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* fix bug in prometheus table view which is throwing error when a query returns no results
1345 lines
42 KiB
TypeScript
1345 lines
42 KiB
TypeScript
import {
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DataFrame,
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DataQueryRequest,
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DataQueryResponse,
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FieldType,
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MutableDataFrame,
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PreferredVisualisationType,
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} from '@grafana/data';
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import { parseSampleValue, transform, transformDFToTable, transformV2 } from './result_transformer';
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import { PromQuery } from './types';
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jest.mock('@grafana/runtime', () => ({
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getTemplateSrv: () => ({
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replace: (str: string) => str,
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}),
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getDataSourceSrv: () => {
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return {
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getInstanceSettings: (uid: string) => {
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const uids = ['Tempo', 'jaeger'];
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return uids.find((u) => u === uid) ? { name: uid } : undefined;
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},
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};
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},
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}));
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const matrixResponse = {
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status: 'success',
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data: {
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resultType: 'matrix',
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result: [
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{
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metric: { __name__: 'test', job: 'testjob' },
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values: [
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[1, '10'],
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[2, '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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describe('Prometheus Result Transformer', () => {
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describe('parse variants of "+Inf" and "-Inf" strings', () => {
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it('+Inf', () => {
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expect(parseSampleValue('+Inf')).toEqual(Number.POSITIVE_INFINITY);
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});
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it('Inf', () => {
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expect(parseSampleValue('Inf')).toEqual(Number.POSITIVE_INFINITY);
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});
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it('inf', () => {
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expect(parseSampleValue('inf')).toEqual(Number.POSITIVE_INFINITY);
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});
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it('+Infinity', () => {
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expect(parseSampleValue('+Infinity')).toEqual(Number.POSITIVE_INFINITY);
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});
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it('+infinity', () => {
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expect(parseSampleValue('+infinity')).toEqual(Number.POSITIVE_INFINITY);
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});
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it('infinity', () => {
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expect(parseSampleValue('infinity')).toEqual(Number.POSITIVE_INFINITY);
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});
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it('-Inf', () => {
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expect(parseSampleValue('-Inf')).toEqual(Number.NEGATIVE_INFINITY);
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});
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it('-inf', () => {
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expect(parseSampleValue('-inf')).toEqual(Number.NEGATIVE_INFINITY);
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});
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it('-Infinity', () => {
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expect(parseSampleValue('-Infinity')).toEqual(Number.NEGATIVE_INFINITY);
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});
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it('-infinity', () => {
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expect(parseSampleValue('-infinity')).toEqual(Number.NEGATIVE_INFINITY);
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});
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});
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describe('transformV2', () => {
