package testdatasource import ( "context" "encoding/base64" "encoding/json" "fmt" "math" "math/rand" "strconv" "strings" "time" "github.com/grafana/grafana-plugin-sdk-go/backend" "github.com/grafana/grafana-plugin-sdk-go/data" "github.com/grafana/grafana/pkg/components/simplejson" ) const ( randomWalkQuery queryType = "random_walk" randomWalkSlowQuery queryType = "slow_query" randomWalkWithErrorQuery queryType = "random_walk_with_error" randomWalkTableQuery queryType = "random_walk_table" exponentialHeatmapBucketDataQuery queryType = "exponential_heatmap_bucket_data" linearHeatmapBucketDataQuery queryType = "linear_heatmap_bucket_data" noDataPointsQuery queryType = "no_data_points" datapointsOutsideRangeQuery queryType = "datapoints_outside_range" csvMetricValuesQuery queryType = "csv_metric_values" predictablePulseQuery queryType = "predictable_pulse" predictableCSVWaveQuery queryType = "predictable_csv_wave" streamingClientQuery queryType = "streaming_client" simulation queryType = "simulation" usaQueryKey queryType = "usa" liveQuery queryType = "live" grafanaAPIQuery queryType = "grafana_api" arrowQuery queryType = "arrow" annotationsQuery queryType = "annotations" tableStaticQuery queryType = "table_static" serverError500Query queryType = "server_error_500" logsQuery queryType = "logs" nodeGraphQuery queryType = "node_graph" flameGraphQuery queryType = "flame_graph" rawFrameQuery queryType = "raw_frame" csvFileQueryType queryType = "csv_file" csvContentQueryType queryType = "csv_content" traceType queryType = "trace" ) type queryType string type Scenario struct { ID string `json:"id"` Name string `json:"name"` StringInput string `json:"stringInput"` Description string `json:"description"` handler backend.QueryDataHandlerFunc } func (s *Service) registerScenarios() { s.registerScenario(&Scenario{ ID: string(exponentialHeatmapBucketDataQuery), Name: "Exponential heatmap bucket data", handler: s.handleExponentialHeatmapBucketDataScenario, }) s.registerScenario(&Scenario{ ID: string(linearHeatmapBucketDataQuery), Name: "Linear heatmap bucket data", handler: s.handleLinearHeatmapBucketDataScenario, }) s.registerScenario(&Scenario{ ID: string(randomWalkQuery), Name: "Random Walk", handler: s.handleRandomWalkScenario, }) s.registerScenario(&Scenario{ ID: string(predictablePulseQuery), Name: "Predictable Pulse", handler: s.handlePredictablePulseScenario, Description: `Predictable Pulse returns a pulse wave where there is a datapoint every timeStepSeconds. The wave cycles at timeStepSeconds*(onCount+offCount). The cycle of the wave is based off of absolute time (from the epoch) which makes it predictable. Timestamps will line up evenly on timeStepSeconds (For example, 60 seconds means times will all end in :00 seconds).`, }) s.registerScenario(&Scenario{ ID: string(predictableCSVWaveQuery), Name: "Predictable CSV Wave", handler: s.handlePredictableCSVWaveScenario, }) s.registerScenario(&Scenario{ ID: string(randomWalkTableQuery), Name: "Random Walk Table", handler: s.handleRandomWalkTableScenario, }) s.registerScenario(&Scenario{ ID: string(randomWalkSlowQuery), Name: "Slow Query", StringInput: "5s", handler: s.handleRandomWalkSlowScenario, }) s.registerScenario(&Scenario{ ID: string(noDataPointsQuery), Name: "No Data Points", handler: s.handleClientSideScenario, }) s.registerScenario(&Scenario{ ID: string(datapointsOutsideRangeQuery), Name: "Datapoints Outside Range", handler: s.handleDatapointsOutsideRangeScenario, }) s.registerScenario(&Scenario{ ID: string(csvMetricValuesQuery), Name: "CSV Metric Values", StringInput: "1,20,90,30,5,0", handler: s.handleCSVMetricValuesScenario, }) s.registerScenario(&Scenario{ ID: string(streamingClientQuery), Name: "Streaming Client", handler: s.handleClientSideScenario, }) s.registerScenario(&Scenario{ ID: string(liveQuery), Name: "Grafana Live", handler: s.handleClientSideScenario, }) s.registerScenario(&Scenario{ ID: string(simulation), Name: "Simulation", handler: s.sims.QueryData, }) s.registerScenario(&Scenario{ ID: string(usaQueryKey), Name: "USA generated data", handler: s.handleUSAScenario, }) s.registerScenario(&Scenario{ ID: string(grafanaAPIQuery), Name: "Grafana API", handler: s.handleClientSideScenario, }) s.registerScenario(&Scenario{ ID: string(arrowQuery), Name: "Load Apache Arrow Data", handler: s.handleArrowScenario, }) s.registerScenario(&Scenario{ ID: string(annotationsQuery), Name: "Annotations", handler: s.handleClientSideScenario, }) s.registerScenario(&Scenario{ ID: string(tableStaticQuery), Name: "Table Static", handler: s.handleTableStaticScenario, }) s.registerScenario(&Scenario{ ID: string(randomWalkWithErrorQuery), Name: "Random Walk (with error)", handler: s.handleRandomWalkWithErrorScenario, }) s.registerScenario(&Scenario{ // Is no longer strictly a _server_ error scenario, but ID is kept for legacy :) ID: string(serverError500Query), Name: "Conditional Error", handler: s.handleServerError500Scenario, StringInput: "1,20,90,30,5,0", Description: "Returns an error when the String Input field is empty", }) s.registerScenario(&Scenario{ ID: string(logsQuery), Name: "Logs", handler: s.handleLogsScenario, }) s.registerScenario(&Scenario{ ID: string(nodeGraphQuery), Name: "Node Graph", }) s.registerScenario(&Scenario{ ID: string(flameGraphQuery), Name: "Flame Graph", }) s.registerScenario(&Scenario{ ID: string(rawFrameQuery), Name: "Raw Frames", }) s.registerScenario(&Scenario{ ID: string(csvFileQueryType), Name: "CSV File", handler: s.handleCsvFileScenario, }) s.registerScenario(&Scenario{ ID: string(csvContentQueryType), Name: "CSV Content", handler: s.handleCsvContentScenario, }) s.registerScenario(&Scenario{ ID: string(traceType), Name: "Trace", }) s.queryMux.HandleFunc("", s.handleFallbackScenario) } func (s *Service) registerScenario(scenario *Scenario) { s.scenarios[scenario.ID] = scenario s.queryMux.HandleFunc(scenario.ID, scenario.handler) } // handleFallbackScenario handles the scenario where queryType is not set and fallbacks to scenarioId. func (s *Service) handleFallbackScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { scenarioQueries := map[string][]backend.DataQuery{} for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { s.logger.Error("Failed to unmarshal query model to JSON", "error", err) continue } scenarioID := model.Get("scenarioId").MustString(string(randomWalkQuery)) if _, exist := s.scenarios[scenarioID]; exist { if _, ok := scenarioQueries[scenarioID]; !ok { scenarioQueries[scenarioID] = []backend.DataQuery{} } scenarioQueries[scenarioID] = append(scenarioQueries[scenarioID], q) } else { s.logger.Error("Scenario not found", "scenarioId", scenarioID) } } resp := backend.NewQueryDataResponse() for scenarioID, queries := range scenarioQueries { if scenario, exist := s.scenarios[scenarioID]; exist { sReq := &backend.QueryDataRequest{ PluginContext: req.PluginContext, Headers: req.Headers, Queries: queries, } if sResp, err := scenario.handler(ctx, sReq); err != nil { s.logger.Error("Failed to handle scenario", "scenarioId", scenarioID, "error", err) } else { for refID, dr := range sResp.Responses { resp.Responses[refID] = dr } } } } return resp, nil } func (s *Service) handleRandomWalkScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { continue } seriesCount := model.Get("seriesCount").MustInt(1) for i := 0; i < seriesCount; i++ { respD := resp.Responses[q.RefID] respD.Frames = append(respD.Frames, RandomWalk(q, model, i)) resp.Responses[q.RefID] = respD } } return resp, nil } func (s *Service) handleDatapointsOutsideRangeScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { