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https://github.com/grafana/grafana.git
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InfluxDB: Parse data for table view to have parity with frontend parser (#78365)
* Use TimeSeriesWide format for table response * fix group by query result parsing * handle labels * provide a test where result has no tags * parsing results without time column * clean the code * remove the comment line * more cleaning * lint
This commit is contained in:
ismail simsek
GitHub
parent
eef8525a4b
commit
c5f3ce1371
@ -49,9 +49,13 @@ func parse(buf io.Reader, statusCode int, query *models.Query) *backend.DataResp
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result := response.Results[0]
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if result.Error != "" {
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return &backend.DataResponse{Error: fmt.Errorf(result.Error)}
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} else {
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return &backend.DataResponse{Frames: transformRows(result.Series, *query)}
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}
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if query.ResultFormat == "table" {
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return &backend.DataResponse{Frames: transformRowsForTable(result.Series, *query)}
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}
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return &backend.DataResponse{Frames: transformRowsForTimeSeries(result.Series, *query)}
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}
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func parseJSON(buf io.Reader) (models.Response, error) {
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@ -65,7 +69,125 @@ func parseJSON(buf io.Reader) (models.Response, error) {
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return response, err
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}
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func transformRows(rows []models.Row, query models.Query) data.Frames {
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func transformRowsForTable(rows []models.Row, query models.Query) data.Frames {
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if len(rows) == 0 {
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return make([]*data.Frame, 0)
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}
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frames := make([]*data.Frame, 0, 1)
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newFrame := data.NewFrame(rows[0].Name)
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newFrame.Meta = &data.FrameMeta{
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ExecutedQueryString: query.RawQuery,
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PreferredVisualization: getVisType(query.ResultFormat),
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}
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conLen := len(rows[0].Columns)
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if rows[0].Columns[0] == "time" {
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newFrame.Fields = append(newFrame.Fields, newTimeField(rows))
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} else {
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newFrame.Fields = append(newFrame.Fields, newValueFields(rows, nil, 0, 1)...)
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}
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newFrame.Fields = append(newFrame.Fields, newTagField(rows, nil)...)
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newFrame.Fields = append(newFrame.Fields, newValueFields(rows, nil, 1, conLen)...)
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frames = append(frames, newFrame)
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return frames
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}
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func newTimeField(rows []models.Row) *data.Field {
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var timeArray []time.Time
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for _, row := range rows {
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for _, valuePair := range row.Values {
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timestamp, timestampErr := parseTimestamp(valuePair[0])
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// we only add this row if the timestamp is valid
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if timestampErr != nil {
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continue
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}
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timeArray = append(timeArray, timestamp)
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}
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}
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timeField := data.NewField("Time", nil, timeArray)
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return timeField
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}
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func newTagField(rows []models.Row, labels data.Labels) []*data.Field {
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fields := make([]*data.Field, 0, len(rows[0].Tags))
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for key := range rows[0].Tags {
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tagField := data.NewField(key, labels, []*string{})
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for _, row := range rows {
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for range row.Values {
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value := row.Tags[key]
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tagField.Append(&value)
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}
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}
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tagField.SetConfig(&data.FieldConfig{DisplayNameFromDS: key})
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fields = append(fields, tagField)
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}
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return fields
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}
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func newValueFields(rows []models.Row, labels data.Labels, colIdxStart, colIdxEnd int) []*data.Field {
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fields := make([]*data.Field, 0)
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for colIdx := colIdxStart; colIdx < colIdxEnd; colIdx++ {