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it('results with time_series format should be enriched with preferredVisualisationType', () => {
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const request = {
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targets: [
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{
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format: 'time_series',
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refId: 'A',
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},
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],
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} as unknown as DataQueryRequest<PromQuery>;
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const response = {
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state: 'Done',
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data: [
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{
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fields: [],
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length: 2,
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name: 'ALERTS',
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refId: 'A',
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},
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],
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} as unknown as DataQueryResponse;
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const series = transformV2(response, request, {});
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expect(series).toEqual({
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data: [{ fields: [], length: 2, meta: { preferredVisualisationType: 'graph' }, name: 'ALERTS', refId: 'A' }],
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state: 'Done',
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});
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});
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it('results with table format should be transformed to table dataFrames', () => {
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const request = {
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targets: [
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{
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format: 'table',
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refId: 'A',
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},
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],
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} as unknown as DataQueryRequest<PromQuery>;
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const response = {
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state: 'Done',
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data: [
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'value',
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type: FieldType.number,
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values: [6, 5, 4],
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labels: { label1: 'value1', label2: 'value2' },
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},
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],
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}),
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],
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} as unknown as DataQueryResponse;
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const series = transformV2(response, request, {});
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expect(series.data[0].fields[0].name).toEqual('Time');
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expect(series.data[0].fields[1].name).toEqual('label1');
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expect(series.data[0].fields[2].name).toEqual('label2');
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expect(series.data[0].fields[3].name).toEqual('Value');
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expect(series.data[0].meta?.preferredVisualisationType).toEqual('rawPrometheus');
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});
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it('results with table format and multiple data frames should be transformed to 1 table dataFrame', () => {
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const request = {
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targets: [
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{
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format: 'table',
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refId: 'A',
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},
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],
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} as unknown as DataQueryRequest<PromQuery>;
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const response = {
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state: 'Done',
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data: [
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'value',
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type: FieldType.number,
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values: [6, 5, 4],
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labels: { label1: 'value1', label2: 'value2' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'time', type: FieldType.time, values: [2, 3, 7] },
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{
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name: 'value',
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type: FieldType.number,
