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grafana/public/app/plugins/datasource/prometheus/specs/result_transformer.jest.ts

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2018-03-12 17:13:05 +03:00
import { ResultTransformer } from '../result_transformer';
describe('Prometheus Result Transformer', () => {
let ctx: any = {};
beforeEach(() => {
ctx.templateSrv = {
replace: str => str,
};
ctx.resultTransformer = new ResultTransformer(ctx.templateSrv);
});
describe('When resultFormat is table', () => {
var response = {
status: 'success',
data: {
resultType: 'matrix',
result: [
{
metric: { __name__: 'test', job: 'testjob' },
values: [[1443454528, '3846']],
},
{
metric: {
__name__: 'test',
instance: 'localhost:8080',
job: 'otherjob',
},
values: [[1443454529, '3847']],
},
],
},
};
it('should return table model', () => {
var table = ctx.resultTransformer.transformMetricDataToTable(response.data.result);
expect(table.type).toBe('table');
expect(table.rows).toEqual([
[1443454528000, 'test', '', 'testjob', 3846],
[1443454529000, 'test', 'localhost:8080', 'otherjob', 3847],
]);
expect(table.columns).toMatchObject([
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{ text: 'Time', type: 'time' },
{ text: '__name__' },
{ text: 'instance' },
{ text: 'job' },
{ text: 'Value' },
]);
});
it('should column title include refId if response count is more than 2', () => {
var table = ctx.resultTransformer.transformMetricDataToTable(response.data.result, 2, 'B');
expect(table.type).toBe('table');
expect(table.columns).toMatchObject([
{ text: 'Time', type: 'time' },
{ text: '__name__' },
{ text: 'instance' },
{ text: 'job' },
{ text: 'Value #B' },
]);
});
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});
describe('When resultFormat is table and instant = true', () => {
var response = {
status: 'success',
data: {
resultType: 'vector',
result: [
{
metric: { __name__: 'test', job: 'testjob' },
value: [1443454528, '3846'],
},
],
},
};
it('should return table model', () => {
var table = ctx.resultTransformer.transformMetricDataToTable(response.data.result);
expect(table.type).toBe('table');
expect(table.rows).toEqual([[1443454528000, 'test', 'testjob', 3846]]);
expect(table.columns).toMatchObject([
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{ text: 'Time', type: 'time' },
{ text: '__name__' },
{ text: 'job' },
{ text: 'Value' },
]);
});
});
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describe('When resultFormat is heatmap', () => {
var response = {
status: 'success',
data: {
resultType: 'matrix',
result: [
{
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']],
},
],
},
};
it('should convert cumulative histogram to regular', () => {
let result = [];
let options = {
format: 'heatmap',
start: 1445000010,
end: 1445000030,
legendFormat: '{{le}}',
};
ctx.resultTransformer.transform(result, { data: response }, options);
expect(result).toEqual([
{ target: '1', datapoints: [[10, 1445000010000], [10, 1445000020000], [0, 1445000030000]] },
{ target: '2', datapoints: [[10, 1445000010000], [0, 1445000020000], [30, 1445000030000]] },
{ target: '3', datapoints: [[10, 1445000010000], [0, 1445000020000], [10, 1445000030000]] },
]);
});
it('should handle missing datapoints', () => {
const seriesList = [
{ datapoints: [[1, 1000], [2, 2000]] },
{ datapoints: [[2, 1000], [5, 2000], [1, 3000]] },
{ datapoints: [[3, 1000], [7, 2000]] },
];
const expected = [
{ datapoints: [[1, 1000], [2, 2000]] },
{ datapoints: [[1, 1000], [3, 2000], [1, 3000]] },
{ datapoints: [[1, 1000], [2, 2000]] },
];
const result = ctx.resultTransformer.transformToHistogramOverTime(seriesList);
expect(result).toEqual(expected);
});
it('should throw error when data in wrong format', () => {
const seriesList = [{ rows: [] }, { datapoints: [] }];
expect(() => {
ctx.resultTransformer.transformToHistogramOverTime(seriesList);
}).toThrow();
});
it('should throw error when prometheus returned non-timeseries', () => {
// should be { metric: {}, values: [] } for timeseries
const metricData = { metric: {}, value: [] };
expect(() => {
ctx.resultTransformer.transformMetricData(metricData, { step: 1 }, 1000, 2000);
}).toThrow();
});
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});
describe('When resultFormat is time series', () => {
it('should transform matrix into timeseries', () => {
const response = {
status: 'success',
data: {
resultType: 'matrix',
result: [
{
metric: { __name__: 'test', job: 'testjob' },
values: [[0, '10'], [1, '10'], [2, '0']],
},
],
},
};
let result = [];
let options = {
format: 'timeseries',
start: 0,
end: 2,
};
ctx.resultTransformer.transform(result, { data: response }, options);
expect(result).toEqual([{ target: 'test{job="testjob"}', datapoints: [[10, 0], [10, 1000], [0, 2000]] }]);
});
it('should fill timeseries with null values', () => {
const response = {
status: 'success',
data: {
resultType: 'matrix',
result: [
{
metric: { __name__: 'test', job: 'testjob' },
values: [[1, '10'], [2, '0']],
},
],
},
};
let result = [];
let options = {
format: 'timeseries',
step: 1,
start: 0,
end: 2,
};
ctx.resultTransformer.transform(result, { data: response }, options);
expect(result).toEqual([{ target: 'test{job="testjob"}', datapoints: [[null, 0], [10, 1000], [0, 2000]] }]);
});
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']],
},
],
},
};
let result = [];
let options = {
format: 'timeseries',
step: 2,
start: 0,
end: 8,
};
ctx.resultTransformer.transform(result, { data: response }, options);
expect(result).toEqual([
{ target: 'test{job="testjob"}', datapoints: [[null, 0], [null, 2000], [10, 4000], [null, 6000], [10, 8000]] },
]);
});
});
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});