grafana/public/app/plugins/datasource/loki/result_transformer.test.ts

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import { CircularDataFrame, FieldCache, FieldType, MutableDataFrame } from '@grafana/data';
import {
LokiStreamResult,
LokiTailResponse,
LokiStreamResponse,
LokiResultType,
TransformerOptions,
LokiMatrixResult,
} from './types';
import * as ResultTransformer from './result_transformer';
import { setTemplateSrv } from '@grafana/runtime';
import { TemplateSrv } from 'app/features/templating/template_srv';
const streamResult: LokiStreamResult[] = [
{
stream: {
foo: 'bar',
},
values: [['1579857562021616000', "foo: 'bar'"]],
},
{
stream: {
bar: 'foo',
},
values: [['1579857562031616000', "bar: 'foo'"]],
},
];
const lokiResponse: LokiStreamResponse = {
status: 'success',
data: {
result: streamResult,
resultType: LokiResultType.Stream,
stats: {
summary: {
bytesTotal: 900,
},
},
},
};
jest.mock('@grafana/runtime', () => ({
// @ts-ignore
...jest.requireActual('@grafana/runtime'),
getDataSourceSrv: () => {
return {
getInstanceSettings: () => {
return { name: 'Loki1' };
},
};
},
}));
describe('loki result transformer', () => {
beforeAll(() => {
setTemplateSrv(new TemplateSrv());
});
afterAll(() => {
jest.restoreAllMocks();
});
afterEach(() => {
jest.clearAllMocks();
});
describe('lokiStreamResultToDataFrame', () => {
it('converts streams to series', () => {
const data = streamResult.map((stream) => ResultTransformer.lokiStreamResultToDataFrame(stream));
expect(data.length).toBe(2);
expect(data[0].fields[1].labels!['foo']).toEqual('bar');
expect(data[0].fields[0].values.get(0)).toEqual('2020-01-24T09:19:22.021Z');
expect(data[0].fields[1].values.get(0)).toEqual(streamResult[0].values[0][1]);
expect(data[0].fields[2].values.get(0)).toEqual('4b79cb43-81ce-52f7-b1e9-a207fff144dc');
expect(data[1].fields[0].values.get(0)).toEqual('2020-01-24T09:19:22.031Z');
expect(data[1].fields[1].values.get(0)).toEqual(streamResult[1].values[0][1]);
expect(data[1].fields[2].values.get(0)).toEqual('73d144f6-57f2-5a45-a49c-eb998e2006b1');
});
it('should always generate unique ids for logs', () => {
const streamResultWithDuplicateLogs: LokiStreamResult[] = [
{
stream: {
foo: 'bar',
},
values: [
['1579857562021616000', 't=2020-02-12T15:04:51+0000 lvl=info msg="Duplicated"'],
['1579857562021616000', 't=2020-02-12T15:04:51+0000 lvl=info msg="Duplicated"'],
['1579857562021616000', 't=2020-02-12T15:04:51+0000 lvl=info msg="Non-duplicated"'],
['1579857562021616000', 't=2020-02-12T15:04:51+0000 lvl=info msg="Duplicated"'],
],
},
{
stream: {
bar: 'foo',
},
values: [['1579857562021617000', 't=2020-02-12T15:04:51+0000 lvl=info msg="Non-dupliicated"']],
},
];
const data = streamResultWithDuplicateLogs.map((stream) => ResultTransformer.lokiStreamResultToDataFrame(stream));
expect(data[0].fields[2].values.get(0)).toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa');
expect(data[0].fields[2].values.get(1)).toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa_1');
expect(data[0].fields[2].values.get(2)).not.toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa_2');
expect(data[0].fields[2].values.get(3)).toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa_2');
expect(data[1].fields[2].values.get(0)).not.toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa_3');
});
it('should append refId to the unique ids if refId is provided', () => {