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values: [2, 3, 7],
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labels: { label3: 'value3', label4: 'value4' },
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},
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],
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}),
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],
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} as unknown as DataQueryResponse;
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const series = transformV2(response, request, {});
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expect(series.data.length).toEqual(1);
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expect(series.data[0].fields[0].name).toEqual('Time');
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expect(series.data[0].fields[1].name).toEqual('label1');
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expect(series.data[0].fields[2].name).toEqual('label2');
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expect(series.data[0].fields[3].name).toEqual('label3');
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expect(series.data[0].fields[4].name).toEqual('label4');
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expect(series.data[0].fields[5].name).toEqual('Value');
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expect(series.data[0].meta?.preferredVisualisationType).toEqual('rawPrometheus' as PreferredVisualisationType);
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});
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it('results with table and time_series format should be correctly transformed', () => {
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const options = {
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targets: [
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{
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format: 'table',
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refId: 'A',
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},
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{
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format: 'time_series',
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refId: 'B',
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},
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],
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} as unknown as DataQueryRequest<PromQuery>;
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const response = {
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state: 'Done',
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data: [
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'value',
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type: FieldType.number,
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values: [6, 5, 4],
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labels: { label1: 'value1', label2: 'value2' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'B',
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fields: [
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{ name: 'time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'value',
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type: FieldType.number,
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values: [6, 5, 4],
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labels: { label1: 'value1', label2: 'value2' },
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},
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],
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}),
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],
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} as unknown as DataQueryResponse;
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const series = transformV2(response, options, {});
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expect(series.data[0].fields.length).toEqual(2);
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expect(series.data[0].meta?.preferredVisualisationType).toEqual('graph');
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expect(series.data[1].fields.length).toEqual(4);
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expect(series.data[1].meta?.preferredVisualisationType).toEqual('rawPrometheus' as PreferredVisualisationType);
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});
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it('results with heatmap format should be correctly transformed', () => {
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const options = {
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targets: [
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{
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format: 'heatmap',
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refId: 'A',
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},
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],
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} as unknown as DataQueryRequest<PromQuery>;
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const response = {
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state: 'Done',
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data: [
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [10, 10, 0],
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labels: { le: '1' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [30, 10, 40],
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labels: { le: '+Inf' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [20, 10, 30],
