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Began work on alias support and alias patterns for InfluxDB 0.9, #1525
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@ -69,8 +69,11 @@ function (angular, _, kbn, InfluxSeries, InfluxQueryBuilder) {
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var query = annotation.query.replace('$timeFilter', timeFilter);
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query = templateSrv.replace(query);
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return this._seriesQuery(query).then(function(results) {
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return new InfluxSeries({ seriesList: results, annotation: annotation }).getAnnotations();
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return this._seriesQuery(query).then(function(data) {
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if (!data || !data.results || !data.results[0]) {
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throw { message: 'No results in response from InfluxDB' };
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}
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return new InfluxSeries({ series: data.results[0].series, annotation: annotation }).getAnnotations();
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});
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};
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@ -168,9 +171,11 @@ function (angular, _, kbn, InfluxSeries, InfluxQueryBuilder) {
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return deferred.promise;
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};
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function handleInfluxQueryResponse(alias, seriesList) {
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var influxSeries = new InfluxSeries({ seriesList: seriesList, alias: alias });
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return influxSeries.getTimeSeries();
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function handleInfluxQueryResponse(alias, data) {
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if (!data || !data.results || !data.results[0]) {
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throw { message: 'No results in response from InfluxDB' };
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}
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return new InfluxSeries({ series: data.results[0].series, alias: alias }).getTimeSeries();
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}
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function getTimeFilter(options) {
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@ -5,8 +5,7 @@ function (_) {
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'use strict';
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function InfluxSeries(options) {
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this.seriesList = options.seriesList && options.seriesList.results && options.seriesList.results.length > 0
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? options.seriesList.results[0].series || [] : [];
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this.series = options.series;
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this.alias = options.alias;
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this.annotation = options.annotation;
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}
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@ -17,23 +16,25 @@ function (_) {
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var output = [];
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var self = this;
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console.log(self.seriesList);
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if (self.seriesList.length === 0) {
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if (self.series.length === 0) {
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return output;
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}
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_.each(self.seriesList, function(series) {
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_.each(self.series, function(series) {
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var datapoints = [];
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for (var i = 0; i < series.values.length; i++) {
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datapoints[i] = [series.values[i][1], new Date(series.values[i][0]).getTime()];
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}
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var seriesName = series.name;
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var tags = _.map(series.tags, function(value, key) {
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return key + ': ' + value;
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});
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if (tags.length > 0) {
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if (self.alias) {
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seriesName = self.alias;
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} else if (series.tags) {
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var tags = _.map(series.tags, function(value, key) {
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return key + ': ' + value;
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});
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seriesName = seriesName + ' {' + tags.join(', ') + '}';
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}
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@ -141,14 +141,103 @@
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</ul>
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</li>
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</ul>
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<ul class="tight-form-list pull-right">
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<li class="tight-form-item">
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Alias pattern
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</li>
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<li>
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<input type="text" class="input-medium tight-form-input" ng-model="target.alias" spellcheck='false' placeholder="alias" ng-blur="get_data()">
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</li>
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</ul>
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<div class="clearfix"></div>
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</div>
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</div>
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</div>
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<section class="grafana-metric-options">
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<div class="tight-form">
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<ul class="tight-form-list">
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<li class="tight-form-item tight-form-item-icon">
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<i class="fa fa-wrench"></i>
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</li>
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<li class="tight-form-item">
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Group by time interval
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</li>
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<li>
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<input type="text" class="input-medium tight-form-input" ng-model="panel.interval" ng-blur="get_data();"
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spellcheck='false' placeholder="example: >10s">
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</li>
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<li class="tight-form-item">
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<i class="fa fa-question-circle" bs-tooltip="'Set a low limit by having a greater sign: example: >60s'" data-placement="right"></i>
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</li>
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</ul>
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<div class="clearfix"></div>
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</div>
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<div class="tight-form">
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<ul class="tight-form-list">
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<li class="tight-form-item tight-form-item-icon">
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<i class="fa fa-info-circle"></i>
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</li>
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<li class="tight-form-item">
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<a ng-click="toggleEditorHelp(1);" bs-tooltip="'click to show helpful info'" data-placement="bottom">
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alias patterns
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</a>
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</li>
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<li class="tight-form-item">
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<a ng-click="toggleEditorHelp(2)" bs-tooltip="'click to show helpful info'" data-placement="bottom">
