mirror of https://github.com/grafana/grafana
prometheushacktoberfestmetricsmonitoringalertinggrafanagoinfluxdbmysqlpostgresanalyticsdata-visualizationdashboardbusiness-intelligenceelasticsearch
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
1074 lines
34 KiB
1074 lines
34 KiB
import {
|
|
cacheFieldDisplayNames,
|
|
createDataFrame,
|
|
DataQueryRequest,
|
|
DataQueryResponse,
|
|
FieldType,
|
|
PreferredVisualisationType,
|
|
} from '@grafana/data';
|
|
|
|
import { parseSampleValue, sortSeriesByLabel, transformDFToTable, transformV2 } from './result_transformer';
|
|
import { PromQuery } from './types';
|
|
|
|
jest.mock('@grafana/runtime', () => ({
|
|
getTemplateSrv: () => ({
|
|
replace: (str: string) => str,
|
|
}),
|
|
getDataSourceSrv: () => {
|
|
return {
|
|
getInstanceSettings: (uid: string) => {
|
|
const uids = ['Tempo', 'jaeger'];
|
|
return uids.find((u) => u === uid) ? { name: uid } : undefined;
|
|
},
|
|
};
|
|
},
|
|
config: {
|
|
featureToggles: {
|
|
prometheusDataplane: true,
|
|
},
|
|
},
|
|
}));
|
|
|
|
describe('Prometheus Result Transformer', () => {
|
|
describe('parse variants of "+Inf" and "-Inf" strings', () => {
|
|
it('+Inf', () => {
|
|
expect(parseSampleValue('+Inf')).toEqual(Number.POSITIVE_INFINITY);
|
|
});
|
|
it('Inf', () => {
|
|
expect(parseSampleValue('Inf')).toEqual(Number.POSITIVE_INFINITY);
|
|
});
|
|
it('inf', () => {
|
|
expect(parseSampleValue('inf')).toEqual(Number.POSITIVE_INFINITY);
|
|
});
|
|
it('+Infinity', () => {
|
|
expect(parseSampleValue('+Infinity')).toEqual(Number.POSITIVE_INFINITY);
|
|
});
|
|
it('+infinity', () => {
|
|
expect(parseSampleValue('+infinity')).toEqual(Number.POSITIVE_INFINITY);
|
|
});
|
|
it('infinity', () => {
|
|
expect(parseSampleValue('infinity')).toEqual(Number.POSITIVE_INFINITY);
|
|
});
|
|
|
|
it('-Inf', () => {
|
|
expect(parseSampleValue('-Inf')).toEqual(Number.NEGATIVE_INFINITY);
|
|
});
|
|
|
|
it('-inf', () => {
|
|
expect(parseSampleValue('-inf')).toEqual(Number.NEGATIVE_INFINITY);
|
|
});
|
|
|
|
it('-Infinity', () => {
|
|
expect(parseSampleValue('-Infinity')).toEqual(Number.NEGATIVE_INFINITY);
|
|
});
|
|
|
|
it('-infinity', () => {
|
|
expect(parseSampleValue('-infinity')).toEqual(Number.NEGATIVE_INFINITY);
|
|
});
|
|
});
|
|
|
|
describe('sortSeriesByLabel() should use frame.fields[1].state?.displayName when available', () => {
|
|
let frames = [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [1, 2, 3] },
|
|
{
|
|
type: FieldType.number,
|
|
values: [4, 5, 6],
|
|
config: {
|
|
displayNameFromDS: '2',
|
|
},
|
|
labels: {
|
|
offset_days: '2',
|
|
},
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [1, 2, 3] },
|
|
{
|
|
type: FieldType.number,
|
|
values: [7, 8, 9],
|
|
config: {
|
|
displayNameFromDS: '1',
|
|
},
|
|
labels: {
|
|
offset_days: '1',
|
|
},
|
|
},
|
|
],
|
|
}),
|
|
];
|
|
|
|
it('sorts by displayNameFromDS', () => {
|
|
cacheFieldDisplayNames(frames);
|
|
|
|
let sorted = frames.slice().sort(sortSeriesByLabel);
|
|
|
|
expect(sorted[0]).toEqual(frames[1]);
|
|
expect(sorted[1]).toEqual(frames[0]);
|
|
});
|
|
});
|
|
|
|
describe('transformV2', () => {
|
|
it('results with time_series format should be enriched with preferredVisualisationType', () => {
|
|
const request = {
|
|
targets: [
|
|
{
|
|
format: 'time_series',
|
|
refId: 'A',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
{
|
|
fields: [],
|
|
length: 2,
|
|
name: 'ALERTS',
|
|
refId: 'A',
|
|
},
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
const series = transformV2(response, request, {});
|
|
expect(series).toEqual({
|
|
