if key, err := bucket.Get("key").Int64(); err == nil {
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newProps[aggDef.Field] = strconv.FormatInt(key, 10)
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}
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if key, err := bucket.Get("key_as_string").String(); err == nil {
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newProps[aggDef.Field] = key
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}
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err = processBuckets(bucket.MustMap(), target, queryResult, newProps, depth+1)
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if err != nil {
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return err
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}
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}
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buckets := esAgg.Get("buckets").MustMap()
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bucketKeys := make([]string, 0)
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for k := range buckets {
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bucketKeys = append(bucketKeys, k)
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}
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sort.Strings(bucketKeys)
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for _, bucketKey := range bucketKeys {
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bucket := simplejson.NewFromAny(buckets[bucketKey])
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newProps := make(map[string]string)
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for k, v := range props {
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newProps[k] = v
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}
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newProps["filter"] = bucketKey
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err = processBuckets(bucket.MustMap(), target, queryResult, newProps, depth+1)
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if err != nil {
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return err
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}
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}
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}
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}
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return nil
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}
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func newTimeSeriesFrame(timeData []time.Time, tags map[string]string, values []*float64) *data.Frame {
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frame := data.NewFrame("",
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data.NewField("time", nil, timeData),
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data.NewField("value", tags, values))
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frame.Meta = &data.FrameMeta{
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Type: data.FrameTypeTimeSeriesMulti,
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}
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return frame
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}
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// nolint:gocyclo
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func processMetrics(esAgg *simplejson.Json, target *Query, query *backend.DataResponse,
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props map[string]string) error {
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frames := data.Frames{}
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esAggBuckets := esAgg.Get("buckets").MustArray()
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for _, metric := range target.Metrics {
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if metric.Hide {
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continue
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}
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tags := make(map[string]string, len(props))
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timeVector := make([]time.Time, 0, len(esAggBuckets))
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values := make([]*float64, 0, len(esAggBuckets))
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switch metric.Type {
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case countType:
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for _, v := range esAggBuckets {
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bucket := simplejson.NewFromAny(v)
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value := castToFloat(bucket.Get("doc_count"))
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key := castToFloat(bucket.Get("key"))
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timeVector = append(timeVector, time.Unix(int64(*key)/1000, 0).UTC())
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values = append(values, value)
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}
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for k, v := range props {
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tags[k] = v
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}
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tags["metric"] = countType
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frames = append(frames, newTimeSeriesFrame(timeVector, tags, values))
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case percentilesType:
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buckets := esAggBuckets
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if len(buckets) == 0 {
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break
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}
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firstBucket := simplejson.NewFromAny(buckets[0])
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percentiles := firstBucket.GetPath(metric.ID, "values").MustMap()
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percentileKeys := make([]string, 0)
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for k := range percentiles {
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percentileKeys = append(percentileKeys, k)
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}
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sort.Strings(percentileKeys)
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for _, percentileName := range percentileKeys {
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tags := make(map[string]string, len(props))
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timeVector := make([]time.Time, 0, len(esAggBuckets))
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values := make([]*float64, 0, len(esAggBuckets))
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for k, v := range props {
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tags[k] = v
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}
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tags["metric"] = "p" + percentileName
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tags["field"] = metric.Field
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for _, v := range buckets {
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bucket := simplejson.NewFromAny(v)
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value := castToFloat(bucket.GetPath(metric.ID, "values", percentileName))
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key := castToFloat(bucket.Get("key"))
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timeVector = append(timeVector, time.Unix(int64(*key)/1000, 0).UTC())
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values = append(values, value)
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}
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frames = append(frames, newTimeSeriesFrame(timeVector, tags, values))
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}
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case topMetricsType:
