The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
grafana/pkg/tsdb/cloudmonitoring/time_series_query.go

367 lines
12 KiB

package cloudmonitoring
import (
"bytes"
"context"
"encoding/json"
"fmt"
"net/url"
"path"
"strconv"
"strings"
"time"
"github.com/grafana/grafana-plugin-sdk-go/data"
"github.com/grafana/grafana/pkg/components/simplejson"
"github.com/grafana/grafana/pkg/tsdb"
"github.com/opentracing/opentracing-go"
"golang.org/x/net/context/ctxhttp"
)
func (timeSeriesQuery cloudMonitoringTimeSeriesQuery) run(ctx context.Context, tsdbQuery *tsdb.TsdbQuery, e *CloudMonitoringExecutor) (*tsdb.QueryResult, cloudMonitoringResponse, string, error) {
queryResult := &tsdb.QueryResult{Meta: simplejson.New(), RefId: timeSeriesQuery.RefID}
projectName := timeSeriesQuery.ProjectName
if projectName == "" {
defaultProject, err := e.getDefaultProject(ctx)
if err != nil {
queryResult.Error = err
return queryResult, cloudMonitoringResponse{}, "", nil
}
projectName = defaultProject
slog.Info("No project name set on query, using project name from datasource", "projectName", projectName)
}
from, err := tsdbQuery.TimeRange.ParseFrom()
if err != nil {
queryResult.Error = err
return queryResult, cloudMonitoringResponse{}, "", nil
}
to, err := tsdbQuery.TimeRange.ParseTo()
if err != nil {
queryResult.Error = err
return queryResult, cloudMonitoringResponse{}, "", nil
}
intervalCalculator := tsdb.NewIntervalCalculator(&tsdb.IntervalOptions{})
interval := intervalCalculator.Calculate(tsdbQuery.TimeRange, time.Duration(timeSeriesQuery.IntervalMS/1000)*time.Second)
timeFormat := "2006/01/02-15:04:05"
timeSeriesQuery.Query += fmt.Sprintf(" | graph_period %s | within d'%s', d'%s'", interval.Text, from.UTC().Format(timeFormat), to.UTC().Format(timeFormat))
buf, err := json.Marshal(map[string]interface{}{
"query": timeSeriesQuery.Query,
})
if err != nil {
queryResult.Error = err
return queryResult, cloudMonitoringResponse{}, "", nil
}
req, err := e.createRequest(ctx, e.dsInfo, path.Join("cloudmonitoringv3/projects", projectName, "timeSeries:query"), bytes.NewBuffer(buf))
if err != nil {
queryResult.Error = err
return queryResult, cloudMonitoringResponse{}, "", nil
}
span, ctx := opentracing.StartSpanFromContext(ctx, "cloudMonitoring MQL query")
span.SetTag("query", timeSeriesQuery.Query)
span.SetTag("from", tsdbQuery.TimeRange.From)
span.SetTag("until", tsdbQuery.TimeRange.To)
span.SetTag("datasource_id", e.dsInfo.Id)
span.SetTag("org_id", e.dsInfo.OrgId)
defer span.Finish()
if err := opentracing.GlobalTracer().Inject(
span.Context(),
opentracing.HTTPHeaders,
opentracing.HTTPHeadersCarrier(req.Header)); err != nil {
queryResult.Error = err
return queryResult, cloudMonitoringResponse{}, "", nil
}
res, err := ctxhttp.Do(ctx, e.httpClient, req)
if err != nil {
queryResult.Error = err
return queryResult, cloudMonitoringResponse{}, "", nil
}
data, err := unmarshalResponse(res)
if err != nil {
queryResult.Error = err
return queryResult, cloudMonitoringResponse{}, "", nil
}
return queryResult, data, timeSeriesQuery.Query, nil
}
func (timeSeriesQuery cloudMonitoringTimeSeriesQuery) parseResponse(queryRes *tsdb.QueryResult, response cloudMonitoringResponse, executedQueryString string) error {
labels := make(map[string]map[string]bool)
frames := data.Frames{}
for _, series := range response.TimeSeriesData {
seriesLabels := make(map[string]string)
frame := data.NewFrameOfFieldTypes("", len(series.PointData), data.FieldTypeTime, data.FieldTypeFloat64)
frame.RefID = timeSeriesQuery.RefID
frame.Meta = &data.FrameMeta{
ExecutedQueryString: executedQueryString,
}
for n, d := range response.TimeSeriesDescriptor.LabelDescriptors {
key := toSnakeCase(d.Key)
key = strings.Replace(key, ".", ".label.", 1)
if _, ok := labels[key]; !ok {
labels[key] = map[string]bool{}
}