continue } frame := newSeriesForQuery(q, model, 0) outsideTime := q.TimeRange.From.Add(-1 * time.Hour) frame.Fields = data.Fields{ data.NewField(data.TimeSeriesTimeFieldName, nil, []time.Time{outsideTime}), data.NewField(data.TimeSeriesValueFieldName, nil, []float64{10}), } respD := resp.Responses[q.RefID] respD.Frames = append(respD.Frames, frame) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handleCSVMetricValuesScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { continue } stringInput := model.Get("stringInput").MustString() valueField, err := csvLineToField(stringInput) if err != nil { return nil, err } valueField.Name = frameNameForQuery(q, model, 0) timeField := data.NewFieldFromFieldType(data.FieldTypeTime, valueField.Len()) timeField.Name = "time" startTime := q.TimeRange.From.UnixNano() / int64(time.Millisecond) endTime := q.TimeRange.To.UnixNano() / int64(time.Millisecond) count := valueField.Len() var step int64 = 0 if count > 1 { step = (endTime - startTime) / int64(count-1) } for i := 0; i < count; i++ { t := time.Unix(startTime/int64(1e+3), (startTime%int64(1e+3))*int64(1e+6)) timeField.Set(i, t) startTime += step } frame := data.NewFrame("", timeField, valueField) respD := resp.Responses[q.RefID] respD.Frames = append(respD.Frames, frame) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handleRandomWalkWithErrorScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { continue } respD := resp.Responses[q.RefID] respD.Frames = append(respD.Frames, RandomWalk(q, model, 0)) respD.Error = fmt.Errorf("this is an error and it can include URLs http://grafana.com/") resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handleRandomWalkSlowScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { continue } stringInput := model.Get("stringInput").MustString() parsedInterval, _ := time.ParseDuration(stringInput) time.Sleep(parsedInterval) respD := resp.Responses[q.RefID] respD.Frames = append(respD.Frames, RandomWalk(q, model, 0)) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handleRandomWalkTableScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { continue } respD := resp.Responses[q.RefID] respD.Frames = append(respD.Frames, randomWalkTable(q, model)) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handlePredictableCSVWaveScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { return nil, err } respD := resp.Responses[q.RefID] frames, err := predictableCSVWave(q, model) if err != nil { return nil, err } respD.Frames = append(respD.Frames, frames...) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handlePredictablePulseScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { continue } respD := resp.Responses[q.RefID] frame, err := predictablePulse(q, model) if err != nil { continue } respD.Frames = append(respD.Frames, frame) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handleServerError500Scenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { continue } stringInput := model.Get("stringInput").MustString() if stringInput == "" { panic("Test Data Panic!") } } return s.handleCSVMetricValuesScenario(ctx, req) } func (s *Service) handleClientSideScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { return backend.NewQueryDataResponse(), nil } func (s *Service) handleArrowScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { model, err := simplejson.NewJson(q.JSON) if err != nil { return nil, err } respD := resp.Responses[q.RefID] frame, err := doArrowQuery(q, model) if err != nil { return nil, err } if frame == nil { continue } respD.Frames = append(respD.Frames, frame) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handleExponentialHeatmapBucketDataScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { respD := resp.Responses[q.RefID] frame := randomHeatmapData(q, func(index int) float64 { return math.Exp2(float64(index)) }) respD.Frames = append(respD.Frames, frame) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handleLinearHeatmapBucketDataScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { respD := resp.Responses[q.RefID] frame := randomHeatmapData(q, func(index int) float64 { return float64(index * 10) }) respD.Frames = append(respD.Frames, frame) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handleTableStaticScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { timeWalkerMs := q.TimeRange.From.UnixNano() / int64(time.Millisecond) to := q.TimeRange.To.UnixNano() / int64(time.Millisecond) step := q.Interval.Milliseconds() frame := data.NewFrame(q.RefID, data.NewField("Time", nil, []time.Time{}), data.NewField("Message", nil, []string{}), data.NewField("Description", nil, []string{}), data.NewField("Value", nil, []float64{}), ) for i := int64(0); i < 10 && timeWalkerMs < to; i++ { t := time.Unix(timeWalkerMs/int64(1e+3), (timeWalkerMs%int64(1e+3))*int64(1e+6)) frame.AppendRow(t, "This is a message", "Description", 23.1) timeWalkerMs += step } respD := resp.Responses[q.RefID] respD.Frames = append(respD.Frames, frame) resp.Responses[q.RefID] = respD } return resp, nil } func (s *Service) handleLogsScenario(ctx context.Context, req *backend.QueryDataRequest) (*backend.QueryDataResponse, error) { resp := backend.NewQueryDataResponse() for _, q := range req.Queries { from := q.TimeRange.From.UnixNano() / int64(time.Millisecond) to := q.TimeRange.To.UnixNano() / int64(time.Millisecond) model, err := simplejson.NewJson(q.JSON) if err != nil { continue } lines := model.Get("lines").MustInt64(10) includeLevelColumn := model.Get("levelColumn").MustBool(false) logLevelGenerator := newRandomStringProvider([]string{ "emerg", "alert", "crit", "critical", "warn", "warning", "err", "eror", "error", "info", "notice", "dbug", "debug", "trace", "", }) containerIDGenerator := newRandomStringProvider([]string{ "f36a9eaa6d34310686f2b851655212023a216de955cbcc764210cefa71179b1a", "5a354a630364f3742c602f315132e16def594fe68b1e4a195b2fce628e24c97a", }) hostnameGenerator := newRandomStringProvider([]string{ "srv-001", "srv-002", }) frame := data.NewFrame(q.RefID, data.NewField("time", nil, []time.Time{}), data.NewField("message", nil, []string{}), data.NewField("container_id", nil, []string{}), data.NewField("hostname", nil, []string{}), ).SetMeta(&data.FrameMeta{ PreferredVisualization: "logs", }) if includeLevelColumn { frame.Fields = append(frame.Fields, data.NewField("level", nil, []string{})) } for i := int64(0); i < lines && to > from; i++ { logLevel := logLevelGenerator.Next() timeFormatted := time.Unix(to/1000, 0).Format(time.RFC3339) lvlString := "" if !includeLevelColumn { lvlString = fmt.Sprintf("lvl=%s ", logLevel) } message := fmt.Sprintf("t=%s %smsg=\"Request Completed\" logger=context userId=1 orgId=1 uname=admin method=GET path=/api/datasources/proxy/152/api/prom/label status=502 remote_addr=[::1] time_ms=1 size=0 referer=\"http://localhost:3000/explore?left=%%5B%%22now-6h%%22,%%22now%%22,%%22Prometheus%%202.x%%22,%%7B%%7D,%%7B%%22ui%%22:%%5Btrue,true,true,%%22none%%22%%5D%%7D%%5D\"", timeFormatted, lvlString) containerID := containerIDGenerator.Next() hostname := hostnameGenerator.Next() t := time.Unix(to/int64(1e+3), (to%int64(1e+3))*int64(1e+6)) if includeLevelColumn { frame.AppendRow(t, message, containerID, hostname, logLevel) } else { frame.AppendRow(t, message, containerID, hostname) } to -= q.Interval.Milliseconds() } respD := resp.Responses[q.RefID] respD.Frames = append(respD.Frames, frame) resp.Responses[q.RefID] = respD } return resp, nil } func RandomWalk(query backend.DataQuery, model *simplejson.Json, index