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var valueField *data.Field
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var floatArray []*float64
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var stringArray []*string
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var boolArray []*bool
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for _, row := range rows {
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valType := typeof(row.Values, colIdx)
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for _, valuePair := range row.Values {
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switch valType {
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case "string":
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value, ok := valuePair[colIdx].(string)
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if ok {
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stringArray = append(stringArray, &value)
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} else {
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stringArray = append(stringArray, nil)
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}
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case "json.Number":
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value := parseNumber(valuePair[colIdx])
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floatArray = append(floatArray, value)
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case "bool":
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value, ok := valuePair[colIdx].(bool)
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if ok {
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boolArray = append(boolArray, &value)
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} else {
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boolArray = append(boolArray, nil)
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}
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case "null":
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floatArray = append(floatArray, nil)
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}
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}
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switch valType {
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case "string":
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valueField = data.NewField(row.Columns[colIdx], labels, stringArray)
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case "json.Number":
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valueField = data.NewField(row.Columns[colIdx], labels, floatArray)
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case "bool":
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valueField = data.NewField(row.Columns[colIdx], labels, boolArray)
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case "null":
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valueField = data.NewField(row.Columns[colIdx], labels, floatArray)
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}
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valueField.SetConfig(&data.FieldConfig{DisplayNameFromDS: row.Columns[colIdx]})
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}
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fields = append(fields, valueField)
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}
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return fields
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}
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func transformRowsForTimeSeries(rows []models.Row, query models.Query) data.Frames {
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// pre-allocate frames - this can save many allocations
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cols := 0
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for _, row := range rows {
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@ -810,6 +810,97 @@ func TestResponseParser_Parse_RetentionPolicy(t *testing.T) {
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})
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}
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func TestResponseParser_table_format(t *testing.T) {
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t.Run("test table result format parsing", func(t *testing.T) {
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resp := ResponseParse(prepare(tableResultFormatInfluxResponse1), 200, &models.Query{RefID: "A", RawQuery: `a nice query`, ResultFormat: "table"})
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assert.Equal(t, 1, len(resp.Frames))
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assert.Equal(t, "a nice query", resp.Frames[0].Meta.ExecutedQueryString)
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assert.Equal(t, 3, len(resp.Frames[0].Fields))
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for i := range resp.Frames[0].Fields {
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assert.Equal(t, resp.Frames[0].Fields[0].Len(), resp.Frames[0].Fields[i].Len())
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}
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assert.Equal(t, "Time", resp.Frames[0].Fields[0].Name)
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assert.Equal(t, "usage_idle", resp.Frames[0].Fields[1].Name)
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assert.Equal(t, toPtr(99.09456740445926), resp.Frames[0].Fields[1].At(2))
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assert.Equal(t, "usage_iowait", resp.Frames[0].Fields[2].Name)
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})
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t.Run("test table result format parsing with grouping", func(t *testing.T) {
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resp := ResponseParse(prepare(tableResultFormatInfluxResponse2), 200, &models.Query{RefID: "A", RawQuery: `a nice query`, ResultFormat: "table"})
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assert.Equal(t, 1, len(resp.Frames))
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assert.Equal(t, "a nice query", resp.Frames[0].Meta.ExecutedQueryString)
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assert.Equal(t, 7, len(resp.Frames[0].Fields))
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for i := range resp.Frames[0].Fields {
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assert.Equal(t, resp.Frames[0].Fields[0].Len(), resp.Frames[0].Fields[i].Len())
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}
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assert.Equal(t, "Time", resp.Frames[0].Fields[0].Name)