labelValue := series.LabelValues[n]
switch d.ValueType {
case "BOOL":
strVal := strconv.FormatBool(labelValue.BoolValue)
labels[key][strVal] = true
seriesLabels[key] = strVal
case "INT64":
intVal := strconv.FormatInt(labelValue.Int64Value, 10)
labels[key][intVal] = true
seriesLabels[key] = intVal
default:
labels[key][labelValue.StringValue] = true
seriesLabels[key] = labelValue.StringValue
}
}
for n, d := range response.TimeSeriesDescriptor.PointDescriptors {
if _, ok := labels["metric.name"]; !ok {
labels["metric.name"] = map[string]bool{}
}
labels["metric.name"][d.Key] = true
seriesLabels["metric.name"] = d.Key
defaultMetricName := d.Key
// process non-distribution series
if d.ValueType != "DISTRIBUTION" {
// reverse the order to be ascending
for i := len(series.PointData) - 1; i >= 0; i-- {
point := series.PointData[i]
value := point.Values[n].DoubleValue
if d.ValueType == "INT64" {
parsedValue, err := strconv.ParseFloat(point.Values[n].Int64Value, 64)
if err == nil {
value = parsedValue
}
} else if d.ValueType == "BOOL" {
if point.Values[n].BoolValue {
value = 1
} else {
value = 0
}
}
frame.SetRow(len(series.PointData)-1-i, series.PointData[i].TimeInterval.EndTime, value)
}
metricName := formatLegendKeys(d.Key, defaultMetricName, seriesLabels, nil, &cloudMonitoringTimeSeriesFilter{ProjectName: timeSeriesQuery.ProjectName, AliasBy: timeSeriesQuery.AliasBy})
dataField := frame.Fields[1]
dataField.Name = metricName
frames = append(frames, frame)
continue
}
// process distribution series
buckets := make(map[int]*data.Frame)
// reverse the order to be ascending
for i := len(series.PointData) - 1; i >= 0; i-- {
point := series.PointData[i]
if len(point.Values[n].DistributionValue.BucketCounts) == 0 {
continue
}
maxKey := 0
for i := 0; i < len(point.Values[n].DistributionValue.BucketCounts); i++ {
value, err := strconv.ParseFloat(point.Values[n].DistributionValue.BucketCounts[i], 64)
if err != nil {
continue
}
if _, ok := buckets[i]; !ok {
// set lower bounds
// https://cloud.google.com/monitoring/api/ref_v3/rest/v3/TimeSeries#Distribution
bucketBound := calcBucketBound(point.Values[n].DistributionValue.BucketOptions, i)
additionalLabels := map[string]string{"bucket": bucketBound}
timeField := data.NewField(data.TimeSeriesTimeFieldName, nil, []time.Time{})
valueField := data.NewField(data.TimeSeriesValueFieldName, nil, []float64{})
frameName := formatLegendKeys(d.Key, defaultMetricName, nil, additionalLabels, &cloudMonitoringTimeSeriesFilter{ProjectName: timeSeriesQuery.ProjectName, AliasBy: timeSeriesQuery.AliasBy})
valueField.Name = frameName
buckets[i] = &data.Frame{
Name: frameName,
Fields: []*data.Field{
timeField,
valueField,
},
RefID: timeSeriesQuery.RefID,
}
if maxKey < i {
maxKey = i
}
}
buckets[i].AppendRow(point.TimeInterval.EndTime, value)
}
// fill empty bucket
for i := 0; i < maxKey; i++ {
if _, ok := buckets[i]; !ok {
bucketBound := calcBucketBound(point.Values[n].DistributionValue.BucketOptions, i)
additionalLabels := data.Labels{"bucket": bucketBound}
timeField := data.NewField(data.TimeSeriesTimeFieldName, nil, []time.Time{})
valueField := data.NewField(data.TimeSeriesValueFieldName, nil, []float64{})
frameName := formatLegendKeys(d.Key, defaultMetricName, seriesLabels, additionalLabels, &cloudMonitoringTimeSeriesFilter{ProjectName: timeSeriesQuery.ProjectName, AliasBy: timeSeriesQuery.AliasBy})
valueField.Name = frameName
buckets[i] = &data.Frame{
Name: frameName,
Fields: []*data.Field{
timeField,
valueField,
},
RefID: timeSeriesQuery.RefID,
}
}
}
}
for i := 0; i < len(buckets); i++ {
frames = append(frames, buckets[i])
}
}
}
if len(response.TimeSeriesData) > 0 {
dl := timeSeriesQuery.buildDeepLink()
frames = addConfigData(frames, dl)
}
queryRes.Dataframes = tsdb.NewDecodedDataFrames(frames)