const data = streamResult.map((stream) => ResultTransformer.lokiStreamResultToDataFrame(stream, false, 'B'));
expect(data.length).toBe(2);
expect(data[0].fields[2].values.get(0)).toEqual('4b79cb43-81ce-52f7-b1e9-a207fff144dc_B');
expect(data[1].fields[2].values.get(0)).toEqual('73d144f6-57f2-5a45-a49c-eb998e2006b1_B');
});
});
describe('lokiStreamsToDataFrames', () => {
it('should enhance data frames', () => {
jest.spyOn(ResultTransformer, 'enhanceDataFrame');
const dataFrames = ResultTransformer.lokiStreamsToDataFrames(lokiResponse, { refId: 'B' }, 500, {
derivedFields: [
{
matcherRegex: 'trace=(w+)',
name: 'test',
url: 'example.com',
},
],
});
expect(ResultTransformer.enhanceDataFrame).toBeCalled();
dataFrames.forEach((frame) => {
expect(
frame.fields.filter((field) => field.name === 'test' && field.type === 'string').length
).toBeGreaterThanOrEqual(1);
});
});
});
describe('appendResponseToBufferedData', () => {
it('should return a dataframe with ts in iso format', () => {
const tailResponse: LokiTailResponse = {
streams: [
{
stream: {
filename: '/var/log/grafana/grafana.log',
job: 'grafana',
},
values: [
[
'1581519914265798400',
't=2020-02-12T15:04:51+0000 lvl=info msg="Starting Grafana" logger=server version=6.7.0-pre commit=6f09bc9fb4 branch=issue-21929 compiled=2020-02-11T20:43:28+0000',
],
],
},
],
};
const data = new CircularDataFrame({ capacity: 1 });
data.addField({ name: 'ts', type: FieldType.time, config: { displayName: 'Time' } });
data.addField({ name: 'tsNs', type: FieldType.time, config: { displayName: 'Time ns' } });
data.addField({ name: 'line', type: FieldType.string }).labels = { job: 'grafana' };
data.addField({ name: 'labels', type: FieldType.other });
data.addField({ name: 'id', type: FieldType.string });
ResultTransformer.appendResponseToBufferedData(tailResponse, data);
expect(data.get(0)).toEqual({
ts: '2020-02-12T15:05:14.265Z',
tsNs: '1581519914265798400',
line:
't=2020-02-12T15:04:51+0000 lvl=info msg="Starting Grafana" logger=server version=6.7.0-pre commit=6f09bc9fb4 branch=issue-21929 compiled=2020-02-11T20:43:28+0000',
labels: { filename: '/var/log/grafana/grafana.log' },
id: '07f0607c-04ee-51bd-8a0c-fc0f85d37489',
});
});
it('should always generate unique ids for logs', () => {
const tailResponse: LokiTailResponse = {
streams: [
{
stream: {
filename: '/var/log/grafana/grafana.log',
job: 'grafana',
},
values: [
['1581519914265798400', 't=2020-02-12T15:04:51+0000 lvl=info msg="Dupplicated 1"'],
['1581519914265798400', 't=2020-02-12T15:04:51+0000 lvl=info msg="Dupplicated 1"'],
['1581519914265798400', 't=2020-02-12T15:04:51+0000 lvl=info msg="Dupplicated 2"'],
['1581519914265798400', 't=2020-02-12T15:04:51+0000 lvl=info msg="Not dupplicated"'],
['1581519914265798400', 't=2020-02-12T15:04:51+0000 lvl=info msg="Dupplicated 1"'],
['1581519914265798400', 't=2020-02-12T15:04:51+0000 lvl=info msg="Dupplicated 2"'],
],
},
],
};
const data = new CircularDataFrame({ capacity: 6 });
data.addField({ name: 'ts', type: FieldType.time, config: { displayName: 'Time' } });
data.addField({ name: 'tsNs', type: FieldType.time, config: { displayName: 'Time ns' } });
data.addField({ name: 'line', type: FieldType.string }).labels = { job: 'grafana' };
data.addField({ name: 'labels', type: FieldType.other });
data.addField({ name: 'id', type: FieldType.string });
data.refId = 'C';
ResultTransformer.appendResponseToBufferedData(tailResponse, data);
