Range-related variables #814

.circleci/config.yml

@@ -162,7 +162,7 @@ jobs:
     steps:
     - checkout
     - run: sudo pip install codespell
-    - run: codespell -S './.git*,./src/img*' -L que
+    - run: codespell -S './.git*,./src/img*' -L que --ignore-words=./.codespell_ignore
 
 workflows:
   version: 2

.codespell_ignore

@@ -0,0 +1 @@
+hist

docs/sources/reference/functions.md

@@ -1,6 +1,23 @@
 Functions reference
 ===================
 
+## Functions Variables
+
+There are some built-in template variables available for using in functions:
+
+- `$__range_ms` - panel time range in ms
+- `$__range_s` - panel time range in seconds
+- `$__range` - panel time range, string representation (`30s`, `1m`, `1h`)
+- `$__range_series` - invoke function over all series values
+
+Examples:
+```
+groupBy($__range, avg)
+percentile($__range_series, 95) - 95th percentile over all values
+```
+
+---
+
 ## Transform
 
 
@@ -10,7 +27,7 @@ Functions reference
 groupBy(interval, function)
 ```
 
-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_.
+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_.
 
 Examples:
 ```
@@ -124,7 +141,7 @@ Replaces `null` values with N
 aggregateBy(interval, function)
 ```
 
-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_.
+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_.
 
 Examples:
 ```
@@ -142,6 +159,20 @@ This will add metrics together and return the sum at each datapoint. This method
 
