import { CircularDataFrame, FieldCache, FieldType, MutableDataFrame } from '@grafana/data'; import { setTemplateSrv } from '@grafana/runtime'; import { TemplateSrv } from 'app/features/templating/template_srv'; import * as ResultTransformer from './result_transformer'; import { LokiStreamResult, LokiTailResponse, LokiStreamResponse, LokiResultType, TransformerOptions, LokiMatrixResult, } from './types'; 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('lokiStreamsToRawDataFrame', () => { it('converts streams to series', () => { const data = ResultTransformer.lokiStreamsToRawDataFrame(streamResult); expect(data.fields[0].values.get(0)).toStrictEqual({ foo: 'bar' }); expect(data.fields[1].values.get(0)).toEqual('2020-01-24T09:19:22.021Z'); expect(data.fields[2].values.get(0)).toEqual(streamResult[0].values[0][1]); expect(data.fields[3].values.get(0)).toEqual(streamResult[0].values[0][0]); expect(data.fields[4].values.get(0)).toEqual('4b79cb43-81ce-52f7-b1e9-a207fff144dc'); expect(data.fields[0].values.get(1)).toStrictEqual({ bar: 'foo' }); expect(data.fields[1].values.get(1)).toEqual('2020-01-24T09:19:22.031Z'); expect(data.fields[2].values.get(1)).toEqual(streamResult[1].values[0][1]); expect(data.fields[3].values.get(1)).toEqual(streamResult[1].values[0][0]); expect(data.fields[4].values.get(1)).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 = ResultTransformer.lokiStreamsToRawDataFrame(streamResultWithDuplicateLogs); expect(data.fields[4].values.get(0)).toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa'); expect(data.fields[4].values.get(1)).toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa_1'); expect(data.fields[4].values.get(2)).not.toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa_2'); expect(data.fields[4].values.get(3)).toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa_2'); expect(data.fields[4].values.get(4)).not.toEqual('b48fe7dc-36aa-5d37-bfba-087ef810d8fa_3'); }); it('should append refId to the unique ids if refId is provided', () => { const data = ResultTransformer.lokiStreamsToRawDataFrame(streamResult, 'B'); expect(data.fields[4].values.get(0)).toEqual('4b79cb43-81ce-52f7-b1e9-a207fff144dc_B'); expect(data.fields[4].values.get(1)).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', expr: '' }, 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: 'labels', type: FieldType.other }); data.addField({ name: 'ts', type: FieldType.time, config: { displayName: 'Time' } }); data.addField({ name: 'line', type: FieldType.string }).labels = { job: 'grafana' }; data.addField({ name: 'id', type: FieldType.string }); data.addField({ name: 'tsNs', type: FieldType.time, config: { displayName: 'Time ns' } }); 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: 'labels', type: FieldType.other }); data.addField({ name: 'ts', type: FieldType.time, config: { displayName: 'Time' } }); data.addField({ name: 'line', type: FieldType.string }).labels = { job: 'grafana' }; data.addField({ name: 'id', type: FieldType.string }); data.addField({ name: 'tsNs', type: FieldType.time, config: { displayName: 'Time ns' } }); 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) */ const data: Array<[number, string]> = [ [1, '1'], [2, '0'], [4, '1'], [7, 'NaN'], [8, '+Inf'], [9, '-Inf'], ]; it('returns data as is if step, start, and end align', () => { const result = ResultTransformer.lokiPointsToTimeseriesPoints(data); expect(result).toEqual([ [1, 1000], [0, 2000], [1, 4000], [NaN, 7000], [Infinity, 8000], [-Infinity, 9000], ]); }); }); });