Range-related variables #814
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@@ -162,7 +162,7 @@ jobs:
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steps:
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- checkout
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- run: sudo pip install codespell
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- run: codespell -S './.git*,./src/img*' -L que
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- run: codespell -S './.git*,./src/img*' -L que --ignore-words=./.codespell_ignore
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workflows:
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version: 2
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1
.codespell_ignore
Normal file
1
.codespell_ignore
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@@ -0,0 +1 @@
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hist
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@@ -1,6 +1,23 @@
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Functions reference
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===================
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## Functions Variables
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There are some built-in template variables available for using in functions:
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- `$__range_ms` - panel time range in ms
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- `$__range_s` - panel time range in seconds
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- `$__range` - panel time range, string representation (`30s`, `1m`, `1h`)
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- `$__range_series` - invoke function over all series values
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Examples:
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```
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groupBy($__range, avg)
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percentile($__range_series, 95) - 95th percentile over all values
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```
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---
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## Transform
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@@ -10,7 +27,7 @@ Functions reference
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groupBy(interval, function)
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```
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Takes each timeseries and consolidate its points falled in given _interval_ into one point using _function_, which can be one of: _avg_, _min_, _max_, _median_.
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Takes each timeseries and consolidate its points fallen in the given _interval_ into one point using _function_, which can be one of: _avg_, _min_, _max_, _median_.
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Examples:
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```
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@@ -124,7 +141,7 @@ Replaces `null` values with N
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aggregateBy(interval, function)
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```
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Takes all timeseries and consolidate all its points falled in given _interval_ into one point using _function_, which can be one of: _avg_, _min_, _max_, _median_.
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Takes all timeseries and consolidate all its points fallen in the given _interval_ into one point using _function_, which can be one of: _avg_, _min_, _max_, _median_.
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Examples:
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```
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@@ -142,6 +159,20 @@ This will add metrics together and return the sum at each datapoint. This method
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---
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### _percentile_
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```
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percentile(interval, N)
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```
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Takes all timeseries and consolidate all its points fallen in the given _interval_ into one point by Nth percentile.
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Examples:
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```
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percentile(1h, 99)
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percentile($__range_series, 95) - 95th percentile over all values
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```
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---
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### _average_
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```
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average(interval)
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@@ -37,3 +37,5 @@ export const TRIGGER_SEVERITY = [
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/** Minimum interval for SLA over time (1 hour) */
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export const MIN_SLA_INTERVAL = 3600;
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export const RANGE_VARIABLE_VALUE = 'range_series';
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@@ -1,9 +1,8 @@
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import _ from 'lodash';
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import * as utils from './utils';
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import ts from './timeseries';
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import ts, { groupBy_perf as groupBy } from './timeseries';
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let downsampleSeries = ts.downsample;
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let groupBy = ts.groupBy_perf;
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let groupBy_exported = (interval, groupFunc, datapoints) => groupBy(datapoints, interval, groupFunc);
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let sumSeries = ts.sumSeries;
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let delta = ts.delta;
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@@ -111,6 +111,9 @@ export class ZabbixDatasource {
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let timeFrom = Math.ceil(dateMath.parse(options.range.from) / 1000);
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let timeTo = Math.ceil(dateMath.parse(options.range.to) / 1000);
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// Add range variables
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options.scopedVars = Object.assign({}, options.scopedVars, utils.getRangeScopedVars(options.range));
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// Prevent changes of original object
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let target = _.cloneDeep(t);
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@@ -2,6 +2,7 @@ import _ from 'lodash';
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import mocks from '../../test-setup/mocks';
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import { Datasource } from "../module";
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import { zabbixTemplateFormat } from "../datasource";
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import { dateMath } from '@grafana/data';
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describe('ZabbixDatasource', () => {
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let ctx = {};
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@@ -41,7 +42,10 @@ describe('ZabbixDatasource', () => {
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item: {filter: ""}
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}
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],
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range: {from: 'now-7d', to: 'now'}
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range: {
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from: dateMath.parse('now-1h'),
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to: dateMath.parse('now')
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}
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};
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it('should return an empty array when no targets are set', (done) => {
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@@ -59,7 +63,7 @@ describe('ZabbixDatasource', () => {
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let ranges = ['now-8d', 'now-169h', 'now-1M', 'now-1y'];
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_.forEach(ranges, range => {
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ctx.options.range.from = range;
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ctx.options.range.from = dateMath.parse(range);
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ctx.ds.queryNumericData = jest.fn();
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ctx.ds.query(ctx.options);
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@@ -76,7 +80,7 @@ describe('ZabbixDatasource', () => {
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let ranges = ['now-7d', 'now-168h', 'now-1h', 'now-30m', 'now-30s'];