expect(data.get(0).id).toEqual('75e72b25-8589-5f99-8d10-ccb5eb27c1b4_C');
expect(data.get(1).id).toEqual('75e72b25-8589-5f99-8d10-ccb5eb27c1b4_1_C');
expect(data.get(2).id).toEqual('3ca99d6b-3ab5-5970-93c0-eb3c9449088e_C');
expect(data.get(3).id).toEqual('ec9bea1d-70cb-556c-8519-d5d6ae18c004_C');
expect(data.get(4).id).toEqual('75e72b25-8589-5f99-8d10-ccb5eb27c1b4_2_C');
expect(data.get(5).id).toEqual('3ca99d6b-3ab5-5970-93c0-eb3c9449088e_1_C');
});
});
describe('createMetricLabel', () => {
it('should create correct label based on passed variables', () => {
const label = ResultTransformer.createMetricLabel({}, ({
scopedVars: { testLabel: { selected: true, text: 'label1', value: 'label1' } },
legendFormat: '{{$testLabel}}',
} as unknown) as TransformerOptions);
expect(label).toBe('label1');
});
});
describe('lokiResultsToTableModel', () => {
it('should correctly set the type of the label column to be a string', () => {
const lokiResultWithIntLabel = ([
{ metric: { test: 1 }, value: [1610367143, 10] },
{ metric: { test: 2 }, value: [1610367144, 20] },
] as unknown) as LokiMatrixResult[];
const table = ResultTransformer.lokiResultsToTableModel(lokiResultWithIntLabel, 1, 'A', {});
expect(table.columns[0].type).toBe('time');
expect(table.columns[1].type).toBe('string');
expect(table.columns[2].type).toBe('number');
});
});
});
describe('enhanceDataFrame', () => {
it('adds links to fields', () => {
const df = new MutableDataFrame({ fields: [{ name: 'line', values: ['nothing', 'trace1=1234', 'trace2=foo'] }] });
ResultTransformer.enhanceDataFrame(df, {
derivedFields: [
{
matcherRegex: 'trace1=(\\w+)',
name: 'trace1',
url: 'http://localhost/${__value.raw}',
},
{
matcherRegex: 'trace2=(\\w+)',
name: 'trace2',
url: 'test',
datasourceUid: 'uid',
},
{
matcherRegex: 'trace2=(\\w+)',
name: 'trace2',
url: 'test',
datasourceUid: 'uid2',
urlDisplayLabel: 'Custom Label',
},
],
});
expect(df.fields.length).toBe(3);
const fc = new FieldCache(df);
expect(fc.getFieldByName('trace1')!.values.toArray()).toEqual([null, '1234', null]);
expect(fc.getFieldByName('trace1')!.config.links![0]).toEqual({
url: 'http://localhost/${__value.raw}',
title: '',
});
expect(fc.getFieldByName('trace2')!.values.toArray()).toEqual([null, null, 'foo']);
expect(fc.getFieldByName('trace2')!.config.links!.length).toBe(2);
expect(fc.getFieldByName('trace2')!.config.links![0]).toEqual({
title: '',
internal: { datasourceName: 'Loki1', datasourceUid: 'uid', query: { query: 'test' } },
url: '',
});
expect(fc.getFieldByName('trace2')!.config.links![1]).toEqual({
title: 'Custom Label',
internal: { datasourceName: 'Loki1', datasourceUid: 'uid2', query: { query: 'test' } },
url: '',
});
});
describe('lokiPointsToTimeseriesPoints()', () => {
/**
* NOTE on time parameters:
* - Input time series data has timestamps in sec (like Prometheus)
* - Output time series has timestamps in ms (as expected for the chart lib)
* - Start/end parameters are in ns (as expected for Loki)
* - Step is in sec (like in Prometheus)
*/
const data: Array<[number, string]> = [
[1, '1'],
[2, '0'],
[4, '1'],
];
it('returns data as is if step, start, and end align', () => {
const options: Partial<TransformerOptions> = { start: 1 * 1e9, end: 4 * 1e9, step: 1 };
const result = ResultTransformer.lokiPointsToTimeseriesPoints(data, options as TransformerOptions);
expect(result).toEqual([
[1, 1000],
[0, 2000],
[null, 3000],
[1, 4000],
]);
});
});
});