mirror of
https://github.com/grafana/grafana.git
synced 2024-11-29 20:24:18 -06:00
221 lines
6.4 KiB
JavaScript
221 lines
6.4 KiB
JavaScript
define([
|
|
'plugins/datasource/influxdb_08/influxSeries'
|
|
], function(InfluxSeries) {
|
|
'use strict';
|
|
|
|
describe('when generating timeseries from influxdb response', function() {
|
|
|
|
describe('given two series', function() {
|
|
var series = new InfluxSeries({
|
|
seriesList: [
|
|
{
|
|
columns: ['time', 'mean', 'sequence_number'],
|
|
name: 'prod.server1.cpu',
|
|
points: [[1402596000, 10, 1], [1402596001, 12, 2]]
|
|
},
|
|
{
|
|
columns: ['time', 'mean', 'sequence_number'],
|
|
name: 'prod.server2.cpu',
|
|
points: [[1402596000, 15, 1], [1402596001, 16, 2]]
|
|
}
|
|
]
|
|
});
|
|
|
|
var result = series.getTimeSeries();
|
|
|
|
it('should generate two time series', function() {
|
|
expect(result.length).to.be(2);
|
|
expect(result[0].target).to.be('prod.server1.cpu.mean');
|
|
expect(result[0].datapoints[0][0]).to.be(10);
|
|
expect(result[0].datapoints[0][1]).to.be(1402596000);
|
|
expect(result[0].datapoints[1][0]).to.be(12);
|
|
expect(result[0].datapoints[1][1]).to.be(1402596001);
|
|
|
|
expect(result[1].target).to.be('prod.server2.cpu.mean');
|
|
expect(result[1].datapoints[0][0]).to.be(15);
|
|
expect(result[1].datapoints[0][1]).to.be(1402596000);
|
|
expect(result[1].datapoints[1][0]).to.be(16);
|
|
expect(result[1].datapoints[1][1]).to.be(1402596001);
|
|
});
|
|
|
|
});
|
|
|
|
describe('given an alias format', function() {
|
|
var series = new InfluxSeries({
|
|
seriesList: [
|
|
{
|
|
columns: ['time', 'mean', 'sequence_number'],
|
|
name: 'prod.server1.cpu',
|
|
points: [[1402596000, 10, 1], [1402596001, 12, 2]]
|
|
}
|
|
],
|
|
alias: '$s.testing'
|
|
});
|
|
|
|
var result = series.getTimeSeries();
|
|
|
|
it('should generate correct series name', function() {
|
|
expect(result[0].target).to.be('prod.server1.cpu.testing');
|
|
});
|
|
|
|
});
|
|
|
|
describe('given an alias format with segment numbers', function() {
|
|
var series = new InfluxSeries({
|
|
seriesList: [
|
|
{
|
|
columns: ['time', 'mean', 'sequence_number'],
|
|
name: 'prod.server1.cpu',
|
|
points: [[1402596000, 10, 1], [1402596001, 12, 2]]
|
|
}
|
|
],
|
|
alias: '$1.mean'
|
|
});
|
|
|
|
var result = series.getTimeSeries();
|
|
|
|
it('should generate correct series name', function() {
|
|
expect(result[0].target).to.be('server1.mean');
|
|
});
|
|
|
|
});
|
|
|
|
describe('given an alias format and many segments', function() {
|
|
var series = new InfluxSeries({
|
|
seriesList: [
|
|
{
|
|
columns: ['time', 'mean', 'sequence_number'],
|
|
name: 'a0.a1.a2.a3.a4.a5.a6.a7.a8.a9.a10.a11.a12',
|
|
points: [[1402596000, 10, 1], [1402596001, 12, 2]]
|
|
}
|
|
],
|
|
alias: '$5.$11.mean'
|
|
});
|
|
|
|
var result = series.getTimeSeries();
|
|
|
|
it('should generate correct series name', function() {
|
|
expect(result[0].target).to.be('a5.a11.mean');
|
|
});
|
|
|
|
});
|
|
|
|
|
|
describe('given an alias format with group by field', function() {
|
