grafana/pkg/expr/converter.go
Kyle Brandt 82aa000e9d
SSE: (Chore) Update log line with context (trace) (#89172)
Improves log line to help with debugging in Server Side Expressions. In particular, the traceId, datasourceType, and datasourceUid will now be included.
2024-06-13 10:58:39 -04:00

363 lines
11 KiB
Go

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