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labels: { le: '2' },
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},
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],
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}),
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],
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} as unknown as DataQueryResponse;
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const series = transformV2(response, options, {});
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expect(series.data[0].fields.length).toEqual(4);
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expect(series.data[0].fields[1].values.toArray()).toEqual([10, 10, 0]);
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expect(series.data[0].fields[2].values.toArray()).toEqual([10, 0, 30]);
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expect(series.data[0].fields[3].values.toArray()).toEqual([10, 0, 10]);
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expect(series.data[0].fields[1].name).toEqual('1');
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expect(series.data[0].fields[2].name).toEqual('2');
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expect(series.data[0].fields[3].name).toEqual('+Inf');
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});
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it('results with heatmap format from multiple queries should be correctly transformed', () => {
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const options = {
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targets: [
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{
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format: 'heatmap',
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refId: 'A',
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},
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{
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format: 'heatmap',
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refId: 'B',
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},
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],
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} as unknown as DataQueryRequest<PromQuery>;
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const response = {
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state: 'Done',
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data: [
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [10, 10, 0],
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labels: { le: '1' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [20, 10, 30],
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labels: { le: '2' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [30, 10, 40],
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labels: { le: '+Inf' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'B',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [10, 10, 0],
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labels: { le: '1' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'B',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [20, 10, 30],
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labels: { le: '2' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'B',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [30, 10, 40],
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labels: { le: '+Inf' },
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},
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],
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}),
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],
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} as unknown as DataQueryResponse;
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const series = transformV2(response, options, {});
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expect(series.data[0].fields.length).toEqual(4);
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expect(series.data[0].fields[1].values.toArray()).toEqual([10, 10, 0]);
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expect(series.data[0].fields[2].values.toArray()).toEqual([10, 0, 30]);
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expect(series.data[0].fields[3].values.toArray()).toEqual([10, 0, 10]);
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});
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it('results with heatmap format and multiple histograms should be grouped and de-accumulated by non-le labels', () => {
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const options = {
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targets: [
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{
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format: 'heatmap',
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refId: 'A',
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},
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],
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} as unknown as DataQueryRequest<PromQuery>;
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const response = {
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state: 'Done',
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data: [
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// 10
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [10, 10, 0],
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labels: { le: '1', additionalProperty: '10' },
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},