|
var series = new InfluxSeries({
|
|
seriesList: [
|
|
{
|
|
columns: ['time', 'mean', 'host'],
|
|
name: 'prod.cpu',
|
|
points: [[1402596000, 10, 'A']]
|
|
}
|
|
],
|
|
groupByField: 'host',
|
|
alias: '$g.$1'
|
|
});
|
|
|
|
var result = series.getTimeSeries();
|
|
|
|
it('should generate correct series name', function() {
|
|
expect(result[0].target).to.be('A.cpu');
|
|
});
|
|
|
|
});
|
|
|
|
describe('given group by column', function() {
|
|
var series = new InfluxSeries({
|
|
seriesList: [
|
|
{
|
|
columns: ['time', 'mean', 'host'],
|
|
name: 'prod.cpu',
|
|
points: [
|
|
[1402596000, 10, 'A'],
|
|
[1402596001, 11, 'A'],
|
|
[1402596000, 5, 'B'],
|
|
[1402596001, 6, 'B'],
|
|
]
|
|
}
|
|
],
|
|
groupByField: 'host'
|
|
});
|
|
|
|
var result = series.getTimeSeries();
|
|
|
|
it('should generate two time series', function() {
|
|
expect(result.length).to.be(2);
|
|
expect(result[0].target).to.be('prod.cpu.A');
|
|
expect(result[0].datapoints[0][0]).to.be(10);
|
|
expect(result[0].datapoints[0][1]).to.be(1402596000);
|
|
expect(result[0].datapoints[1][0]).to.be(11);
|
|
expect(result[0].datapoints[1][1]).to.be(1402596001);
|
|
|
|
expect(result[1].target).to.be('prod.cpu.B');
|
|
expect(result[1].datapoints[0][0]).to.be(5);
|
|
expect(result[1].datapoints[0][1]).to.be(1402596000);
|
|
expect(result[1].datapoints[1][0]).to.be(6);
|
|
expect(result[1].datapoints[1][1]).to.be(1402596001);
|
|
});
|
|
|
|
});
|
|
|
|
});
|
|
|
|
describe("when creating annotations from influxdb response", function() {
|
|
describe('given column mapping for all columns', function() {
|
|
var series = new InfluxSeries({
|
|
seriesList: [
|
|
{
|
|
columns: ['time', 'text', 'sequence_number', 'title', 'tags'],
|
|
name: 'events1',
|
|
points: [[1402596000000, 'some text', 1, 'Hello', 'B'], [1402596001000, 'asd', 2, 'Hello2', 'B']]
|
|
}
|
|
],
|
|
annotation: {
|
|
query: 'select',
|
|
titleColumn: 'title',
|
|
tagsColumn: 'tags',
|
|
textColumn: 'text',
|
|
}
|
|
});
|
|
|
|
var result = series.getAnnotations();
|
|
|
|
it(' should generate 2 annnotations ', function() {
|
|
expect(result.length).to.be(2);
|
|
expect(result[0].annotation.query).to.be('select');
|
|
expect(result[0].title).to.be('Hello');
|
|
expect(result[0].time).to.be(1402596000000);
|
|
expect(result[0].tags).to.be('B');
|
|
expect(result[0].text).to.be('some text');
|
|
});
|
|
|
|
});
|
|
|
|
describe('given no column mapping', function() {
|
|
var series = new InfluxSeries({
|
|
seriesList: [
|
|
{
|
|
columns: ['time', 'text', 'sequence_number'],
|
|
name: 'events1',
|
|
points: [[1402596000000, 'some text', 1]]
|
|
}
|
|
],
|
|
annotation: { query: 'select' }
|
|
});
|
|
|
|
var result = series.getAnnotations();
|
|
|
|
it('should generate 1 annnotation', function() {
|
|
expect(result.length).to.be(1);
|
|
expect(result[0].title).to.be('some text');
|
|
expect(result[0].time).to.be(1402596000000);
|
|
expect(result[0].tags).to.be(undefined);
|
|
expect(result[0].text).to.be(undefined);
|
|
});
|
|
|
|
});
|
|
|
|
});
|
|
|
|
});
|