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Prometheus: add support for new _experimental_ sparse histograms/heatmaps (#47801)

Browse Source 
Co-authored-by: Ryan McKinley <ryantxu@gmail.com>
This commit is contained in:
Björn Rabenstein
2022-05-16 02:47:18 +02:00
committed by GitHub
parent 6f1f7cdc88
commit 97759c75f4
13 changed files with 23913 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files

11
packages/grafana-data/src/types/dataFrameTypes.ts
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@@ -9,6 +9,9 @@ export enum DataFrameType {
TimeSeriesLong = 'timeseries-long',
TimeSeriesMany = 'timeseries-many',
/** Directory listing */
DirectoryListing = 'directory-listing',
/**
* First field is X, the rest are bucket values
*/
@@ -22,6 +25,10 @@ export enum DataFrameType {
*/
HeatmapScanlines = 'heatmap-scanlines',
/** Directory listing */
DirectoryListing = 'directory-listing',
/**
* WIP sparse heatmap support
*
* @private
*/
HeatmapSparse = 'heatmap-cells-sparse',
}

143
pkg/util/converter/prom.go
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@@ -358,6 +358,8 @@ func readMatrixOrVector(iter *jsoniter.Iterator, resultType string) *backend.Dat
valueField.Name = data.TimeSeriesValueFieldName
valueField.Labels = data.Labels{}
var histogram *histogramInfo
for l1Field := iter.ReadObject(); l1Field != ""; l1Field = iter.ReadObject() {
switch l1Field {
case "metric":
@@ -379,15 +381,51 @@ func readMatrixOrVector(iter *jsoniter.Iterator, resultType string) *backend.Dat
valueField.Append(v)
}
}
case "histogram":
if histogram == nil {
histogram = newHistogramInfo()
}
err := readHistogram(iter, histogram)
if err != nil {
rsp.Error = err
}
case "histograms":
if histogram == nil {
histogram = newHistogramInfo()
}
for iter.ReadArray() {
err := readHistogram(iter, histogram)
if err != nil {
rsp.Error = err
}
}
default:
iter.Skip()
logf("readMatrixOrVector: %s\n", l1Field)
}
}
frame := data.NewFrame("", timeField, valueField)
frame.Meta = &data.FrameMeta{
Type: data.FrameTypeTimeSeriesMany,
Custom: resultTypeToCustomMeta(resultType),
if histogram != nil {
histogram.yMin.Labels = valueField.Labels
frame := data.NewFrame(valueField.Name, histogram.time, histogram.yMin, histogram.yMax, histogram.count, histogram.yLayout)
frame.Meta = &data.FrameMeta{
Type: "heatmap-cells-sparse",
}
if frame.Name == data.TimeSeriesValueFieldName {
frame.Name = "" // only set the name if useful
}
rsp.Frames = append(rsp.Frames, frame)
} else {
frame := data.NewFrame("", timeField, valueField)
frame.Meta = &data.FrameMeta{
Type: data.FrameTypeTimeSeriesMany,
Custom: resultTypeToCustomMeta(resultType),
}
rsp.Frames = append(rsp.Frames, frame)
}
rsp.Frames = append(rsp.Frames, frame)
}
return rsp
@@ -405,6 +443,101 @@ func readTimeValuePair(iter *jsoniter.Iterator) (time.Time, float64, error) {
return tt, fv, err
}
type histogramInfo struct {
//XMax (time) YMin Ymax Count YLayout
time *data.Field
yMin *data.Field // will have labels?
yMax *data.Field
count *data.Field
yLayout *data.Field
}
func newHistogramInfo() *histogramInfo {
hist := &histogramInfo{
time: data.NewFieldFromFieldType(data.FieldTypeTime, 0),
yMin: data.NewFieldFromFieldType(data.FieldTypeFloat64, 0),
yMax: data.NewFieldFromFieldType(data.FieldTypeFloat64, 0),
count: data.NewFieldFromFieldType(data.FieldTypeFloat64, 0),
yLayout: data.NewFieldFromFieldType(data.FieldTypeInt8, 0),
}
hist.time.Name = "xMax"
hist.yMin.Name = "yMin"
hist.yMax.Name = "yMax"
hist.count.Name = "count"
hist.yLayout.Name = "yLayout"
return hist
}
// This will read a single sparse histogram
// [ time, { count, sum, buckets: [...] }]
func readHistogram(iter *jsoniter.Iterator, hist *histogramInfo) error {
// first element
iter.ReadArray()
t := timeFromFloat(iter.ReadFloat64())
var err error
// next object element
iter.ReadArray()
for l1Field := iter.ReadObject(); l1Field != ""; l1Field = iter.ReadObject() {
switch l1Field {
case "count":
iter.Skip()
case "sum":
iter.Skip()
case "buckets":
for iter.ReadArray() {
hist.time.Append(t)
iter.ReadArray()
hist.yLayout.Append(iter.ReadInt8())
iter.ReadArray()
err = appendValueFromString(iter, hist.yMin)
if err != nil {
return err
}
iter.ReadArray()
err = appendValueFromString(iter, hist.yMax)
if err != nil {
return err
}
iter.ReadArray()
err = appendValueFromString(iter, hist.count)
if err != nil {
return err
}
if iter.ReadArray() {
return fmt.Errorf("expected close array")
}
}
default:
iter.Skip()
logf("[SKIP]readHistogram: %s\n", l1Field)
}
}
if iter.ReadArray() {
return fmt.Errorf("expected to be done")
}
return nil
}
func appendValueFromString(iter *jsoniter.Iterator, field *data.Field) error {
v, err := strconv.ParseFloat(iter.ReadString(), 64)
if err != nil {
return err
}
field.Append(v)
return nil
}
func readStream(iter *jsoniter.Iterator) *backend.DataResponse {
rsp := &backend.DataResponse{}