int) *data.Frame { rand := rand.New(rand.NewSource(time.Now().UnixNano())) timeWalkerMs := query.TimeRange.From.UnixNano() / int64(time.Millisecond) to := query.TimeRange.To.UnixNano() / int64(time.Millisecond) startValue := model.Get("startValue").MustFloat64(rand.Float64() * 100) spread := model.Get("spread").MustFloat64(1) noise := model.Get("noise").MustFloat64(0) drop := model.Get("drop").MustFloat64(0) / 100.0 // value is 0-100 min, err := model.Get("min").Float64() hasMin := err == nil max, err := model.Get("max").Float64() hasMax := err == nil timeVec := make([]*time.Time, 0) floatVec := make([]*float64, 0) walker := startValue for i := int64(0); i < 10000 && timeWalkerMs < to; i++ { nextValue := walker + (rand.Float64() * noise) if hasMin && nextValue < min { nextValue = min walker = min } if hasMax && nextValue > max { nextValue = max walker = max } if drop > 0 && rand.Float64() < drop { // skip value } else { t := time.Unix(timeWalkerMs/int64(1e+3), (timeWalkerMs%int64(1e+3))*int64(1e+6)) timeVec = append(timeVec, &t) floatVec = append(floatVec, &nextValue) } walker += (rand.Float64() - 0.5) * spread timeWalkerMs += query.Interval.Milliseconds() } return data.NewFrame("", data.NewField("time", nil, timeVec). SetConfig(&data.FieldConfig{ Interval: float64(query.Interval.Milliseconds()), }), data.NewField(frameNameForQuery(query, model, index), parseLabels(model), floatVec), ) } func randomWalkTable(query backend.DataQuery, model *simplejson.Json) *data.Frame { rand := rand.New(rand.NewSource(time.Now().UnixNano())) timeWalkerMs := query.TimeRange.From.UnixNano() / int64(time.Millisecond) to := query.TimeRange.To.UnixNano() / int64(time.Millisecond) withNil := model.Get("withNil").MustBool(false) walker := model.Get("startValue").MustFloat64(rand.Float64() * 100) spread := 2.5 stateField := data.NewFieldFromFieldType(data.FieldTypeEnum, 0) stateField.Name = "State" stateField.Config = &data.FieldConfig{ TypeConfig: &data.FieldTypeConfig{ Enum: &data.EnumFieldConfig{ Text: []string{ "Unknown", "Up", "Down", // 0,1,2 }, }, }, } frame := data.NewFrame(query.RefID, data.NewField("Time", nil, []*time.Time{}), data.NewField("Value", nil, []*float64{}), data.NewField("Min", nil, []*float64{}), data.NewField("Max", nil, []*float64{}), data.NewField("Info", nil, []*string{}), stateField, ) var info strings.Builder state := data.EnumItemIndex(0) for i := int64(0); i < query.MaxDataPoints && timeWalkerMs < to; i++ { delta := rand.Float64() - 0.5 walker += delta info.Reset() if delta > 0 { info.WriteString("up") state = 1 } else { info.WriteString("down") state = 2 } if math.Abs(delta) > .4 { info.WriteString(" fast") } t := time.Unix(timeWalkerMs/int64(1e+3), (timeWalkerMs%int64(1e+3))*int64(1e+6)) val := walker min := walker - ((rand.Float64() * spread) + 0.01) max := walker + ((rand.Float64() * spread) + 0.01) infoString := info.String() vals := []*float64{&val, &min, &max} // Add some random null values if withNil && rand.Float64() > 0.8 { for i := range vals { if rand.Float64() > .2 { vals[i] = nil state = 0 } } } frame.AppendRow(&t, vals[0], vals[1], vals[2], &infoString, state) timeWalkerMs += query.Interval.Milliseconds() } return frame } type pCSVOptions struct { TimeStep int64 `json:"timeStep"` ValuesCSV string `json:"valuesCSV"` Labels string `json:"labels"` Name string `json:"name"` } func predictableCSVWave(query backend.DataQuery, model *simplejson.Json) ([]*data.Frame, error) { rawQueries, err := model.Get("csvWave").ToDB() if err != nil { return nil, err } queries := []pCSVOptions{} err = json.Unmarshal(rawQueries, &queries) if err != nil { return nil, err } frames := make([]*data.Frame, 0, len(queries)) for _, subQ := range queries { var err error rawValues := strings.TrimRight(strings.TrimSpace(subQ.ValuesCSV), ",") // Strip