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buckets := esAggBuckets
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metrics := metric.Settings.Get("metrics").MustArray()
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for _, metricField := range metrics {
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tags := make(map[string]string, len(props))
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timeVector := make([]time.Time, 0, len(esAggBuckets))
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values := make([]*float64, 0, len(esAggBuckets))
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for k, v := range props {
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tags[k] = v
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}
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tags["field"] = metricField.(string)
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tags["metric"] = "top_metrics"
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for _, v := range buckets {
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bucket := simplejson.NewFromAny(v)
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stats := bucket.GetPath(metric.ID, "top")
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key := castToFloat(bucket.Get("key"))
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timeVector = append(timeVector, time.Unix(int64(*key)/1000, 0).UTC())
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for _, stat := range stats.MustArray() {
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stat := stat.(map[string]interface{})
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metrics, hasMetrics := stat["metrics"]
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if hasMetrics {
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metrics := metrics.(map[string]interface{})
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metricValue, hasMetricValue := metrics[metricField.(string)]
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if hasMetricValue && metricValue != nil {
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v := metricValue.(float64)
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values = append(values, &v)
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}
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}
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}
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}
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frames = append(frames, newTimeSeriesFrame(timeVector, tags, values))
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}
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case extendedStatsType:
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buckets := esAggBuckets
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metaKeys := make([]string, 0)
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meta := metric.Meta.MustMap()
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for k := range meta {
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metaKeys = append(metaKeys, k)
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}
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sort.Strings(metaKeys)
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for _, statName := range metaKeys {
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v := meta[statName]
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if enabled, ok := v.(bool); !ok || !enabled {
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continue
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}
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tags := make(map[string]string, len(props))
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timeVector := make([]time.Time, 0, len(esAggBuckets))
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values := make([]*float64, 0, len(esAggBuckets))
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for k, v := range props {
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tags[k] = v
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}
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tags["metric"] = statName
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tags["field"] = metric.Field
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for _, v := range buckets {
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bucket := simplejson.NewFromAny(v)
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key := castToFloat(bucket.Get("key"))
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var value *float64
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switch statName {
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case "std_deviation_bounds_upper":
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value = castToFloat(bucket.GetPath(metric.ID, "std_deviation_bounds", "upper"))
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case "std_deviation_bounds_lower":
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value = castToFloat(bucket.GetPath(metric.ID, "std_deviation_bounds", "lower"))
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default:
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value = castToFloat(bucket.GetPath(metric.ID, statName))
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}
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timeVector = append(timeVector, time.Unix(int64(*key)/1000, 0).UTC())
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values = append(values, value)
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}
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labels := tags
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frames = append(frames, newTimeSeriesFrame(timeVector, labels, values))
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}
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default:
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for k, v := range props {
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tags[k] = v
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}
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tags["metric"] = metric.Type
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tags["field"] = metric.Field
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tags["metricId"] = metric.ID
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for _, v := range esAggBuckets {
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bucket := simplejson.NewFromAny(v)
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key := castToFloat(bucket.Get("key"))
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valueObj, err := bucket.Get(metric.ID).Map()
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if err != nil {
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continue
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}
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var value *float64
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if _, ok := valueObj["normalized_value"]; ok {
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value = castToFloat(bucket.GetPath(metric.ID, "normalized_value"))
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} else {
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value = castToFloat(bucket.GetPath(metric.ID, "value"))
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}
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timeVector = append(timeVector, time.Unix(int64(*key)/1000, 0).UTC())
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values = append(values, value)
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}
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frames = append(frames, newTimeSeriesFrame(timeVector, tags, values))
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}
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}
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if query.Frames != nil {
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oldFrames := query.Frames
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frames = append(oldFrames, frames...)