data: [{ fields: [], length: 2, meta: { preferredVisualisationType: 'graph' }, name: 'ALERTS', refId: 'A' }],
|
|
state: 'Done',
|
|
});
|
|
});
|
|
|
|
it('dataplane handling, adds displayNameFromDs from calculateFieldDisplayName() when __name__ is the field name when legendFormat is auto', () => {
|
|
const request = {
|
|
targets: [
|
|
{
|
|
format: 'time_series',
|
|
refId: 'A',
|
|
legendFormat: '__auto',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
{
|
|
fields: [
|
|
{
|
|
name: 'Time',
|
|
type: 'time',
|
|
values: [1],
|
|
typeInfo: { frame: 'time.Time' },
|
|
},
|
|
{
|
|
name: 'up',
|
|
labels: { __name__: 'up' },
|
|
config: {},
|
|
values: [1],
|
|
},
|
|
],
|
|
length: 1,
|
|
refId: 'A',
|
|
meta: {
|
|
type: 'timeseries-multi',
|
|
typeVersion: [0, 1],
|
|
},
|
|
},
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
const series = transformV2(response, request, {});
|
|
expect(series).toEqual({
|
|
data: [
|
|
{
|
|
fields: [
|
|
{
|
|
name: 'Time',
|
|
type: 'time',
|
|
values: [1],
|
|
typeInfo: { frame: 'time.Time' },
|
|
},
|
|
{
|
|
config: { displayNameFromDS: 'up' },
|
|
labels: { __name__: 'up' },
|
|
name: 'up',
|
|
values: [1],
|
|
},
|
|
],
|
|
length: 1,
|
|
meta: {
|
|
type: 'timeseries-multi',
|
|
typeVersion: [0, 1],
|
|
preferredVisualisationType: 'graph',
|
|
},
|
|
refId: 'A',
|
|
},
|
|
],
|
|
state: 'Done',
|
|
});
|
|
});
|
|
|
|
it('results with table format should be transformed to table dataFrames', () => {
|
|
const request = {
|
|
targets: [
|
|
{
|
|
format: 'table',
|
|
refId: 'A',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [6, 5, 4],
|
|
labels: { label1: 'value1', label2: 'value2' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
const series = transformV2(response, request, {});
|
|
|
|
expect(series.data[0].fields[0].name).toEqual('Time');
|
|
expect(series.data[0].fields[1].name).toEqual('label1');
|
|
expect(series.data[0].fields[2].name).toEqual('label2');
|
|
expect(series.data[0].fields[3].name).toEqual('Value');
|
|
expect(series.data[0].meta?.preferredVisualisationType).toEqual('rawPrometheus');
|
|
});
|
|
|
|
it('results with table format and multiple data frames should be transformed to 1 table dataFrame', () => {
|
|
const request = {
|
|
targets: [
|
|
{
|
|
format: 'table',
|
|
refId: 'A',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [6, 5, 4],
|
|
labels: { label1: 'value1', label2: 'value2' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [2, 3, 7] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [2, 3, 7],
|
|
labels: { label3: 'value3', label4: 'value4' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
const series = transformV2(response, request, {});
|
|
|
|
expect(series.data.length).toEqual(1);
|
|
expect(series.data[0].fields[0].name).toEqual('Time');
|
|
expect(series.data[0].fields[1].name).toEqual('label1');
|
|
expect(series.data[0].fields[2].name).toEqual('label2');
|
|
expect(series.data[0].fields[3].name).toEqual('label3');
|
|
expect(series.data[0].fields[4].name).toEqual('label4');
|
|
expect(series.data[0].fields[5].name).toEqual('Value');
|
|
expect(series.data[0].meta?.preferredVisualisationType).toEqual('rawPrometheus' as PreferredVisualisationType);
|
|
});
|
|
|
|
it('results with table and time_series format should be correctly transformed', () => {
|
|
const options = {
|
|
targets: [
|
|
{
|
|
format: 'table',
|
|
refId: 'A',
|
|
},
|
|
{
|
|
format: 'time_series',
|
|
refId: 'B',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [6, 5, 4],
|
|
labels: { label1: 'value1', label2: 'value2' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'B',
