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