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}
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query.Frames = frames
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return nil
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}
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func processAggregationDocs(esAgg *simplejson.Json, aggDef *BucketAgg, target *Query,
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queryResult *backend.DataResponse, props map[string]string) error {
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propKeys := make([]string, 0)
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for k := range props {
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propKeys = append(propKeys, k)
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}
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sort.Strings(propKeys)
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frames := data.Frames{}
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var fields []*data.Field
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if queryResult.Frames == nil {
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for _, propKey := range propKeys {
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fields = append(fields, data.NewField(propKey, nil, []*string{}))
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}
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}
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addMetricValue := func(values []interface{}, metricName string, value *float64) {
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index := -1
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for i, f := range fields {
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if f.Name == metricName {
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index = i
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break
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}
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}
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var field data.Field
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if index == -1 {
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field = *data.NewField(metricName, nil, []*float64{})
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fields = append(fields, &field)
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} else {
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field = *fields[index]
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}
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field.Append(value)
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}
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for _, v := range esAgg.Get("buckets").MustArray() {
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bucket := simplejson.NewFromAny(v)
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var values []interface{}
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found := false
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for _, e := range fields {
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for _, propKey := range propKeys {
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if e.Name == propKey {
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e.Append(props[propKey])
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}
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}
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if e.Name == aggDef.Field {
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found = true
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if key, err := bucket.Get("key").String(); err == nil {
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e.Append(&key)
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} else {
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f, err := bucket.Get("key").Float64()
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if err != nil {
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return err
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}
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e.Append(&f)
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}
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}
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}
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if !found {
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var aggDefField *data.Field
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if key, err := bucket.Get("key").String(); err == nil {
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aggDefField = extractDataField(aggDef.Field, &key)
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aggDefField.Append(&key)
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} else {
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f, err := bucket.Get("key").Float64()
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if err != nil {
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return err
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}
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aggDefField = extractDataField(aggDef.Field, &f)
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aggDefField.Append(&f)
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}
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fields = append(fields, aggDefField)
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}
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for _, metric := range target.Metrics {
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switch metric.Type {
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case countType:
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addMetricValue(values, getMetricName(metric.Type), castToFloat(bucket.Get("doc_count")))
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case extendedStatsType:
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metaKeys := make([]string, 0)
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meta := metric.Meta.MustMap()
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for k := range meta {
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metaKeys = append(metaKeys, k)
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}
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sort.Strings(metaKeys)
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for _, statName := range metaKeys {
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v := meta[statName]
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if enabled, ok := v.(bool); !ok || !enabled {
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continue
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}
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var value *float64
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switch statName {
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case "std_deviation_bounds_upper":
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value = castToFloat(bucket.GetPath(metric.ID, "std_deviation_bounds", "upper"))
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case "std_deviation_bounds_lower":
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value = castToFloat(bucket.GetPath(metric.ID, "std_deviation_bounds", "lower"))
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default:
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value = castToFloat(bucket.GetPath(metric.ID, statName))
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}
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addMetricValue(values, getMetricName(metric.Type), value)
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break
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}
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default:
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metricName := getMetricName(metric.Type)
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otherMetrics := make([]*MetricAgg, 0)
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for _, m := range target.Metrics {
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if m.Type == metric.Type {
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otherMetrics = append(otherMetrics, m)
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}
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}
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if len(otherMetrics) > 1 {
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metricName += " " + metric.Field
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if metric.Type == "bucket_script" {
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// Use the formula in the column name
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metricName = metric.Settings.Get("script").MustString("")
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}
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}
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addMetricValue(values, metricName, castToFloat(bucket.GetPath(metric.ID, "value")))
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}
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}
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var dataFields []*data.Field
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dataFields = append(dataFields, fields...)