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [6, 5, 4],
|
|
labels: { label1: 'value1', label2: 'value2' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
const series = transformV2(response, options, {});
|
|
expect(series.data[0].fields.length).toEqual(2);
|
|
expect(series.data[0].meta?.preferredVisualisationType).toEqual('graph');
|
|
expect(series.data[1].fields.length).toEqual(4);
|
|
expect(series.data[1].meta?.preferredVisualisationType).toEqual('rawPrometheus' as PreferredVisualisationType);
|
|
});
|
|
|
|
// Heatmap frames can either have a name of the metric, or if there is no metric, a name of "Value"
|
|
it('results with heatmap format (no metric name) should be correctly transformed', () => {
|
|
const options = {
|
|
targets: [
|
|
{
|
|
format: 'heatmap',
|
|
refId: 'A',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [30, 10, 40],
|
|
labels: { le: '+Inf' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [20, 10, 30],
|
|
labels: { le: '2' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
|
|
const series = transformV2(response, options, {});
|
|
expect(series.data[0].fields.length).toEqual(4);
|
|
expect(series.data[0].fields[1].values).toEqual([10, 10, 0]);
|
|
expect(series.data[0].fields[2].values).toEqual([10, 0, 30]);
|
|
expect(series.data[0].fields[3].values).toEqual([10, 0, 10]);
|
|
expect(series.data[0].fields[1].name).toEqual('1');
|
|
expect(series.data[0].fields[2].name).toEqual('2');
|
|
expect(series.data[0].fields[3].name).toEqual('+Inf');
|
|
});
|
|
it('results with heatmap format (with metric name) should be correctly transformed', () => {
|
|
const options = {
|
|
targets: [
|
|
{
|
|
format: 'heatmap',
|
|
refId: 'A',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'metric_name',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1', __name__: 'metric_name' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'metric_name',
|
|
type: FieldType.number,
|
|
values: [30, 10, 40],
|
|
labels: { le: '+Inf', __name__: 'metric_name' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'metric_name',
|
|
type: FieldType.number,
|
|
values: [20, 10, 30],
|
|
labels: { le: '2', __name__: 'metric_name' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
|
|
const series = transformV2(response, options, {});
|
|
expect(series.data[0].fields.length).toEqual(4);
|
|
expect(series.data[0].fields[1].values).toEqual([10, 10, 0]);
|
|
expect(series.data[0].fields[2].values).toEqual([10, 0, 30]);
|
|
expect(series.data[0].fields[3].values).toEqual([10, 0, 10]);
|
|
expect(series.data[0].fields[1].name).toEqual('1');
|
|
expect(series.data[0].fields[2].name).toEqual('2');
|
|
expect(series.data[0].fields[3].name).toEqual('+Inf');
|
|
});
|
|
|
|
it('results with heatmap format (no metric name) from multiple queries should be correctly transformed', () => {
|
|
const options = {
|
|
targets: [
|
|
{
|
|
format: 'heatmap',
|
|
refId: 'A',
|
|
},
|
|
{
|
|
format: 'heatmap',
|
|
refId: 'B',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [20, 10, 30],
|
|
labels: { le: '2' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [30, 10, 40],
|
|
labels: { le: '+Inf' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'B',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'B',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [20, 10, 30],
|
|
labels: { le: '2' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'B',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [30, 10, 40],
|
|
labels: { le: '+Inf' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
|
|
const series = transformV2(response, options, {});