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assert.Equal(t, "cpu", resp.Frames[0].Fields[1].Name)
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assert.Equal(t, toPtr("cpu-total"), resp.Frames[0].Fields[1].At(0))
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assert.Equal(t, toPtr("cpu0"), resp.Frames[0].Fields[1].At(1))
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assert.Equal(t, toPtr("cpu9"), resp.Frames[0].Fields[1].At(10))
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assert.Equal(t, "mean", resp.Frames[0].Fields[2].Name)
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assert.Equal(t, "min", resp.Frames[0].Fields[3].Name)
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assert.Equal(t, "p90", resp.Frames[0].Fields[4].Name)
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assert.Equal(t, "p95", resp.Frames[0].Fields[5].Name)
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assert.Equal(t, "max", resp.Frames[0].Fields[6].Name)
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})
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t.Run("parse result as table group by tag", func(t *testing.T) {
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resp := ResponseParse(prepare(tableResultFormatInfluxResponse3), 200, &models.Query{RefID: "A", RawQuery: `a nice query`, ResultFormat: "table"})
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assert.Equal(t, 1, len(resp.Frames))
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assert.Equal(t, "a nice query", resp.Frames[0].Meta.ExecutedQueryString)
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for i := range resp.Frames[0].Fields {
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assert.Equal(t, resp.Frames[0].Fields[0].Len(), resp.Frames[0].Fields[i].Len())
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}
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assert.Equal(t, "Time", resp.Frames[0].Fields[0].Name)
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assert.Equal(t, "cpu", resp.Frames[0].Fields[1].Name)
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assert.Equal(t, resp.Frames[0].Fields[1].Name, resp.Frames[0].Fields[1].Config.DisplayNameFromDS)
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assert.Equal(t, toPtr("cpu-total"), resp.Frames[0].Fields[1].At(0))
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assert.Equal(t, toPtr("cpu0"), resp.Frames[0].Fields[1].At(5))
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assert.Equal(t, toPtr("cpu2"), resp.Frames[0].Fields[1].At(12))
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assert.Equal(t, "mean", resp.Frames[0].Fields[2].Name)
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assert.Equal(t, resp.Frames[0].Fields[2].Name, resp.Frames[0].Fields[2].Config.DisplayNameFromDS)
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})
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t.Run("parse result without tags as table", func(t *testing.T) {
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resp := ResponseParse(prepare(tableResultFormatInfluxResponse4), 200, &models.Query{RefID: "A", RawQuery: `a nice query`, ResultFormat: "table"})
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assert.Equal(t, 1, len(resp.Frames))
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assert.Equal(t, "a nice query", resp.Frames[0].Meta.ExecutedQueryString)
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for i := range resp.Frames[0].Fields {
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assert.Equal(t, resp.Frames[0].Fields[0].Len(), resp.Frames[0].Fields[i].Len())
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}
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assert.Equal(t, "Time", resp.Frames[0].Fields[0].Name)
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assert.Equal(t, "mean", resp.Frames[0].Fields[1].Name)
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assert.Equal(t, resp.Frames[0].Fields[1].Name, resp.Frames[0].Fields[1].Config.DisplayNameFromDS)
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})
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t.Run("parse show measurements response as table", func(t *testing.T) {
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resp := ResponseParse(prepare(showMeasurementsResponse), 200, &models.Query{RefID: "A", RawQuery: `a nice query`, ResultFormat: "table"})
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assert.Equal(t, 1, len(resp.Frames))
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assert.Equal(t, "a nice query", resp.Frames[0].Meta.ExecutedQueryString)
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for i := range resp.Frames[0].Fields {
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assert.Equal(t, resp.Frames[0].Fields[0].Len(), resp.Frames[0].Fields[i].Len())
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}
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assert.Equal(t, 1, len(resp.Frames[0].Fields))
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assert.Equal(t, "name", resp.Frames[0].Fields[0].Name)
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})
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t.Run("parse retention policy response as table", func(t *testing.T) {
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resp := ResponseParse(prepare(showRetentionPolicyResponse), 200, &models.Query{RefID: "A", RawQuery: `a nice query`, ResultFormat: "table"})
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assert.Equal(t, 1, len(resp.Frames))
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assert.Equal(t, "a nice query", resp.Frames[0].Meta.ExecutedQueryString)
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for i := range resp.Frames[0].Fields {
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assert.Equal(t, resp.Frames[0].Fields[0].Len(), resp.Frames[0].Fields[i].Len())
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}
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assert.Equal(t, 5, len(resp.Frames[0].Fields))
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assert.Equal(t, "name", resp.Frames[0].Fields[0].Name)
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assert.Equal(t, "duration", resp.Frames[0].Fields[1].Name)
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assert.Equal(t, "shardGroupDuration", resp.Frames[0].Fields[2].Name)
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assert.Equal(t, "replicaN", resp.Frames[0].Fields[3].Name)
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assert.Equal(t, "default", resp.Frames[0].Fields[4].Name)
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})
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}