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frames = data.Frames{
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&data.Frame{
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Fields: dataFields,
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}}
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}
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queryResult.Frames = frames
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return nil
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}
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func extractDataField(name string, v interface{}) *data.Field {
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switch v.(type) {
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case *string:
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return data.NewField(name, nil, []*string{})
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case *float64:
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return data.NewField(name, nil, []*float64{})
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default:
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return &data.Field{}
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}
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}
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func trimDatapoints(queryResult backend.DataResponse, target *Query) {
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var histogram *BucketAgg
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for _, bucketAgg := range target.BucketAggs {
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if bucketAgg.Type == dateHistType {
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histogram = bucketAgg
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break
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}
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}
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if histogram == nil {
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return
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}
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trimEdges, err := castToInt(histogram.Settings.Get("trimEdges"))
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if err != nil {
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return
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}
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frames := queryResult.Frames
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for _, frame := range frames {
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for _, field := range frame.Fields {
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if field.Len() > trimEdges*2 {
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// first we delete the first "trim" items
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for i := 0; i < trimEdges; i++ {
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field.Delete(0)
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}
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// then we delete the last "trim" items
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for i := 0; i < trimEdges; i++ {
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field.Delete(field.Len() - 1)
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}
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}
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}
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}
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}
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// we sort the label's pairs by the label-key,
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// and return the label-values
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func getSortedLabelValues(labels data.Labels) []string {
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var keys []string
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for key := range labels {
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keys = append(keys, key)
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}
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sort.Strings(keys)
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var values []string
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for _, key := range keys {
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values = append(values, labels[key])
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}
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return values
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}
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|
|
func nameFields(queryResult backend.DataResponse, target *Query) {
|
|
set := make(map[string]struct{})
|
|
frames := queryResult.Frames
|
|
for _, v := range frames {
|
|
for _, vv := range v.Fields {
|
|
