mirror of
https://github.com/grafana/grafana.git
synced 2024-11-25 18:30:41 -06:00
d3fee607e2
* feat: sort numeric metrics behind feature toggle * chore: upgrade `dataplane/sdata` to latest tag * chore: `go work sync`
362 lines
11 KiB
Go
362 lines
11 KiB
Go
package expr
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import (
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"context"
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"fmt"
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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/expr/mathexp"
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"github.com/grafana/grafana/pkg/infra/tracing"
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"github.com/grafana/grafana/pkg/services/datasources"
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"github.com/grafana/grafana/pkg/services/featuremgmt"
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)
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type ResultConverter struct {
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Features featuremgmt.FeatureToggles
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Tracer tracing.Tracer
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}
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func (c *ResultConverter) Convert(ctx context.Context,
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datasourceType string,
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frames data.Frames,
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allowLongFrames bool,
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) (string, mathexp.Results, error) {
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if len(frames) == 0 {
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return "no-data", mathexp.Results{Values: mathexp.Values{mathexp.NewNoData()}}, nil
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}
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var dt data.FrameType
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dt, useDataplane, _ := shouldUseDataplane(frames, logger, c.Features.IsEnabled(ctx, featuremgmt.FlagDisableSSEDataplane))
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if useDataplane {
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logger.Debug("Handling SSE data source query through dataplane", "datatype", dt)
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result, err := handleDataplaneFrames(ctx, c.Tracer, c.Features, dt, frames)
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return fmt.Sprintf("dataplane-%s", dt), result, err
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}
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if isAllFrameVectors(datasourceType, frames) { // Prometheus Specific Handling
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vals, err := framesToNumbers(frames)
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if err != nil {
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return "", mathexp.Results{}, fmt.Errorf("failed to read frames as numbers: %w", err)
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}
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return "vector", mathexp.Results{Values: vals}, nil
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}
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if len(frames) == 1 {
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frame := frames[0]
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// Handle Untyped NoData
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if len(frame.Fields) == 0 {
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return "no-data", mathexp.Results{Values: mathexp.Values{mathexp.NoData{Frame: frame}}}, nil
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}
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// Handle Numeric Table
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if frame.TimeSeriesSchema().Type == data.TimeSeriesTypeNot && isNumberTable(frame) {
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numberSet, err := extractNumberSet(frame)
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if err != nil {
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return "", mathexp.Results{}, err
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}
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vals := make([]mathexp.Value, 0, len(numberSet))
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for _, n := range numberSet {
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vals = append(vals, n)
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}
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return "number set", mathexp.Results{
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Values: vals,
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}, nil
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}
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}
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filtered := make([]*data.Frame, 0, len(frames))
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totalLen := 0
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for _, frame := range frames {
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schema := frame.TimeSeriesSchema()
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// Check for TimeSeriesTypeNot in InfluxDB queries. A data frame of this type will cause
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// the WideToMany() function to error out, which results in unhealthy alerts.
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// This check should be removed once inconsistencies in data source responses are solved.