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],
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}),
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
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{
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name: 'Value',
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type: FieldType.number,
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values: [20, 10, 30],
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labels: { le: '2', additionalProperty: '10' },
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},
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],
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}),
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new MutableDataFrame({
|
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refId: 'A',
|
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
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{
|
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name: 'Value',
|
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type: FieldType.number,
|
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values: [30, 10, 40],
|
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labels: { le: '+Inf', additionalProperty: '10' },
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},
|
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],
|
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}),
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// 20
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new MutableDataFrame({
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refId: 'A',
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fields: [
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
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name: 'Value',
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type: FieldType.number,
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values: [0, 10, 10],
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labels: { le: '1', additionalProperty: '20' },
|
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},
|
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],
|
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}),
|
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new MutableDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
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values: [20, 10, 40],
|
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labels: { le: '2', additionalProperty: '20' },
|
|
},
|
|
],
|
|
}),
|
|
new MutableDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
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values: [30, 10, 60],
|
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labels: { le: '+Inf', additionalProperty: '20' },
|
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},
|
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],
|
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}),
|
|
// 30
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new MutableDataFrame({
|
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refId: 'A',
|
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fields: [
|
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
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values: [30, 30, 60],
|
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labels: { le: '1', additionalProperty: '30' },
|
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},
|
|
],
|
|
}),
|
|
new MutableDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
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values: [30, 40, 60],
|
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labels: { le: '2', additionalProperty: '30' },
|
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},
|
|
],
|
|
}),
|
|
new MutableDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
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{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
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values: [40, 40, 60],
|
|
labels: { le: '+Inf', additionalProperty: '30' },
|
|
},
|
|
],
|
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}),
|
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],
|
|
} as unknown as DataQueryResponse;
|
|
|
|
const series = transformV2(response, options, {});
|
|
expect(series.data[0].fields.length).toEqual(4);
|
|
expect(series.data[0].fields[1].values.toArray()).toEqual([10, 10, 0]);
|
|
expect(series.data[0].fields[2].values.toArray()).toEqual([10, 0, 30]);
|
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expect(series.data[0].fields[3].values.toArray()).toEqual([10, 0, 10]);
|
|
|
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expect(series.data[1].fields[1].values.toArray()).toEqual([0, 10, 10]);
|
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expect(series.data[1].fields[2].values.toArray()).toEqual([20, 0, 30]);
|
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expect(series.data[1].fields[3].values.toArray()).toEqual([10, 0, 20]);
|
|
|
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expect(series.data[2].fields[1].values.toArray()).toEqual([30, 30, 60]);
|
|
expect(series.data[2].fields[2].values.toArray()).toEqual([0, 10, 0]);
|
|
expect(series.data[2].fields[3].values.toArray()).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: [
|
|
new MutableDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1' },
|
|
},
|
|
],
|
|
}),
|
|
new MutableDataFrame({
|
|
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.toArray()).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: [