 ---
 
+### _percentile_
+```
+percentile(interval, N)
+```
+Takes all timeseries and consolidate all its points fallen in the given _interval_ into one point by Nth percentile.
+
+Examples:
+```
+percentile(1h, 99)
+percentile($__range_series, 95) - 95th percentile over all values
+```
+
+---
+
 ### _average_
 ```
 average(interval)

src/datasource-zabbix/constants.js

@@ -37,3 +37,5 @@ export const TRIGGER_SEVERITY = [
 
 /** Minimum interval for SLA over time (1 hour) */
 export const MIN_SLA_INTERVAL = 3600;
+
+export const RANGE_VARIABLE_VALUE = 'range_series';

src/datasource-zabbix/dataProcessor.js

@@ -1,9 +1,8 @@
 import _ from 'lodash';
 import * as utils from './utils';
-import ts from './timeseries';
+import ts, { groupBy_perf as groupBy } from './timeseries';
 
 let downsampleSeries = ts.downsample;
-let groupBy = ts.groupBy_perf;
 let groupBy_exported = (interval, groupFunc, datapoints) => groupBy(datapoints, interval, groupFunc);
 let sumSeries = ts.sumSeries;
 let delta = ts.delta;

src/datasource-zabbix/datasource.js

@@ -111,6 +111,9 @@ export class ZabbixDatasource {
       let timeFrom = Math.ceil(dateMath.parse(options.range.from) / 1000);
       let timeTo = Math.ceil(dateMath.parse(options.range.to) / 1000);
 
+      // Add range variables
+      options.scopedVars = Object.assign({}, options.scopedVars, utils.getRangeScopedVars(options.range));
+
       // Prevent changes of original object
       let target = _.cloneDeep(t);
 

src/datasource-zabbix/specs/datasource.spec.js

@@ -2,6 +2,7 @@ import _ from 'lodash';
 import mocks from '../../test-setup/mocks';
 import { Datasource } from "../module";
 import { zabbixTemplateFormat } from "../datasource";
+import { dateMath } from '@grafana/data';
 
 describe('ZabbixDatasource', () => {
   let ctx = {};
@@ -41,7 +42,10 @@ describe('ZabbixDatasource', () => {
           item: {filter: ""}
         }
       ],
-      range: {from: 'now-7d', to: 'now'}
+      range: {
+        from: dateMath.parse('now-1h'),
+        to: dateMath.parse('now')
+      }
     };
 
     it('should return an empty array when no targets are set', (done) => {
@@ -59,7 +63,7 @@ describe('ZabbixDatasource', () => {
       let ranges = ['now-8d', 'now-169h', 'now-1M', 'now-1y'];
 
       _.forEach(ranges, range => {
-        ctx.options.range.from = range;
+        ctx.options.range.from = dateMath.parse(range);
         ctx.ds.queryNumericData = jest.fn();
         ctx.ds.query(ctx.options);
 
@@ -76,7 +80,7 @@ describe('ZabbixDatasource', () => {
       let ranges = ['now-7d', 'now-168h', 'now-1h', 'now-30m', 'now-30s'];
 
       _.forEach(ranges, range => {
-        ctx.options.range.from = range;
+        ctx.options.range.from = dateMath.parse(range);
         ctx.ds.queryNumericData = jest.fn();
         ctx.ds.query(ctx.options);
 
@@ -108,10 +112,7 @@ describe('ZabbixDatasource', () => {
         }
       ]));
 
-      ctx.options = {
+      ctx.options.targets = [{
-        range: {from: 'now-1h', to: 'now'},
-        targets: [
-          {
         group: {filter: ""},
         host: {filter: "Zabbix server"},
         application: {filter: ""},
@@ -123,9 +124,7 @@ describe('ZabbixDatasource', () => {
         options: {
           skipEmptyValues: false
         }
-          }
+      }];
-        ],
-      };
     });
 
     it('should return data in table format', (done) => {

src/datasource-zabbix/timeseries.js

@@ -11,6 +11,7 @@
 
 import _ from 'lodash';
 import * as utils from './utils';
+import * as c from './constants';
 
 const POINT_VALUE = 0;
 const POINT_TIMESTAMP = 1;
@@ -94,11 +95,15 @@ function groupBy(datapoints, interval, groupByCallback) {
   }));
 }
 
-function groupBy_perf(datapoints, interval, groupByCallback) {
+export function groupBy_perf(datapoints, interval, groupByCallback) {
   if (datapoints.length === 0) {
     return [];
   }
 
+  if (interval === c.RANGE_VARIABLE_VALUE) {
+    return groupByRange(datapoints, groupByCallback);
+  }
+
   let ms_interval = utils.parseInterval(interval);
   let grouped_series = [];
   let frame_values = [];
@@ -132,6 +137,19 @@ function groupBy_perf(datapoints, interval, groupByCallback) {
   return grouped_series;
 }
 
+export function groupByRange(datapoints, groupByCallback) {
+  const frame_values = [];
+  const frame_start = datapoints[0][POINT_TIMESTAMP];
+  const frame_end = datapoints[datapoints.length - 1][POINT_TIMESTAMP];
+  let point;
+  for (let i=0; i < datapoints.length; i++) {
+    point = datapoints[i];
+    frame_values.push(point[POINT_VALUE]);
+  }
+  const frame_value = groupByCallback(frame_values);
+  return [[frame_value, frame_start], [frame_value, frame_end]];
+}
+
 /**
  * Summarize set of time series into one.
  * @param {datapoints[]} timeseries array of time series
@@ -495,6 +513,7 @@ const exportedFunctions = {
   downsample,
   groupBy,
   groupBy_perf,
+  groupByRange,
   sumSeries,
   scale,
   offset,

src/datasource-zabbix/utils.js

@@ -1,5 +1,7 @@
 import _ from 'lodash';
 import moment from 'moment';
+import kbn from 'grafana/app/core/utils/kbn';
+import * as c from './constants';
 
 /**
  * Expand Zabbix item name
@@ -141,6 +143,18 @@ export function isTemplateVariable(str, templateVariables) {
   }
 }
 
+export function getRangeScopedVars(range) {
+  const msRange = range.to.diff(range.from);
+  const sRange = Math.round(msRange / 1000);
+  const regularRange = kbn.secondsToHms(msRange / 1000);
+  return {
+    __range_ms: { text: msRange, value: msRange },
+    __range_s: { text: sRange, value: sRange },
+    __range: { text: regularRange, value: regularRange },
+    __range_series: {text: c.RANGE_VARIABLE_VALUE, value: c.RANGE_VARIABLE_VALUE},
+  };
+}
+
 export function buildRegex(str) {
   var matches = str.match(regexPattern);
   var pattern = matches[1];

src/test-setup/jest-setup.js

@@ -45,6 +45,7 @@ jest.mock('grafana/app/core/utils/datemath', () => {
 jest.mock('grafana/app/core/utils/kbn', () => {
   return {
     round_interval: n => n,
+    secondsToHms: n => n + 'ms'
   };
 }, {virtual: true});