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if schema.Type == data.TimeSeriesTypeNot && datasourceType == datasources.DS_INFLUXDB {
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logger.Warn("Ignoring InfluxDB data frame due to missing numeric fields")
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continue
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}
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if schema.Type != data.TimeSeriesTypeWide && !allowLongFrames {
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return "", mathexp.Results{}, fmt.Errorf("input data must be a wide series but got type %s (input refid)", schema.Type)
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}
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filtered = append(filtered, frame)
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totalLen += len(schema.ValueIndices)
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}
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if len(filtered) == 0 {
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return "no data", mathexp.Results{Values: mathexp.Values{mathexp.NoData{Frame: frames[0]}}}, nil
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}
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maybeFixerFn := checkIfSeriesNeedToBeFixed(filtered, datasourceType)
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dataType := "single frame series"
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if len(filtered) > 1 {
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dataType = "multi frame series"
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}
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vals := make([]mathexp.Value, 0, totalLen)
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for _, frame := range filtered {
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schema := frame.TimeSeriesSchema()
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if schema.Type == data.TimeSeriesTypeWide {
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series, err := WideToMany(frame, maybeFixerFn)
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if err != nil {
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return "", mathexp.Results{}, err
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}
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for _, ser := range series {
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vals = append(vals, ser)
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}
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} else {
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v := mathexp.TableData{Frame: frame}
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vals = append(vals, v)
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dataType = "single frame"
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}
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}
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return dataType, mathexp.Results{
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Values: vals,
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}, nil
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}
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func getResponseFrame(resp *backend.QueryDataResponse, refID string) (data.Frames, error) {
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response, ok := resp.Responses[refID]
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if !ok {
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// This indicates that the RefID of the request was not included to the response, i.e. some problem in the data source plugin
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keys := make([]string, 0, len(resp.Responses))
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for refID := range resp.Responses {
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keys = append(keys, refID)
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}
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logger.Warn("Can't find response by refID. Return nodata", "responseRefIds", keys)
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return nil, nil
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}
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if response.Error != nil {
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return nil, response.Error
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}
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return response.Frames, nil
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}
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func isAllFrameVectors(datasourceType string, frames data.Frames) bool {
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if datasourceType != datasources.DS_PROMETHEUS {
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return false
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}
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allVector := false
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for i, frame := range frames {
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if frame.Meta != nil && frame.Meta.Custom != nil {
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if sMap, ok := frame.Meta.Custom.(map[string]string); ok {
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if sMap != nil {
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if sMap["resultType"] == "vector" {
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if i != 0 && !allVector {
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break
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}
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allVector = true
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}
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}
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}
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}
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}
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return allVector
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}
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func framesToNumbers(frames data.Frames) ([]mathexp.Value, error) {
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vals := make([]mathexp.Value, 0, len(frames))
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for _, frame := range frames {
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if frame == nil {
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continue
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}
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if len(frame.Fields) == 2 && frame.Fields[0].Len() == 1 {
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// Can there be zero Len Field results that are being skipped?
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valueField := frame.Fields[1]
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if valueField.Type().Numeric() { // should be []float64
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val, err := valueField.FloatAt(0) // FloatAt should not err if numeric
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if err != nil {
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return nil, fmt.Errorf("failed to read value of frame [%v] (RefID %v) of type [%v] as float: %w", frame.Name, frame.RefID, valueField.Type(), err)
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}
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n := mathexp.NewNumber(frame.Name, valueField.Labels)
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n.SetValue(&val)
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vals = append(vals, n)
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}
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}
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}
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return vals, nil
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}
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func isNumberTable(frame *data.Frame) bool {
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if frame == nil || frame.Fields == nil {
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return false
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}
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numericCount := 0
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stringCount := 0
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otherCount := 0
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for _, field := range frame.Fields {
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fType := field.Type()
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switch {
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case fType.Numeric():
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numericCount++
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case fType == data.FieldTypeString || fType == data.FieldTypeNullableString:
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stringCount++
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default:
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otherCount++
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}
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}
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return numericCount == 1 && otherCount == 0
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}
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func extractNumberSet(frame *data.Frame) ([]mathexp.Number, error) {
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numericField := 0
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stringFieldIdxs := []int{}
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stringFieldNames := []string{}
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for i, field := range frame.Fields {
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fType := field.Type()
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switch {
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case fType.Numeric():
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numericField = i
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case fType == data.FieldTypeString || fType == data.FieldTypeNullableString:
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stringFieldIdxs = append(stringFieldIdxs, i)
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stringFieldNames = append(stringFieldNames, field.Name)
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}
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}
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numbers := make([]mathexp.Number, frame.Rows())
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for rowIdx := 0; rowIdx < frame.Rows(); rowIdx++ {
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val, _ := frame.FloatAt(numericField, rowIdx)
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var labels data.Labels
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for i := 0; i < len(stringFieldIdxs); i++ {
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if i == 0 {
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labels = make(data.Labels)
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}
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key := stringFieldNames[i] // TODO check for duplicate string column names
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val, _ := frame.ConcreteAt(stringFieldIdxs[i], rowIdx)
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labels[key] = val.(string) // TODO check assertion / return error
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}
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n := mathexp.NewNumber(frame.Fields[numericField].Name, labels)
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// The new value fields' configs gets pointed to the one in the original frame
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n.Frame.Fields[0].Config = frame.Fields[numericField].Config
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n.SetValue(&val)
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numbers[rowIdx] = n
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}
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return numbers, nil
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}
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// WideToMany converts a data package wide type Frame to one or multiple Series. A series
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// is created for each value type column of wide frame.