|
|
expect(series.data[0].fields.length).toEqual(4);
|
|
expect(series.data[0].fields[1].values).toEqual([10, 10, 0]);
|
|
expect(series.data[0].fields[2].values).toEqual([10, 0, 30]);
|
|
expect(series.data[0].fields[3].values).toEqual([10, 0, 10]);
|
|
});
|
|
it('results with heatmap format (with metric name) from multiple queries should be correctly transformed', () => {
|
|
const options = {
|
|
targets: [
|
|
{
|
|
format: 'heatmap',
|
|
refId: 'A',
|
|
},
|
|
{
|
|
format: 'heatmap',
|
|
refId: 'B',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'metric_name',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1', __name__: 'metric_name' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'metric_name',
|
|
type: FieldType.number,
|
|
values: [20, 10, 30],
|
|
labels: { le: '2', __name__: 'metric_name' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'metric_name',
|
|
type: FieldType.number,
|
|
values: [30, 10, 40],
|
|
labels: { le: '+Inf', __name__: 'metric_name' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'B',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'metric_name',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1', __name__: 'metric_name' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'B',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'metric_name',
|
|
type: FieldType.number,
|
|
values: [20, 10, 30],
|
|
labels: { le: '2', __name__: 'metric_name' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'B',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'metric_name',
|
|
type: FieldType.number,
|
|
values: [30, 10, 40],
|
|
labels: { le: '+Inf', __name__: 'metric_name' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
|
|
const series = transformV2(response, options, {});
|
|
expect(series.data[0].fields.length).toEqual(4);
|
|
expect(series.data[0].fields[1].values).toEqual([10, 10, 0]);
|
|
expect(series.data[0].fields[2].values).toEqual([10, 0, 30]);
|
|
expect(series.data[0].fields[3].values).toEqual([10, 0, 10]);
|
|
});
|
|
|
|
it('results with heatmap format and multiple histograms should be grouped and de-accumulated by non-le labels', () => {
|
|
const options = {
|
|
targets: [
|
|
{
|
|
format: 'heatmap',
|
|
refId: 'A',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
// 10
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1', additionalProperty: '10' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [20, 10, 30],
|
|
labels: { le: '2', additionalProperty: '10' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [30, 10, 40],
|
|
labels: { le: '+Inf', additionalProperty: '10' },
|
|
},
|
|
],
|
|
}),
|
|
// 20
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [0, 10, 10],
|
|
labels: { le: '1', additionalProperty: '20' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [20, 10, 40],
|
|
labels: { le: '2', additionalProperty: '20' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [30, 10, 60],
|
|
labels: { le: '+Inf', additionalProperty: '20' },
|
|
},
|
|
],
|
|
}),
|
|
// 30
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [30, 30, 60],
|
|
labels: { le: '1', additionalProperty: '30' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [30, 40, 60],
|
|
labels: { le: '2', additionalProperty: '30' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [40, 40, 60],
|
|
labels: { le: '+Inf', additionalProperty: '30' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
|
|
const series = transformV2(response, options, {});
|
|
expect(series.data[0].fields.length).toEqual(4);
|
|
expect(series.data[0].fields[1].values).toEqual([10, 10, 0]);
|
|