3
pkg/util/converter/prom_test.go
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@@ -18,6 +18,9 @@ func TestReadPromFrames(t *testing.T) {
"prom-labels",
"prom-matrix",
"prom-matrix-with-nans",
"prom-matrix-histogram-no-labels",
"prom-matrix-histogram-partitioned",
"prom-vector-histogram-no-labels",
"prom-vector",
"prom-string",
"prom-scalar",

70
pkg/util/converter/testdata/prom-matrix-histogram-no-labels-frame.json vendored Normal file
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27
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5668
pkg/util/converter/testdata/prom-matrix-histogram-no-labels.json vendored Normal file
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1636
pkg/util/converter/testdata/prom-matrix-histogram-partitioned-frame.json vendored Normal file
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490
pkg/util/converter/testdata/prom-matrix-histogram-partitioned-golden.txt vendored Normal file
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14922
pkg/util/converter/testdata/prom-matrix-histogram-partitioned.json vendored Normal file
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70
pkg/util/converter/testdata/prom-vector-histogram-no-labels-frame.json vendored Normal file
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@@ -0,0 +1,70 @@
{
"frames": [
{
"schema": {
"meta": {
"type": "heatmap-cells-sparse"
},
"fields": [
{
"name": "xMax",
"type": "time",
"typeInfo": {
"frame": "time.Time"
}
},
{
"name": "yMin",
"type": "number",
"typeInfo": {
"frame": "float64"
},
"labels": {
}
},
{
"name": "yMax",
"type": "number",
"typeInfo": {
"frame": "float64"
}
},
{
"name": "count",
"type": "number",
"typeInfo": {
"frame": "float64"
}
},
{
"name": "yLayout",
"type": "number",
"typeInfo": {
"frame": "int8"
}
}
]
},
"data": {
"values": [
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],
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]
]
}
}
]
}

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pkg/util/converter/testdata/prom-vector-histogram-no-labels-golden.txt vendored Normal file
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pkg/util/converter/testdata/prom-vector-histogram-no-labels.json vendored Normal file
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@@ -0,0 +1,824 @@
{
"status": "success",
"data": {
"resultType": "vector",
"result": [
{
"metric": {},
"histogram": [
1649967668.042,
{
"count": "316.47719298245624",
"sum": "3.3474505904112015",
"buckets": [
[
0,
"0.000004536465129862675",
"0.000004947050303081549",
"0.13333333333333333"
],
[
0,
"0.000004947050303081549",
"0.000005394796609394436",
"2.0982456140350876"
],
[
0,
"0.000005394796609394436",
"0.000005883067418700946",
"4.224561403508771"
],
[
0,
"0.000005883067418700946",
"0.000006415530511884418",
"4.101754385964911"
],
[
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}
}

30
public/app/plugins/panel/heatmap-new/fields.ts
View File

@@ -84,8 +84,16 @@ export function prepareHeatmapData(data: PanelData, options: PanelOptions, theme
};
}
let first = frames[0];
if (first.meta?.type === DataFrameType.HeatmapSparse) {
return getSparseHeatmapData(first, exemplars, theme);
}
if (source === HeatmapSourceMode.Data) {
return getHeatmapData(bucketsToScanlines(frames[0]), exemplars, theme);
if (first.meta?.type !== DataFrameType.HeatmapScanlines) {
first = bucketsToScanlines(frames[0]);
}
return getHeatmapData(first, exemplars, theme);
}
// TODO, check for error etc
@@ -152,6 +160,26 @@ export const getExemplarsMapping = (heatmapData: HeatmapData, rawData: DataFrame
return mapping;
};
const getSparseHeatmapData = (
frame: DataFrame,
exemplars: DataFrame | undefined,
theme: GrafanaTheme2
): HeatmapData => {
if (frame.meta?.type !== DataFrameType.HeatmapSparse) {
return {
warning: 'Expected sparse heatmap format',
heatmap: frame,
};
}
const disp = frame.fields[3].display ?? getValueFormat('short');
return {
heatmap: frame,
exemplars,
display: (v) => formattedValueToString(disp(v)),
};
};
const getHeatmapData = (frame: DataFrame, exemplars: DataFrame | undefined, theme: GrafanaTheme2): HeatmapData => {
if (frame.meta?.type !== DataFrameType.HeatmapScanlines) {
return {