if metricType, exists := vv.Labels["metric"]; exists {
|
|
if _, ok := set[metricType]; !ok {
|
|
set[metricType] = struct{}{}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
metricTypeCount := len(set)
|
|
for _, frame := range frames {
|
|
if frame.Meta != nil && frame.Meta.Type == data.FrameTypeTimeSeriesMulti {
|
|
// if it is a time-series-multi, it means it has two columns, one is "time",
|
|
// another is "number"
|
|
valueField := frame.Fields[1]
|
|
fieldName := getFieldName(*valueField, target, metricTypeCount)
|
|
if fieldName != "" {
|
|
valueField.SetConfig(&data.FieldConfig{DisplayNameFromDS: fieldName})
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
var aliasPatternRegex = regexp.MustCompile(`\{\{([\s\S]+?)\}\}`)
|
|
|
|
func getFieldName(dataField data.Field, target *Query, metricTypeCount int) string {
|
|
metricType := dataField.Labels["metric"]
|
|
metricName := getMetricName(metricType)
|
|
delete(dataField.Labels, "metric")
|
|
|
|
field := ""
|
|
if v, ok := dataField.Labels["field"]; ok {
|
|
field = v
|
|
delete(dataField.Labels, "field")
|
|
}
|
|
|
|
if target.Alias != "" {
|
|
frameName := target.Alias
|
|
|
|
subMatches := aliasPatternRegex.FindAllStringSubmatch(target.Alias, -1)
|
|
for _, subMatch := range subMatches {
|
|
group := subMatch[0]
|
|
|
|
if len(subMatch) > 1 {
|
|
group = subMatch[1]
|
|
}
|
|
|
|
if strings.Index(group, "term ") == 0 {
|
|
frameName = strings.Replace(frameName, subMatch[0], dataField.Labels[group[5:]], 1)
|
|
}
|
|
if v, ok := dataField.Labels[group]; ok {
|
|
frameName = strings.Replace(frameName, subMatch[0], v, 1)
|
|
}
|
|
if group == "metric" {
|
|
frameName = strings.Replace(frameName, subMatch[0], metricName, 1)
|
|
}
|
|
if group == "field" {
|
|
frameName = strings.Replace(frameName, subMatch[0], field, 1)
|
|
}
|
|
}
|
|
|
|
return frameName
|
|
}
|
|
// todo, if field and pipelineAgg
|
|
if isPipelineAgg(metricType) {
|
|
if metricType != "" && isPipelineAggWithMultipleBucketPaths(metricType) {
|
|
metricID := ""
|
|
if v, ok := dataField.Labels["metricId"]; ok {
|
|
metricID = v
|
|
}
|
|
|
|
for _, metric := range target.Metrics {
|
|
if metric.ID == metricID {
|
|
metricName = metric.Settings.Get("script").MustString()
|
|
for name, pipelineAgg := range metric.PipelineVariables {
|
|
for _, m := range target.Metrics {
|
|
if m.ID == pipelineAgg {
|
|
metricName = strings.ReplaceAll(metricName, "params."+name, describeMetric(m.Type, m.Field))
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
} else {
|
|
if field != "" {
|
|
found := false
|
|
for _, metric := range target.Metrics {
|
|
if metric.ID == field {
|
|
metricName += " " + describeMetric(metric.Type, field)
|
|
found = true
|
|
}
|
|
}
|
|
if !found {
|
|
metricName = "Unset"
|
|
}
|
|
}
|
|
}
|
|
} else if field != "" {
|
|
metricName += " " + field
|
|
}
|
|
|
|
delete(dataField.Labels, "metricId")
|
|
|
|
if len(dataField.Labels) == 0 {
|
|
return metricName
|
|
}
|
|
|
|
name := ""
|
|
for _, v := range getSortedLabelValues(dataField.Labels) {
|
|
name += v + " "
|
|
}
|
|
|
|
if metricTypeCount == 1 {
|
|
return strings.TrimSpace(name)
|
|
}
|
|
|
|
return strings.TrimSpace(name) + " " + metricName
|
|
}
|
|
|
|
func getMetricName(metric string) string {
|
|
if text, ok := metricAggType[metric]; ok {
|
|
return text
|
|
}
|
|
|
|
if text, ok := extendedStats[metric]; ok {
|
|
return text
|
|
}
|
|
|
|
return metric
|
|
}
|
|
|
|
func castToInt(j *simplejson.Json) (int, error) {
|
|
i, err := j.Int()
|
|
if err == nil {
|
|
return i, nil
|
|
}
|
|
|
|
s, err := j.String()
|
|
if err != nil {
|
|
return 0, err
|
|
}
|
|
|
|
v, err := strconv.Atoi(s)
|
|
if err != nil {
|
|
return 0, err
|
|
}
|
|
|
|
return v, nil
|
|
}
|
|
|
|
func castToFloat(j *simplejson.Json) *float64 {
|
|
f, err := j.Float64()
|
|
if err == nil {
|
|
return &f
|
|
}
|
|
|
|
if s, err := j.String(); err == nil {
|
|
if strings.ToLower(s) == "nan" {
|
|
return nil
|
|
}
|
|
|
|
if v, err := strconv.ParseFloat(s, 64); err == nil {
|
|
return &v
|
|
}
|
|
}
|
|
|
|
return nil
|
|
}
|
|
|
|
func findAgg(target *Query, aggID string) (*BucketAgg, error) {
|
|
for _, v := range target.BucketAggs {
|
|
if aggID == v.ID {
|
|
return v, nil
|
|
}
|
|
}
|
|
return nil, errors.New("can't found aggDef, aggID:" + aggID)
|
|
}
|
|
|
|
func getErrorFromElasticResponse(response *es.SearchResponse) string {
|
|
var errorString string
|
|
json := simplejson.NewFromAny(response.Error)
|
|
reason := json.Get("reason").MustString()
|
|
rootCauseReason := json.Get("root_cause").GetIndex(0).Get("reason").MustString()
|
|
causedByReason := json.Get("caused_by").Get("reason").MustString()
|
|
|
|
switch {
|
|
case rootCauseReason != "":
|
|
errorString = rootCauseReason
|
|
case reason != "":
|
|
errorString = reason
|
|
case causedByReason != "":
|
|
errorString = causedByReason
|
|
default:
|
|
errorString = "Unknown elasticsearch error response"
|
|
}
|
|
|
|
return errorString
|
|
}
|