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func TestResponseParser_Parse(t *testing.T) {
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tests := []struct {
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name string
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@ -912,10 +1003,9 @@ func TestResponseParser_Parse(t *testing.T) {
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]
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}`,
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f: func(t *testing.T, got backend.DataResponse) {
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assert.Equal(t, "domain", got.Frames[0].Name)
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assert.Equal(t, "Annotation", got.Frames[0].Name)
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assert.Equal(t, "domain", got.Frames[0].Fields[1].Config.DisplayNameFromDS)
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assert.Equal(t, "ASD", got.Frames[2].Name)
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assert.Equal(t, "ASD", got.Frames[2].Fields[1].Config.DisplayNameFromDS)
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assert.Equal(t, "type", got.Frames[0].Fields[2].Config.DisplayNameFromDS)
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assert.Equal(t, tableVisType, got.Frames[0].Meta.PreferredVisualization)
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},
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},
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@ -930,3 +1020,578 @@ func TestResponseParser_Parse(t *testing.T) {
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})
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}
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}
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func toPtr[T any](v T) *T {
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return &v
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}
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const tableResultFormatInfluxResponse1 = `{
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"results": [
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{
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"statement_id": 0,
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"series": [
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{
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"name": "cpu",
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"columns": [
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"time",
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"usage_idle",
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"usage_iowait"
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],
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"values": [
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[
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1700090120000,
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99.0255173802101,
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0.020092425155804713
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],
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[
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1700090120000,
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99.29718875523953,
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0
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],
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[
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1700090120000,
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99.09456740445926,
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0
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],
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[
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1700090120000,
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99.39455095864957,
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0
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],
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[
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1700090120000,
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99.09729187566201,
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0
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]
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]
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}
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]
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}
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]
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}`
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const tableResultFormatInfluxResponse2 = `{
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"results": [
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{
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"statement_id": 0,
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"series": [
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{
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"name": "cpu",
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"tags": {
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"cpu": "cpu-total"
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},
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"columns": [
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"time",
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"mean",
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"min",
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"p90",
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"p95",
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"max"
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],
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"values": [
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[
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1700046000000,
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99.06348570053983,
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97.3214285712978,
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99.2066680055868,
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99.24812030075188,
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99.31809065366402
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]
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]
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},
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{
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"name": "cpu",
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"tags": {
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"cpu": "cpu0"