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_.forEach(ranges, range => {
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ctx.options.range.from = range;
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ctx.options.range.from = dateMath.parse(range);
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ctx.ds.queryNumericData = jest.fn();
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ctx.ds.query(ctx.options);
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@@ -108,24 +112,19 @@ describe('ZabbixDatasource', () => {
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}
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]));
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ctx.options = {
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range: {from: 'now-1h', to: 'now'},
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targets: [
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{
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group: {filter: ""},
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host: {filter: "Zabbix server"},
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application: {filter: ""},
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item: {filter: "System information"},
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textFilter: "",
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useCaptureGroups: true,
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mode: 2,
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resultFormat: "table",
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options: {
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skipEmptyValues: false
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}
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}
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],
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};
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ctx.options.targets = [{
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group: {filter: ""},
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host: {filter: "Zabbix server"},
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application: {filter: ""},
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item: {filter: "System information"},
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textFilter: "",
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useCaptureGroups: true,
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mode: 2,
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resultFormat: "table",
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options: {
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skipEmptyValues: false
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}
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}];
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});
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it('should return data in table format', (done) => {
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@@ -11,6 +11,7 @@
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import _ from 'lodash';
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import * as utils from './utils';
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import * as c from './constants';
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const POINT_VALUE = 0;
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const POINT_TIMESTAMP = 1;
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@@ -94,11 +95,15 @@ function groupBy(datapoints, interval, groupByCallback) {
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}));
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}
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function groupBy_perf(datapoints, interval, groupByCallback) {
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export function groupBy_perf(datapoints, interval, groupByCallback) {
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if (datapoints.length === 0) {
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return [];
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}
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if (interval === c.RANGE_VARIABLE_VALUE) {
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return groupByRange(datapoints, groupByCallback);
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}
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let ms_interval = utils.parseInterval(interval);
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let grouped_series = [];
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let frame_values = [];
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@@ -132,6 +137,19 @@ function groupBy_perf(datapoints, interval, groupByCallback) {
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return grouped_series;
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}
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export function groupByRange(datapoints, groupByCallback) {
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const frame_values = [];
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const frame_start = datapoints[0][POINT_TIMESTAMP];
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const frame_end = datapoints[datapoints.length - 1][POINT_TIMESTAMP];
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let point;
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for (let i=0; i < datapoints.length; i++) {
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point = datapoints[i];
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frame_values.push(point[POINT_VALUE]);
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}
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const frame_value = groupByCallback(frame_values);
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return [[frame_value, frame_start], [frame_value, frame_end]];
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}
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/**
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* Summarize set of time series into one.
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* @param {datapoints[]} timeseries array of time series
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@@ -495,6 +513,7 @@ const exportedFunctions = {
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downsample,
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groupBy,
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groupBy_perf,
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groupByRange,
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sumSeries,
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scale,
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offset,
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@@ -1,5 +1,7 @@
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import _ from 'lodash';
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import moment from 'moment';
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import kbn from 'grafana/app/core/utils/kbn';
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import * as c from './constants';
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/**
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* Expand Zabbix item name
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@@ -141,6 +143,18 @@ export function isTemplateVariable(str, templateVariables) {
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}
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}
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export function getRangeScopedVars(range) {
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const msRange = range.to.diff(range.from);
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const sRange = Math.round(msRange / 1000);
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const regularRange = kbn.secondsToHms(msRange / 1000);
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return {
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__range_ms: { text: msRange, value: msRange },
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__range_s: { text: sRange, value: sRange },
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__range: { text: regularRange, value: regularRange },
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__range_series: {text: c.RANGE_VARIABLE_VALUE, value: c.RANGE_VARIABLE_VALUE},
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};
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}
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export function buildRegex(str) {
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var matches = str.match(regexPattern);
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var pattern = matches[1];
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@@ -45,6 +45,7 @@ jest.mock('grafana/app/core/utils/datemath', () => {
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jest.mock('grafana/app/core/utils/kbn', () => {
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return {
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round_interval: n => n,
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secondsToHms: n => n + 'ms'
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};
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}, {virtual: true});
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