labelsByKey := make(map[string][]string)
for key, values := range labels {
for value := range values {
labelsByKey[key] = append(labelsByKey[key], value)
}
}
queryRes.Meta.Set("labels", labelsByKey)
return nil
}
func (timeSeriesQuery cloudMonitoringTimeSeriesQuery) parseToAnnotations(queryRes *tsdb.QueryResult, data cloudMonitoringResponse, title string, text string, tags string) error {
annotations := make([]map[string]string, 0)
for _, series := range data.TimeSeriesData {
metricLabels := make(map[string]string)
resourceLabels := make(map[string]string)
for n, d := range data.TimeSeriesDescriptor.LabelDescriptors {
key := toSnakeCase(d.Key)
labelValue := series.LabelValues[n]
value := ""
switch d.ValueType {
case "BOOL":
strVal := strconv.FormatBool(labelValue.BoolValue)
value = strVal
case "INT64":
intVal := strconv.FormatInt(labelValue.Int64Value, 10)
value = intVal
default:
value = labelValue.StringValue
}
if strings.Index(key, "metric.") == 0 {
key = key[len("metric."):]
metricLabels[key] = value
} else if strings.Index(key, "resource.") == 0 {
key = key[len("resource."):]
resourceLabels[key] = value
}
}
for n, d := range data.TimeSeriesDescriptor.PointDescriptors {
// reverse the order to be ascending
for i := len(series.PointData) - 1; i >= 0; i-- {
point := series.PointData[i]
value := strconv.FormatFloat(point.Values[n].DoubleValue, 'f', 6, 64)
if d.ValueType == "STRING" {
value = point.Values[n].StringValue
}
annotation := make(map[string]string)
annotation["time"] = point.TimeInterval.EndTime.UTC().Format(time.RFC3339)
annotation["title"] = formatAnnotationText(title, value, d.MetricKind, metricLabels, resourceLabels)
annotation["tags"] = tags
annotation["text"] = formatAnnotationText(text, value, d.MetricKind, metricLabels, resourceLabels)
annotations = append(annotations, annotation)
}
}
}
transformAnnotationToTable(annotations, queryRes)
return nil
}
func (timeSeriesQuery cloudMonitoringTimeSeriesQuery) buildDeepLink() string {
u, err := url.Parse("https://console.cloud.google.com/monitoring/metrics-explorer")
if err != nil {
slog.Error("Failed to generate deep link: unable to parse metrics explorer URL", "projectName", timeSeriesQuery.ProjectName, "query", timeSeriesQuery.RefID)
return ""
}
q := u.Query()
q.Set("project", timeSeriesQuery.ProjectName)
q.Set("Grafana_deeplink", "true")
pageState := map[string]interface{}{
"xyChart": map[string]interface{}{
"constantLines": []string{},
"dataSets": []map[string]interface{}{
{
"timeSeriesQuery": timeSeriesQuery.Query,
"targetAxis": "Y1",
"plotType": "LINE",
},
},
"timeshiftDuration": "0s",
"y1Axis": map[string]string{
"label": "y1Axis",
"scale": "LINEAR",
},
},
"timeSelection": map[string]string{
"timeRange": "custom",
"start": timeSeriesQuery.timeRange.MustGetFrom().Format(time.RFC3339Nano),
"end": timeSeriesQuery.timeRange.MustGetTo().Format(time.RFC3339Nano),
},
}
blob, err := json.Marshal(pageState)
if err != nil {
slog.Error("Failed to generate deep link", "pageState", pageState, "ProjectName", timeSeriesQuery.ProjectName, "query", timeSeriesQuery.RefID)
return ""
}
q.Set("pageState", string(blob))
u.RawQuery = q.Encode()
accountChooserURL, err := url.Parse("https://accounts.google.com/AccountChooser")
if err != nil {
slog.Error("Failed to generate deep link: unable to parse account chooser URL", "ProjectName", timeSeriesQuery.ProjectName, "query", timeSeriesQuery.RefID)
return ""
}
accountChooserQuery := accountChooserURL.Query()
accountChooserQuery.Set("continue", u.String())
accountChooserURL.RawQuery = accountChooserQuery.Encode()
return accountChooserURL.String()
}
func (timeSeriesQuery cloudMonitoringTimeSeriesQuery) getRefID() string {
return timeSeriesQuery.RefID
}
func (timeSeriesQuery *cloudMonitoringTimeSeriesQuery) getUnit() string {
return timeSeriesQuery.Unit
}