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},
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"columns": [
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"time",
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"mean",
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"min",
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"p90",
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"p95",
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"max"
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],
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"values": [
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[
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1700046000000,
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98.99671817733766,
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96.65991902847126,
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99.29364278499536,
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99.29718875523953,
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99.59839357421622
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]
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]
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},
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{
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"name": "cpu",
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"tags": {
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"cpu": "cpu1"
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},
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"columns": [
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"time",
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"mean",
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"min",
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"p90",
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"p95",
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"max"
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],
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"values": [
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[
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1700046000000,
|
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99.03148357927465,
|
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96.67673715996412,
|
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99.39698492464545,
|
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99.39759036146867,
|
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99.59798994966731
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]
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]
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},
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{
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"name": "cpu",
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"tags": {
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"cpu": "cpu2"
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},
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"columns": [
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"time",
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"mean",
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"min",
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"p90",
|
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"p95",
|
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"max"
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],
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"values": [
|
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[
|
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1700046000000,
|
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99.03087433486812,
|
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96.03658536600605,
|
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99.29859719431953,
|
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99.39759036146867,
|
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99.59879638908582
|
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]
|
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]
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},
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{
|
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"name": "cpu",
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"tags": {
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"cpu": "cpu3"
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},
|
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"columns": [
|
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"time",
|
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"mean",
|
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"min",
|
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"p90",
|
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"p95",
|
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"max"
|
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],
|
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"values": [
|
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[
|
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1700046000000,
|
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99.0796957137731,
|
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97.37903225797402,
|
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99.39698492464723,
|
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99.39879759521435,
|
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99.4984954865762
|
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]
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]
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},
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{
|
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"name": "cpu",
|
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"tags": {
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"cpu": "cpu4"
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},
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"columns": [
|
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"time",
|
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"mean",
|
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"min",
|
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"p90",
|
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"p95",
|
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"max"
|
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],
|
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"values": [
|
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[