Trailing Comma rawValesCSV := strings.Split(rawValues, ",") values := make([]*float64, len(rawValesCSV)) for i, rawValue := range rawValesCSV { var val *float64 rawValue = strings.TrimSpace(rawValue) switch rawValue { case "null": // val stays nil case "nan": f := math.NaN() val = &f default: f, err := strconv.ParseFloat(rawValue, 64) if err != nil { return nil, fmt.Errorf("failed to parse value '%v' into nullable float: %w", rawValue, err) } val = &f } values[i] = val } subQ.TimeStep *= 1000 // Seconds to Milliseconds valuesLen := int64(len(values)) getValue := func(mod int64) (*float64, error) { var i int64 for i = 0; i < valuesLen; i++ { if mod == i*subQ.TimeStep { return values[i], nil } } return nil, fmt.Errorf("did not get value at point in waveform - should not be here") } fields, err := predictableSeries(query.TimeRange, subQ.TimeStep, valuesLen, getValue) if err != nil { return nil, err } frame := newSeriesForQuery(query, model, 0) frame.Fields = fields frame.Fields[1].Labels = parseLabelsString(subQ.Labels) if subQ.Name != "" { frame.Name = subQ.Name } frames = append(frames, frame) } return frames, nil } func predictableSeries(timeRange backend.TimeRange, timeStep, length int64, getValue func(mod int64) (*float64, error)) (data.Fields, error) { from := timeRange.From.UnixNano() / int64(time.Millisecond) to := timeRange.To.UnixNano() / int64(time.Millisecond) timeCursor := from - (from % timeStep) // Truncate Start wavePeriod := timeStep * length maxPoints := 10000 // Don't return too many points timeVec := make([]*time.Time, 0) floatVec := make([]*float64, 0) for i := 0; i < maxPoints && timeCursor < to; i++ { val, err := getValue(timeCursor % wavePeriod) if err != nil { return nil, err } t := time.Unix(timeCursor/int64(1e+3), (timeCursor%int64(1e+3))*int64(1e+6)) timeVec = append(timeVec, &t) floatVec = append(floatVec, val) timeCursor += timeStep } return data.Fields{ data.NewField(data.TimeSeriesTimeFieldName, nil, timeVec), data.NewField(data.TimeSeriesValueFieldName, nil, floatVec), }, nil } func predictablePulse(query backend.DataQuery, model *simplejson.Json) (*data.Frame, error) { // Process Input var timeStep int64 var onCount int64 var offCount int64 var onValue *float64 var offValue *float64 options := model.Get("pulseWave") var err error if timeStep, err = options.Get("timeStep").Int64(); err != nil { return nil, fmt.Errorf("failed to parse timeStep value '%v' into integer: %v", options.Get("timeStep"), err) } if onCount, err = options.Get("onCount").Int64(); err != nil { return nil, fmt.Errorf("failed to parse onCount value '%v' into integer: %v", options.Get("onCount"), err) } if offCount, err = options.Get("offCount").Int64(); err != nil { return nil, fmt.Errorf("failed to parse offCount value '%v' into integer: %v", options.Get("offCount"), err) } onValue, err = fromStringOrNumber(options.Get("onValue")) if err != nil { return nil, fmt.Errorf("failed to parse onValue value '%v' into float: %v", options.Get("onValue"), err) } offValue, err = fromStringOrNumber(options.Get("offValue")) if err != nil { return nil, fmt.Errorf("failed to parse offValue value '%v' into float: %v", options.Get("offValue"), err) } timeStep *= 1000 // Seconds to Milliseconds onFor := func(mod int64) (*float64, error) { // How many items in the cycle should get the on value var i int64 for i = 0; i < onCount; i++ { if mod == i*timeStep { return onValue, nil } } return offValue, nil } fields, err := predictableSeries(query.TimeRange, timeStep, onCount+offCount, onFor) if err != nil { return nil, err } frame := newSeriesForQuery(query, model, 0) frame.Fields = fields frame.Fields[1].Labels = parseLabels(model) return frame, nil } func randomHeatmapData(query backend.DataQuery, fnBucketGen