expect(series.data[0].fields[2].values).toEqual([10, 0, 30]);
|
|
expect(series.data[0].fields[3].values).toEqual([10, 0, 10]);
|
|
|
|
expect(series.data[1].fields[1].values).toEqual([0, 10, 10]);
|
|
expect(series.data[1].fields[2].values).toEqual([20, 0, 30]);
|
|
expect(series.data[1].fields[3].values).toEqual([10, 0, 20]);
|
|
|
|
expect(series.data[2].fields[1].values).toEqual([30, 30, 60]);
|
|
expect(series.data[2].fields[2].values).toEqual([0, 10, 0]);
|
|
expect(series.data[2].fields[3].values).toEqual([10, 0, 0]);
|
|
});
|
|
|
|
it('Retains exemplar frames when data returned is a heatmap', () => {
|
|
const options = {
|
|
targets: [
|
|
{
|
|
format: 'heatmap',
|
|
refId: 'A',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
name: 'exemplar',
|
|
meta: {
|
|
custom: {
|
|
resultType: 'exemplar',
|
|
},
|
|
},
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4, 3, 2, 1] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [30, 10, 40, 90, 14, 21],
|
|
labels: { le: '6' },
|
|
},
|
|
{
|
|
name: 'Test',
|
|
type: FieldType.string,
|
|
values: ['hello', 'doctor', 'name', 'continue', 'yesterday', 'tomorrow'],
|
|
labels: { le: '6' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
|
|
const series = transformV2(response, options, {});
|
|
expect(series.data[0].fields.length).toEqual(2);
|
|
expect(series.data.length).toEqual(2);
|
|
expect(series.data[1].fields[2].values).toEqual(['hello', 'doctor', 'name', 'continue', 'yesterday', 'tomorrow']);
|
|
expect(series.data[1].fields.length).toEqual(3);
|
|
});
|
|
|
|
it('should not add a link with an error when exemplarTraceIdDestinations is not configured properly', () => {
|
|
const response = {
|
|
state: 'Done',
|
|
data: [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1' },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'A',
|
|
name: 'exemplar',
|
|
meta: {
|
|
custom: {
|
|
resultType: 'exemplar',
|
|
},
|
|
},
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4, 3, 2, 1] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [30, 10, 40, 90, 14, 21],
|
|
labels: { le: '6' },
|
|
},
|
|
{
|
|
name: 'traceID',
|
|
type: FieldType.string,
|
|
values: ['unknown'],
|
|
labels: { le: '6' },
|
|
},
|
|
],
|
|
}),
|
|
],
|
|
} as unknown as DataQueryResponse;
|
|
const request = {
|
|
targets: [
|
|
{
|
|
format: 'heatmap',
|
|
refId: 'A',
|
|
},
|
|
],
|
|
} as unknown as DataQueryRequest<PromQuery>;
|
|
const testOptions: any = {
|
|
exemplarTraceIdDestinations: [
|
|
{
|
|
name: 'traceID',
|
|
datasourceUid: 'unknown',
|
|
},
|
|
],
|
|
};
|
|
|
|
const series = transformV2(response, request, testOptions);
|
|
expect(series.data[1].fields.length).toEqual(3);
|
|
expect(series.data[1].name).toEqual('exemplar');
|
|
const traceField = series.data[1].fields.find((f) => f.name === 'traceID');
|
|
expect(traceField).toBeDefined();
|
|
expect(traceField!.config.links?.length).toBe(0);
|
|
});
|
|
});
|
|
|
|
describe('transformDFToTable', () => {
|
|
it('transforms dataFrame with response length 1 to table dataFrame', () => {
|
|
const df = createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [6, 5, 4],
|
|
labels: { label1: 'value1', label2: 'value2' },
|
|
},
|
|
],
|
|
});
|
|
|
|
const tableDf = transformDFToTable([df])[0];
|
|
expect(tableDf.fields.length).toBe(4);
|
|
expect(tableDf.fields[0].name).toBe('Time');
|
|
expect(tableDf.fields[1].name).toBe('label1');
|
|
expect(tableDf.fields[1].values[0]).toBe('value1');
|
|
expect(tableDf.fields[2].name).toBe('label2');
|
|
expect(tableDf.fields[2].values[0]).toBe('value2');
|
|
expect(tableDf.fields[3].name).toBe('Value');
|
|
});
|
|
|
|