|
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1700046000000,
|
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99.09573460946685,
|
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97.57330637016123,
|
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99.39759036146867,
|
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99.49698189117252,
|
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99.59839357450608
|
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]
|
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]
|
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},
|
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{
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"name": "cpu",
|
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"tags": {
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"cpu": "cpu5"
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},
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"columns": [
|
||||
"time",
|
||||
"mean",
|
||||
"min",
|
||||
"p90",
|
||||
"p95",
|
||||
"max"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.0690883079725,
|
||||
96.65991902847126,
|
||||
99.39698492464545,
|
||||
99.39819458377468,
|
||||
99.59798994995865
|
||||
]
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "cpu",
|
||||
"tags": {
|
||||
"cpu": "cpu6"
|
||||
},
|
||||
"columns": [
|
||||
"time",
|
||||
"mean",
|
||||
"min",
|
||||
"p90",
|
||||
"p95",
|
||||
"max"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.06475215715605,
|
||||
97.37108190081956,
|
||||
99.39698492464545,
|
||||
99.39879759521259,
|
||||
99.69879518073434
|
||||
]
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "cpu",
|
||||
"tags": {
|
||||
"cpu": "cpu7"
|
||||
},
|
||||
"columns": [
|
||||
"time",
|
||||
"mean",
|
||||
"min",
|
||||
"p90",
|
||||
"p95",
|
||||
"max"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.06204005079694,
|
||||
97.7596741344093,
|
||||
99.39637826964127,
|
||||
99.39759036147042,
|
||||
99.59879638908698
|
||||
]
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "cpu",
|
||||
"tags": {
|
||||
"cpu": "cpu8"
|
||||
},
|
||||
"columns": [
|
||||
"time",
|
||||
"mean",
|
||||
"min",
|
||||
"p90",
|
||||
"p95",
|
||||
"max"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.0999818796052,
|
||||
96.56565656568982,
|
||||
99.39698492464723,
|
||||
99.39819458377468,
|
||||
99.59758551299777
|
||||
]
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "cpu",
|
||||
"tags": {
|
||||
"cpu": "cpu9"
|
||||
},
|
||||
"columns": [
|
||||
"time",
|
||||
"mean",
|
||||
"min",
|
||||
"p90",
|
||||
"p95",
|
||||
"max"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.10477313534511,
|
||||
96.8463886063268,
|
||||
99.39759036146867,
|
||||
99.39819458377468,
|
||||
99.59839357421622
|
||||
]
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
`
|
||||
|
||||
const tableResultFormatInfluxResponse3 = `{
|
||||
"results": [
|
||||
{
|
||||
"statement_id": 0,
|
||||
"series": [
|
||||
{
|
||||
"name": "cpu",
|
||||
"tags": {
|
||||
"cpu": "cpu-total"
|
||||
},
|
||||
"columns": [
|
||||
"time",
|
||||
"mean"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.06919189833442
|
||||
],
|
||||
[
|
||||
1700047200000,
|
||||
99.13105510262923
|
||||
],
|
||||
[
|
||||
1700048400000,
|
||||
98.99236330721192
|
||||
],
|
||||
[
|
||||
1700049600000,
|
||||
98.80510091380069
|
||||
]
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "cpu",
|
||||
"tags": {
|
||||
"cpu": "cpu0"
|
||||
},
|
||||
"columns": [
|
||||
"time",
|
||||
"mean"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.01372119142576
|
||||
],
|
||||
[
|
||||
1700047200000,
|
||||
99.00430308480553
|
||||
],
|
||||
[
|
||||
1700048400000,
|
||||
98.9737996641964
|
||||
],
|
||||
[
|
||||
1700049600000,
|
||||
98.79638916754935
|
||||
]
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "cpu",
|
||||
"tags": {
|
||||
"cpu": "cpu1"
|
||||
},
|
||||
"columns": [
|
||||
"time",
|
||||
"mean"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.04949983158023
|
||||
],
|
||||
[
|
||||
1700047200000,
|
||||
99.06989461231551
|
||||
],
|
||||
[
|
||||
1700048400000,
|
||||
98.97954813782476
|
||||
],
|
||||
[
|
||||
1700049600000,
|
||||
98.49246231161365
|
||||
]
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "cpu",
|
||||
"tags": {
|
||||
"cpu": "cpu2"
|
||||
},
|
||||
"columns": [
|
||||
"time",
|
||||
"mean"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.11296419686643
|
||||
],
|
||||
[
|
||||
1700047200000,
|
||||
99.01817278917116
|
||||
],
|
||||
[
|
||||
1700048400000,
|
||||
98.96847021232013
|
||||
],
|
||||
[
|
||||
1700049600000,
|
||||
98.192771084406
|
||||
]
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "cpu",
|
||||
"tags": {
|
||||
"cpu": "cpu3"
|
||||
},
|
||||
"columns": [
|
||||
"time",
|
||||
"mean"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.0742704326151
|
||||
],
|
||||
[
|
||||
1700047200000,
|
||||
99.17835628293322
|
||||
],
|
||||
[
|
||||
1700048400000,
|
||||
98.98968994907334
|
||||
],
|
||||
[
|
||||
1700049600000,
|
||||
98.69215291745849
|
||||
]
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
`
|
||||
|
||||
const tableResultFormatInfluxResponse4 = `{
|
||||
"results": [
|
||||
{
|
||||
"statement_id": 0,
|
||||
"series": [
|
||||
{
|
||||
"name": "cpu",
|
||||
"columns": [
|
||||
"time",
|
||||
"mean"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
1700046000000,
|
||||
99.0693929754458
|
||||
],
|
||||
[
|
||||
1700047200000,
|
||||
99.13073313839024
|
||||
],
|
||||
[
|
||||
1700048400000,
|
||||
98.99278645182834
|
||||
],
|
||||
[
|
||||
1700049600000,
|
||||
98.77818123433566
|
||||
]
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}`
|
||||
|
||||
const showMeasurementsResponse = `{
|
||||
"results": [
|
||||
{
|
||||
"statement_id": 0,
|
||||
"series": [
|
||||
{
|
||||
"name": "measurements",
|
||||
"columns": [
|
||||
"name"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
"cpu"
|
||||
],
|
||||
[
|
||||
"disk"
|
||||
],
|
||||
[
|
||||
"diskio"
|
||||
],
|
||||
[
|
||||
"kernel"
|
||||
]
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}`
|
||||
|
||||
const showRetentionPolicyResponse = `{
|
||||
"results": [
|
||||
{
|
||||
"statement_id": 0,
|
||||
"series": [
|
||||
{
|
||||
"columns": [
|
||||
"name",
|
||||
"duration",
|
||||
"shardGroupDuration",
|
||||
"replicaN",
|
||||
"default"
|
||||
],
|
||||
"values": [
|
||||
[
|
||||
"default",
|
||||
"0s",
|
||||
"168h0m0s",
|
||||
1,
|
||||
true
|
||||
],
|
||||
[
|
||||
"autogen",
|
||||
"0s",
|
||||
"168h0m0s",
|
||||
1,
|
||||
false
|
||||
]
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}`
|
||||
|
||||
Loading…
Reference in New Issue
Block a user