|
|
new MutableDataFrame({
|
|
refId: 'A',
|
|
fields: [
|
|
{ name: 'Time', type: FieldType.time, values: [6, 5, 4] },
|
|
{
|
|
name: 'Value',
|
|
type: FieldType.number,
|
|
values: [10, 10, 0],
|
|
labels: { le: '1' },
|
|
},
|
|
],
|
|
}),
|
|
new MutableDataFrame({
|
|
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 = new MutableDataFrame({
|
|
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.get(0)).toBe('value1');
|
|
expect(tableDf.fields[2].name).toBe('label2');
|
|
expect(tableDf.fields[2].values.get(0)).toBe('value2');
|
|
expect(tableDf.fields[3].name).toBe('Value');
|
|
});
|
|
|
|
it('transforms dataFrame with response length 2 to table dataFrame', () => {
|
|
const df = new MutableDataFrame({
|
|
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.get(0)).toBe('value1');
|
|
expect(tableDf.fields[2].name).toBe('label2');
|
|
expect(tableDf.fields[2].values.get(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 = [
|
|
new MutableDataFrame({
|
|
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 },
|
|
},
|
|
],
|
|
}),
|
|
new MutableDataFrame({
|
|
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.get(0)).toBe(value1);
|
|
expect(transformedTableDataFrames[0].fields[2].name).toBe('label2');
|
|
expect(transformedTableDataFrames[0].fields[2].values.get(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.toArray()).toEqual([]);
|
|
expect(transformedTableDataFrames[1].fields[0].values.toArray()).toEqual([]);
|
|
});
|
|
});
|
|
|
|
describe('transform', () => {
|
|
const options: any = { target: {}, query: {} };
|
|
describe('When nothing is returned', () => {
|
|
it('should return empty array', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: '',
|
|
result: null,
|
|
},
|
|
};
|
|
const series = transform({ data: response } as any, options);
|
|
expect(series).toEqual([]);
|
|
});
|
|
it('should return empty array', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: '',
|
|
result: null,
|
|
},
|
|
};
|
|
const result = transform({ data: response } as any, { ...options, target: { format: 'table' } });
|
|
expect(result).toHaveLength(0);
|
|
});
|
|
});
|
|
|
|
describe('When resultFormat is table', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'matrix',
|
|
result: [
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob' },
|
|
values: [
|
|
[1443454528, '3846'],
|
|
[1443454530, '3848'],
|
|
],
|
|
},
|
|
{
|
|
metric: {
|
|
__name__: 'test2',
|
|
instance: 'localhost:8080',
|
|
job: 'otherjob',
|
|
},
|
|
values: [
|
|
[1443454529, '3847'],
|
|
[1443454531, '3849'],
|
|
],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
|
|
it('should return data frame', () => {
|
|
const result = transform({ data: response } as any, {
|
|
...options,
|
|
target: {
|
|
responseListLength: 0,
|
|
refId: 'A',
|
|
format: 'table',
|
|
},
|
|
});
|
|
expect(result[0].fields[0].values.toArray()).toEqual([
|
|
1443454528000, 1443454530000, 1443454529000, 1443454531000,
|
|
]);
|
|
expect(result[0].fields[0].name).toBe('Time');
|
|
expect(result[0].fields[0].type).toBe(FieldType.time);
|
|
expect(result[0].fields[1].values.toArray()).toEqual(['test', 'test', 'test2', 'test2']);
|
|
expect(result[0].fields[1].name).toBe('__name__');
|
|
expect(result[0].fields[1].config.filterable).toBe(true);
|
|
expect(result[0].fields[1].type).toBe(FieldType.string);
|
|
expect(result[0].fields[2].values.toArray()).toEqual(['', '', 'localhost:8080', 'localhost:8080']);
|
|
expect(result[0].fields[2].name).toBe('instance');
|
|
expect(result[0].fields[2].type).toBe(FieldType.string);
|
|
expect(result[0].fields[3].values.toArray()).toEqual(['testjob', 'testjob', 'otherjob', 'otherjob']);
|
|
expect(result[0].fields[3].name).toBe('job');
|
|
expect(result[0].fields[3].type).toBe(FieldType.string);
|
|
expect(result[0].fields[4].values.toArray()).toEqual([3846, 3848, 3847, 3849]);
|
|
expect(result[0].fields[4].name).toEqual('Value');
|
|
expect(result[0].fields[4].type).toBe(FieldType.number);
|
|
expect(result[0].refId).toBe('A');
|
|
});
|
|
|
|
it('should include refId if response count is more than 2', () => {
|
|
const result = transform({ data: response } as any, {
|
|
...options,
|
|
target: {
|
|
refId: 'B',
|
|
format: 'table',
|
|
},
|
|
responseListLength: 2,
|
|
});
|
|
|
|
expect(result[0].fields[4].name).toEqual('Value #B');
|
|
});
|
|
});
|
|
|
|
describe('When resultFormat is table and instant = true', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'vector',
|
|
result: [
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob' },
|
|
value: [1443454528, '3846'],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
|
|
it('should return data frame', () => {
|
|
const result = transform({ data: response } as any, { ...options, target: { format: 'table' } });
|
|
expect(result[0].fields[0].values.toArray()).toEqual([1443454528000]);
|
|
expect(result[0].fields[0].name).toBe('Time');
|
|
expect(result[0].fields[1].values.toArray()).toEqual(['test']);
|
|
expect(result[0].fields[1].name).toBe('__name__');
|
|
expect(result[0].fields[2].values.toArray()).toEqual(['testjob']);
|
|
expect(result[0].fields[2].name).toBe('job');
|
|
expect(result[0].fields[3].values.toArray()).toEqual([3846]);
|
|
expect(result[0].fields[3].name).toEqual('Value');
|
|
});
|
|
|
|
it('should return le label values parsed as numbers', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'vector',
|
|
result: [
|
|
{
|
|
metric: { le: '102' },
|
|
value: [1594908838, '0'],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