it('transforms dataFrame with response length 2 to table dataFrame', () => {
|
|
const df = createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [6, 5, 4],
|
|
labels: { label1: 'value1', label2: 'value2' },
|
|
},
|
|
],
|
|
});
|
|
|
|
const tableDf = transformDFToTable([df])[0];
|
|
expect(tableDf.fields.length).toBe(4);
|
|
expect(tableDf.fields[0].name).toBe('Time');
|
|
expect(tableDf.fields[1].name).toBe('label1');
|
|
expect(tableDf.fields[1].values[0]).toBe('value1');
|
|
expect(tableDf.fields[2].name).toBe('label2');
|
|
expect(tableDf.fields[2].values[0]).toBe('value2');
|
|
expect(tableDf.fields[3].name).toBe('Value');
|
|
});
|
|
|
|
// Queries do not always return results
|
|
it('transforms dataFrame and empty dataFrame mock responses to table dataFrames', () => {
|
|
const value1 = 'value1';
|
|
const value2 = 'value2';
|
|
|
|
const dataframes = [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [6, 5, 4],
|
|
labels: { label1: value1, label2: value2 },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'B',
|
|
fields: [],
|
|
}),
|
|
];
|
|
|
|
const transformedTableDataFrames = transformDFToTable(dataframes);
|
|
// Expect the first query to still return valid results
|
|
expect(transformedTableDataFrames[0].fields.length).toBe(4);
|
|
expect(transformedTableDataFrames[0].fields[0].name).toBe('Time');
|
|
expect(transformedTableDataFrames[0].fields[1].name).toBe('label1');
|
|
expect(transformedTableDataFrames[0].fields[1].values[0]).toBe(value1);
|
|
expect(transformedTableDataFrames[0].fields[2].name).toBe('label2');
|
|
expect(transformedTableDataFrames[0].fields[2].values[0]).toBe(value2);
|
|
expect(transformedTableDataFrames[0].fields[3].name).toBe('Value #A');
|
|
|
|
// Expect the invalid/empty results not to throw an error and to return empty arrays
|
|
expect(transformedTableDataFrames[1].fields[1].labels).toBe(undefined);
|
|
expect(transformedTableDataFrames[1].fields[1].name).toBe('Value #B');
|
|
expect(transformedTableDataFrames[1].fields[1].values).toEqual([]);
|
|
expect(transformedTableDataFrames[1].fields[0].values).toEqual([]);
|
|
});
|
|
|
|
it('transforms dataframes with metadata resolving from their refIds', () => {
|
|
const value1 = 'value1';
|
|
const value2 = 'value2';
|
|
const executedQueryForRefA = 'Expr: avg_over_time(access_evaluation_duration_bucket[15s])\nStep: 15s';
|
|
const executedQueryForRefB = 'Expr: avg_over_time(access_evaluation_duration_bucket[5m])\nStep: 15s';
|
|
|
|
const dataframes = [
|
|
createDataFrame({
|
|
refId: 'A',
|
|
meta: {
|
|
typeVersion: [0, 1],
|
|
custom: {
|
|
resultType: 'vector',
|
|
},
|
|
executedQueryString: executedQueryForRefA,
|
|
},
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [6, 5, 4],
|
|
labels: { label1: value1, label2: value2 },
|
|
},
|
|
],
|
|
}),
|
|
createDataFrame({
|
|
refId: 'B',
|
|
meta: {
|
|
typeVersion: [0, 1],
|
|
custom: {
|
|
resultType: 'vector',
|
|
},
|
|
executedQueryString: executedQueryForRefB,
|
|
},
|
|
fields: [
|
|
{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'value',
|
|
type: FieldType.number,
|
|
values: [6, 5, 4],
|
|
labels: { label1: value1, label2: value2 },
|
|
},
|
|
],
|
|
}),
|
|
];
|
|
|
|
const transformedTableDataFrames = transformDFToTable(dataframes);
|
|
expect(transformedTableDataFrames[0].meta).toBeTruthy();
|
|
expect(transformedTableDataFrames[1].meta).toBeTruthy();
|
|
expect(transformedTableDataFrames[0].meta?.executedQueryString).toEqual(executedQueryForRefA);
|
|
expect(transformedTableDataFrames[1].meta?.executedQueryString).toEqual(executedQueryForRefB);
|
|
});
|
|
});
|
|
});
|
|
|