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stacking & and fill
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</a>
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</li>
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<li class="tight-form-item">
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<a ng-click="toggleEditorHelp(3)" bs-tooltip="'click to show helpful info'" data-placement="bottom">
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group by time
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</a>
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</li>
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</ul>
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<div class="clearfix"></div>
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</div>
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</section>
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<div class="editor-row">
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<div class="pull-left" style="margin-top: 30px;">
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<div class="grafana-info-box span6" ng-if="editorHelpIndex === 1">
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<h5>Alias patterns</h5>
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<ul>
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<li>$m = replaced with measurement name</li>
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<li>$measurement = replaced with measurement name</li>
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<li>$tag_hostname = replaced with the value of the hostname tag</li>
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<li>You can also use [[tag_hostname]] pattern replacement syntax</li>
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</ul>
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</div>
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<div class="grafana-info-box span6" ng-if="editorHelpIndex === 2">
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<h5>Stacking and fill</h5>
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<ul>
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<li>When stacking is enabled it important that points align</li>
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<li>If there are missing points for one series it can cause gaps or missing bars</li>
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<li>You must use fill(0), and select a group by time low limit</li>
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<li>Use the group by time option below your queries and specify for example >10s if your metrics are written every 10 seconds</li>
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<li>This will insert zeros for series that are missing measurements and will make stacking work properly</li>
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</ul>
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</div>
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<div class="grafana-info-box span6" ng-if="editorHelpIndex === 3">
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<h5>Group by time</h5>
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<ul>
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<li>Group by time is important, otherwise the query could return many thousands of datapoints that will slow down Grafana</li>
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<li>Leave the group by time field empty for each query and it will be calculated based on time range and pixel width of the graph</li>
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<li>If you use fill(0) or fill(null) set a low limit for the auto group by time interval</li>
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<li>The low limit can only be set in the group by time option below your queries</li>
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<li>You set a low limit by adding a greater sign before the interval</li>
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<li>Example: >60s if you write metrics to InfluxDB every 60 seconds</li>
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</ul>
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</div>
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</div>
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</div>
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@ -23,7 +23,7 @@
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.tight-form-container-no-item-borders {
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border: 1px solid @grafanaTargetBorder;
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.tight-form, .tight-form-item {
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.tight-form, .tight-form-item, [type=text].tight-form-input {
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border: none;
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}
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}
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@ -1,218 +1,57 @@
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define([
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'plugins/datasource/influxdb_08/influxSeries'
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'plugins/datasource/influxdb/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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var options = { series: [
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{
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name: 'cpu',
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tags: {app: 'test'},
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columns: ['time', 'mean'],
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values: [["2015-05-18T10:57:05Z", 10], ["2015-05-18T10:57:06Z", 12]]
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},
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{
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name: 'cpu',
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tags: {app: 'test2'},
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columns: ['time', 'mean'],
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values: [["2015-05-18T10:57:05Z", 15], ["2015-05-18T10:57:06Z", 16]]
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}
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]};
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describe('and no alias', function() {
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it('should generate two time series', function() {
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var series = new InfluxSeries(options);
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var result = series.getTimeSeries();
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expect(result.length).to.be(2);
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expect(result[0].target).to.be('cpu {app: test}');
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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(1431946625000);
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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(1431946626000);
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expect(result[1].target).to.be('cpu {app: test2}');
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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(1431946625000);
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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(1431946626000);
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});
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});
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var result = series.getAnnotations();
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describe('and simple alias', function() {
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it('should use alias', function() {
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options.alias = 'new series';
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var series = new InfluxSeries(options);
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var result = series.getTimeSeries();
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expect(result[0].target).to.be('new series');
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});
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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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220
public/test/specs/influxSeries08-specs.js
Normal file
220
public/test/specs/influxSeries08-specs.js
Normal file
@ -0,0 +1,220 @@
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define([
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'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',
|
||||
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);
|
||||
});
|
||||
|
||||
});
|
||||
|
||||
});
|
||||
|
||||
});
|
@ -125,6 +125,7 @@ require([
|
||||
'specs/graphiteTargetCtrl-specs',
|
||||
'specs/graphiteDatasource-specs',
|
||||
'specs/influxSeries-specs',
|
||||
'specs/influxSeries08-specs',
|
||||
'specs/influxQueryBuilder-specs',
|
||||
'specs/influx09-querybuilder-specs',
|
||||
'specs/influxdb-datasource-specs',
|
||||
|
Loading…
Reference in New Issue
Block a user