const result = transform({ data: response } as any, { ...options, target: { format: 'table' } });
|
|
expect(result[0].fields[1].values.toArray()).toEqual([102]);
|
|
expect(result[0].fields[1].type).toEqual(FieldType.number);
|
|
});
|
|
});
|
|
|
|
describe('When instant = true', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'vector',
|
|
result: [
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob' },
|
|
value: [1443454528, '3846'],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
|
|
it('should return data frame', () => {
|
|
const result: DataFrame[] = transform({ data: response } as any, { ...options, query: { instant: true } });
|
|
expect(result[0].name).toBe('test{job="testjob"}');
|
|
});
|
|
});
|
|
|
|
describe('When resultFormat is heatmap', () => {
|
|
const getResponse = (result: any) => ({
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'matrix',
|
|
result,
|
|
},
|
|
});
|
|
|
|
const options = {
|
|
format: 'heatmap',
|
|
start: 1445000010,
|
|
end: 1445000030,
|
|
legendFormat: '{{le}}',
|
|
};
|
|
|
|
it('should convert cumulative histogram to regular', () => {
|
|
const response = getResponse([
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob', le: '1' },
|
|
values: [
|
|
[1445000010, '10'],
|
|
[1445000020, '10'],
|
|
[1445000030, '0'],
|
|
],
|
|
},
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob', le: '2' },
|
|
values: [
|
|
[1445000010, '20'],
|
|
[1445000020, '10'],
|
|
[1445000030, '30'],
|
|
],
|
|
},
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob', le: '3' },
|
|
values: [
|
|
[1445000010, '30'],
|
|
[1445000020, '10'],
|
|
[1445000030, '40'],
|
|
],
|
|
},
|
|
]);
|
|
|
|
const result = transform({ data: response } as any, { query: options, target: options } as any);
|
|
expect(result[0].fields[0].values.toArray()).toEqual([1445000010000, 1445000020000, 1445000030000]);
|
|
expect(result[0].fields[1].values.toArray()).toEqual([10, 10, 0]);
|
|
expect(result[0].fields[2].values.toArray()).toEqual([10, 0, 30]);
|
|
expect(result[0].fields[3].values.toArray()).toEqual([10, 0, 10]);
|
|
});
|
|
|
|
it('should handle missing datapoints', () => {
|
|
const response = getResponse([
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob', le: '1' },
|
|
values: [
|
|
[1445000010, '1'],
|
|
[1445000020, '2'],
|
|
],
|
|
},
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob', le: '2' },
|
|
values: [
|
|
[1445000010, '2'],
|
|
[1445000020, '5'],
|
|
[1445000030, '1'],
|
|
],
|
|
},
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob', le: '3' },
|
|
values: [
|
|
[1445000010, '3'],
|
|
[1445000020, '7'],
|
|
],
|
|
},
|
|
]);
|
|
const result = transform({ data: response } as any, { query: options, target: options } as any);
|
|
expect(result[0].fields[1].values.toArray()).toEqual([1, 2]);
|
|
expect(result[0].fields[2].values.toArray()).toEqual([1, 3, 1]);
|
|
expect(result[0].fields[3].values.toArray()).toEqual([1, 2]);
|
|
});
|
|
});
|
|
|
|
describe('When the response is a matrix', () => {
|
|
it('should have labels with the value field', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'matrix',
|
|
result: [
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob', instance: 'testinstance' },
|
|
values: [
|
|
[0, '10'],
|
|
[1, '10'],
|
|
[2, '0'],
|
|
],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
|
|
const result: DataFrame[] = transform({ data: response } as any, {
|
|
...options,
|
|
});
|
|
|
|
expect(result[0].fields[1].labels).toBeDefined();
|
|
expect(result[0].fields[1].labels?.instance).toBe('testinstance');
|
|
expect(result[0].fields[1].labels?.job).toBe('testjob');
|
|
});
|
|
|
|
it('should transform into a data frame', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'matrix',
|
|
result: [
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob' },
|
|
values: [
|
|
[0, '10'],
|
|
[1, '10'],
|
|
[2, '0'],
|
|
],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
|
|
const result: DataFrame[] = transform({ data: response } as any, {
|
|
...options,
|
|
query: {
|
|
start: 0,
|
|
end: 2,
|
|
},
|
|
});
|
|
expect(result[0].fields[0].values.toArray()).toEqual([0, 1000, 2000]);
|
|
expect(result[0].fields[1].values.toArray()).toEqual([10, 10, 0]);
|
|
expect(result[0].name).toBe('test{job="testjob"}');
|
|
});
|
|
|
|
it('should fill null values', () => {
|
|
const result = transform({ data: matrixResponse } as any, {
|
|
...options,
|
|
query: { step: 1, start: 0, end: 2 },
|
|
});
|
|
|
|
expect(result[0].fields[0].values.toArray()).toEqual([0, 1000, 2000]);
|
|
expect(result[0].fields[1].values.toArray()).toEqual([null, 10, 0]);
|
|
});
|
|
|
|
it('should use __name__ label as series name', () => {
|
|
const result = transform({ data: matrixResponse } as any, {
|
|
...options,
|
|
query: {
|
|
step: 1,
|
|
start: 0,
|
|
end: 2,
|
|
},
|
|
});
|
|
expect(result[0].name).toEqual('test{job="testjob"}');
|
|
});
|
|
|
|
it('should use query as series name when __name__ is not available and metric is empty', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'matrix',
|
|
result: [
|
|
{
|
|
metric: {},
|
|
values: [[0, '10']],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
const expr = 'histogram_quantile(0.95, sum(rate(tns_request_duration_seconds_bucket[5m])) by (le))';
|
|
const result = transform({ data: response } as any, {
|
|
...options,
|
|
query: {
|
|
step: 1,
|
|
start: 0,
|
|
end: 2,
|
|
expr,
|
|
},
|
|
});
|
|
expect(result[0].name).toEqual(expr);
|
|
});
|
|
|
|
it('should set frame name to undefined if no __name__ label but there are other labels', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'matrix',
|
|
result: [
|
|
{
|
|