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//
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// This might not be a good idea long term, but works now as an adapter/shim.
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func WideToMany(frame *data.Frame, fixSeries func(series mathexp.Series, valueField *data.Field)) ([]mathexp.Series, error) {
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tsSchema := frame.TimeSeriesSchema()
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if tsSchema.Type != data.TimeSeriesTypeWide {
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return nil, fmt.Errorf("input data must be a wide series but got type %s", tsSchema.Type)
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}
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if len(tsSchema.ValueIndices) == 1 {
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s, err := mathexp.SeriesFromFrame(frame)
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if err != nil {
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return nil, err
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}
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if fixSeries != nil {
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fixSeries(s, frame.Fields[tsSchema.ValueIndices[0]])
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}
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return []mathexp.Series{s}, nil
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}
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series := make([]mathexp.Series, 0, len(tsSchema.ValueIndices))
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for _, valIdx := range tsSchema.ValueIndices {
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l := frame.Rows()
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f := data.NewFrameOfFieldTypes(frame.Name, l, frame.Fields[tsSchema.TimeIndex].Type(), frame.Fields[valIdx].Type())
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f.Fields[0].Name = frame.Fields[tsSchema.TimeIndex].Name
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f.Fields[1].Name = frame.Fields[valIdx].Name
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// The new value fields' configs gets pointed to the one in the original frame
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f.Fields[1].Config = frame.Fields[valIdx].Config
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if frame.Fields[valIdx].Labels != nil {
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f.Fields[1].Labels = frame.Fields[valIdx].Labels.Copy()
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}
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for i := 0; i < l; i++ {
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f.SetRow(i, frame.Fields[tsSchema.TimeIndex].CopyAt(i), frame.Fields[valIdx].CopyAt(i))
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}
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s, err := mathexp.SeriesFromFrame(f)
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if err != nil {
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return nil, err
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}
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if fixSeries != nil {
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fixSeries(s, frame.Fields[valIdx])
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}
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series = append(series, s)
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}
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return series, nil
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}
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// checkIfSeriesNeedToBeFixed scans all value fields of all provided frames and determines whether the resulting mathexp.Series
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// needs to be updated so each series could be identifiable by labels.
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// NOTE: applicable only to only datasources.DS_GRAPHITE and datasources.DS_TESTDATA data sources
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// returns a function that patches the mathexp.Series with information from data.Field from which it was created if the all series need to be fixed. Otherwise, returns nil
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func checkIfSeriesNeedToBeFixed(frames []*data.Frame, datasourceType string) func(series mathexp.Series, valueField *data.Field) {
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if !(datasourceType == datasources.DS_GRAPHITE || datasourceType == datasources.DS_TESTDATA) {
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return nil
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}
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// get all value fields
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var valueFields []*data.Field
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for _, frame := range frames {
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tsSchema := frame.TimeSeriesSchema()
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for _, index := range tsSchema.ValueIndices {
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field := frame.Fields[index]
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// if at least one value field contains labels, the result does not need to be fixed.
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if len(field.Labels) > 0 {
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return nil
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}
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if valueFields == nil {
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valueFields = make([]*data.Field, 0, len(frames)*len(tsSchema.ValueIndices))
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}
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valueFields = append(valueFields, field)
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}
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}
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// selectors are in precedence order.
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nameSelectors := []func(f *data.Field) string{
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func(f *data.Field) string {
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if f == nil || f.Config == nil {
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return ""
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}
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return f.Config.DisplayNameFromDS
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},
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func(f *data.Field) string {
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if f == nil || f.Config == nil {
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return ""
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}
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return f.Config.DisplayName
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},
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func(f *data.Field) string {
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return f.Name
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},
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}
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// now look for the first selector that would make all value fields be unique
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for _, selector := range nameSelectors {
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names := make(map[string]struct{}, len(valueFields))
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good := true
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for _, field := range valueFields {
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name := selector(field)
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if _, ok := names[name]; ok || name == "" {
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good = false
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break
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}
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names[name] = struct{}{}
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}
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if good {
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return func(series mathexp.Series, valueField *data.Field) {
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series.SetLabels(data.Labels{
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nameLabelName: selector(valueField),
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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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