func(index int) float64) *data.Frame { rand := rand.New(rand.NewSource(time.Now().UnixNano())) frame := data.NewFrame("data", data.NewField("time", nil, []*time.Time{})) for i := 0; i < 10; i++ { frame.Fields = append(frame.Fields, data.NewField(strconv.FormatInt(int64(fnBucketGen(i)), 10), nil, []*float64{})) } timeWalkerMs := query.TimeRange.From.UnixNano() / int64(time.Millisecond) to := query.TimeRange.To.UnixNano() / int64(time.Millisecond) for j := int64(0); j < 100 && timeWalkerMs < to; j++ { t := time.Unix(timeWalkerMs/int64(1e+3), (timeWalkerMs%int64(1e+3))*int64(1e+6)) vals := []interface{}{&t} for n := 1; n < len(frame.Fields); n++ { v := float64(rand.Int63n(100)) vals = append(vals, &v) } frame.AppendRow(vals...) timeWalkerMs += query.Interval.Milliseconds() * 50 } return frame } func doArrowQuery(query backend.DataQuery, model *simplejson.Json) (*data.Frame, error) { encoded := model.Get("stringInput").MustString("") if encoded == "" { return nil, nil } arrow, err := base64.StdEncoding.DecodeString(encoded) if err != nil { return nil, err } return data.UnmarshalArrowFrame(arrow) } func newSeriesForQuery(query backend.DataQuery, model *simplejson.Json, index int) *data.Frame { alias := model.Get("alias").MustString("") suffix := "" if index > 0 { suffix = strconv.Itoa(index) } if alias == "" { alias = fmt.Sprintf("%s-series%s", query.RefID, suffix) } if alias == "__server_names" && len(serverNames) > index { alias = serverNames[index] } if alias == "__house_locations" && len(houseLocations) > index { alias = houseLocations[index] } return data.NewFrame(alias) } /** * Looks for a labels request and adds them as tags * * '{job="foo", instance="bar"} => {job: "foo", instance: "bar"}` */ func parseLabels(model *simplejson.Json) data.Labels { labelText := model.Get("labels").MustString("") return parseLabelsString(labelText) } func parseLabelsString(labelText string) data.Labels { if labelText == "" { return data.Labels{} } text := strings.Trim(labelText, `{}`) if len(text) < 2 { return data.Labels{} } tags := make(data.Labels) for _, keyval := range strings.Split(text, ",") { idx := strings.Index(keyval, "=") key := strings.TrimSpace(keyval[:idx]) val := strings.TrimSpace(keyval[idx+1:]) val = strings.Trim(val, "\"") tags[key] = val } return tags } func frameNameForQuery(query backend.DataQuery, model *simplejson.Json, index int) string { name := model.Get("alias").MustString("") suffix := "" if index > 0 { suffix = strconv.Itoa(index) } if name == "" { name = fmt.Sprintf("%s-series%s", query.RefID, suffix) } if name == "__server_names" && len(serverNames) > index { name = serverNames[index] } if name == "__house_locations" && len(houseLocations) > index { name = houseLocations[index] } return name } func fromStringOrNumber(val *simplejson.Json) (*float64, error) { switch v := val.Interface().(type) { case json.Number: fV, err := v.Float64() if err != nil { return nil, err } return &fV, nil case string: switch v { case "null": return nil, nil case "nan": v := math.NaN() return &v, nil default: return nil, fmt.Errorf("failed to extract value from %v", v) } default: return nil, fmt.Errorf("failed to extract value") } } var serverNames = []string{ "Backend-ops-01", "Backend-ops-02", "Backend-ops-03", "Backend-ops-04", "Frontend-web-01", "Frontend-web-02", "Frontend-web-03", "Frontend-web-04", "MySQL-01", "MySQL-02", "MySQL-03", "MySQL-04", "Postgres-01", "Postgres-02", "Postgres-03", "Postgres-04", "DB-01", "DB-02", "SAN-01", "SAN-02", "SAN-02", "SAN-04", "Kaftka-01", "Kaftka-02", "Kaftka-03", "Zookeeper-01", "Zookeeper-02", "Zookeeper-03", "Zookeeper-04", } var houseLocations = []string{ "Cellar", "Living room", "Porch", "Bedroom", "Guest room", "Kitchen", "Playroom", "Bathroom", "Outside", "Roof", "Terrace", }