metric: { job: 'testjob' },
|
|
values: [
|
|
[1, '10'],
|
|
[2, '0'],
|
|
],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
|
|
const result = transform({ data: response } as any, {
|
|
...options,
|
|
query: {
|
|
step: 1,
|
|
start: 0,
|
|
end: 2,
|
|
},
|
|
});
|
|
expect(result[0].name).toBe('{job="testjob"}');
|
|
});
|
|
|
|
it('should not set displayName for ValueFields', () => {
|
|
const result = transform({ data: matrixResponse } as any, options);
|
|
expect(result[0].fields[1].config.displayName).toBeUndefined();
|
|
expect(result[0].fields[1].config.displayNameFromDS).toBe('test{job="testjob"}');
|
|
});
|
|
|
|
it('should align null values with step', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'matrix',
|
|
result: [
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob' },
|
|
values: [
|
|
[4, '10'],
|
|
[8, '10'],
|
|
],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
|
|
const result = transform({ data: response } as any, { ...options, query: { step: 2, start: 0, end: 8 } });
|
|
expect(result[0].fields[0].values.toArray()).toEqual([0, 2000, 4000, 6000, 8000]);
|
|
expect(result[0].fields[1].values.toArray()).toEqual([null, null, 10, null, 10]);
|
|
});
|
|
});
|
|
|
|
describe('When infinity values are returned', () => {
|
|
describe('When resultType is scalar', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'scalar',
|
|
result: [1443454528, '+Inf'],
|
|
},
|
|
};
|
|
|
|
it('should correctly parse values', () => {
|
|
const result: DataFrame[] = transform({ data: response } as any, {
|
|
...options,
|
|
target: { format: 'table' },
|
|
});
|
|
expect(result[0].fields[1].values.toArray()).toEqual([Number.POSITIVE_INFINITY]);
|
|
});
|
|
});
|
|
|
|
describe('When resultType is vector', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: {
|
|
resultType: 'vector',
|
|
result: [
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob' },
|
|
value: [1443454528, '+Inf'],
|
|
},
|
|
{
|
|
metric: { __name__: 'test', job: 'testjob' },
|
|
value: [1443454528, '-Inf'],
|
|
},
|
|
],
|
|
},
|
|
};
|
|
|
|
describe('When format is table', () => {
|
|
it('should correctly parse values', () => {
|
|
const result: DataFrame[] = transform({ data: response } as any, {
|
|
...options,
|
|
target: { format: 'table' },
|
|
});
|
|
expect(result[0].fields[3].values.toArray()).toEqual([Number.POSITIVE_INFINITY, Number.NEGATIVE_INFINITY]);
|
|
});
|
|
});
|
|
});
|
|
});
|
|
|
|
const exemplarsResponse = {
|
|
status: 'success',
|
|
data: [
|
|
{
|
|
seriesLabels: { __name__: 'test' },
|
|
exemplars: [
|
|
{
|
|
timestamp: 1610449069.957,
|
|
labels: { traceID: '5020b5bc45117f07' },
|
|
value: 0.002074123,
|
|
},
|
|
],
|
|
},
|
|
],
|
|
};
|
|
|
|
describe('When the response is exemplar data', () => {
|
|
it('should return as an data frame with a dataTopic annotations', () => {
|
|
const result = transform({ data: exemplarsResponse } as any, options);
|
|
|
|
expect(result[0].meta?.dataTopic).toBe('annotations');
|
|
expect(result[0].fields.length).toBe(4); // __name__, traceID, Time, Value
|
|
expect(result[0].length).toBe(1);
|
|
});
|
|
|
|
it('should return with an empty array when data is empty', () => {
|
|
const result = transform(
|
|
{
|
|
data: {
|
|
status: 'success',
|
|
data: [],
|
|
},
|
|
} as any,
|
|
options
|
|
);
|
|
|
|
expect(result).toHaveLength(0);
|
|
});
|
|
|
|
it('should remove exemplars that are too close to each other', () => {
|
|
const response = {
|
|
status: 'success',
|
|
data: [
|
|
{
|
|
exemplars: [
|
|
{
|
|
timestamp: 1610449070.0,
|
|
value: 5,
|
|
},
|
|
{
|
|
timestamp: 1610449070.0,
|
|
value: 1,
|
|
},
|
|
{
|
|
timestamp: 1610449070.5,
|
|
value: 13,
|
|
},
|
|
{
|
|
timestamp: 1610449070.3,
|
|
value: 20,
|
|
},
|
|
],
|
|
},
|
|
],
|
|
};
|
|
/**
|
|
* the standard deviation for the above values is 8.4 this means that we show the highest
|
|
* value (20) and then the next value should be 2 times the standard deviation which is 1
|
|
**/
|
|
const result = transform({ data: response } as any, options);
|
|
expect(result[0].length).toBe(2);
|
|
});
|
|
|
|
describe('data link', () => {
|
|
it('should be added to the field if found with url', () => {
|
|
const result = transform({ data: exemplarsResponse } as any, {
|
|
...options,
|
|
exemplarTraceIdDestinations: [{ name: 'traceID', url: 'http://localhost' }],
|
|
});
|
|
|
|
expect(result[0].fields.some((f) => f.config.links?.length)).toBe(true);
|
|
});
|
|
|
|
it('should be added to the field if found with internal link', () => {
|
|
const result = transform({ data: exemplarsResponse } as any, {
|
|
...options,
|
|
exemplarTraceIdDestinations: [{ name: 'traceID', datasourceUid: 'jaeger' }],
|
|
});
|
|
|
|
expect(result[0].fields.some((f) => f.config.links?.length)).toBe(true);
|
|
});
|
|
|
|
it('should not add link if exemplarTraceIdDestinations is not configured', () => {
|
|
const result = transform({ data: exemplarsResponse } as any, options);
|
|
|
|
expect(result[0].fields.some((f) => f.config.links?.length)).toBe(false);
|
|
});
|
|
|
|
it('should not add a datalink with an error when exemplarTraceIdDestinations is not configured', () => {
|
|
const testOptions: any = {
|
|
target: {},
|
|
query: {},
|
|
exemplarTraceIdDestinations: [
|
|
{
|
|
name: 'traceID',
|
|
datasourceUid: 'unknown',
|
|
},
|
|
],
|
|
};
|
|
|
|
const result = transform({ data: exemplarsResponse } as any, testOptions);
|
|
const traceField = result[0].fields.find((f) => f.name === 'traceID');
|
|
expect(traceField).toBeDefined();
|
|
expect(traceField!.config.links?.length).toBe(0);
|
|
});
|
|
});
|
|
});
|
|
});
|
|
});
|