506 lines
14 KiB
TypeScript
506 lines
14 KiB
TypeScript
import _ from 'lodash';
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import TableModel from 'grafana/app/core/table_model';
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import * as c from './constants';
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import * as utils from './utils';
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import {
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ArrayVector,
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DataFrame,
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dataFrameFromJSON,
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DataFrameJSON,
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Field,
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FieldType,
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getTimeField,
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MutableDataFrame,
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MutableField,
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TIME_SERIES_TIME_FIELD_NAME,
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TIME_SERIES_VALUE_FIELD_NAME,
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} from '@grafana/data';
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import { ZabbixMetricsQuery } from './types';
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/**
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* Convert Zabbix API history.get response to Grafana format
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*
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* @return {Array} Array of timeseries in Grafana format
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* {
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* target: "Metric name",
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* datapoints: [[<value>, <unixtime>], ...]
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* }
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*/
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function convertHistory(history, items, addHostName, convertPointCallback) {
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/**
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* Response should be in the format:
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* data: [
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* {
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* target: "Metric name",
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* datapoints: [[<value>, <unixtime>], ...]
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* }, ...
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* ]
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*/
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// Group history by itemid
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const grouped_history = _.groupBy(history, 'itemid');
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const hosts = _.uniqBy(_.flatten(_.map(items, 'hosts')), 'hostid'); //uniqBy is needed to deduplicate
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return _.map(grouped_history, (hist, itemid) => {
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const item = _.find(items, {'itemid': itemid}) as any;
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let alias = item.name;
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// Add scopedVars for using in alias functions
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const scopedVars: any = {
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'__zbx_item': { value: item.name },
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'__zbx_item_name': { value: item.name },
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'__zbx_item_key': { value: item.key_ },
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'__zbx_item_interval': { value: item.delay },
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};
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if (_.keys(hosts).length > 0) {
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const host = _.find(hosts, {'hostid': item.hostid});
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scopedVars['__zbx_host'] = { value: host.host };
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scopedVars['__zbx_host_name'] = { value: host.name };
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// Only add host when multiple hosts selected
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if (_.keys(hosts).length > 1 && addHostName) {
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alias = host.name + ": " + alias;
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}
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}
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return {
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target: alias,
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datapoints: _.map(hist, convertPointCallback),
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scopedVars,
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item
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};
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});
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}
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export function seriesToDataFrame(timeseries, target: ZabbixMetricsQuery, valueMappings?: any[], fieldType?: FieldType): MutableDataFrame {
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const { datapoints, scopedVars, target: seriesName, item } = timeseries;
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const timeFiled: Field = {
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name: TIME_SERIES_TIME_FIELD_NAME,
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type: FieldType.time,
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config: {
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custom: {}
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},
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values: new ArrayVector<number>(datapoints.map(p => p[c.DATAPOINT_TS])),
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};
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let values: ArrayVector<number> | ArrayVector<string>;
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if (fieldType === FieldType.string) {
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values = new ArrayVector<string>(datapoints.map(p => p[c.DATAPOINT_VALUE]));
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} else {
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values = new ArrayVector<number>(datapoints.map(p => p[c.DATAPOINT_VALUE]));
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}
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const valueFiled: Field = {
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name: TIME_SERIES_VALUE_FIELD_NAME,
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type: fieldType ?? FieldType.number,
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labels: {},
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config: {
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displayNameFromDS: seriesName,
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custom: {}
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},
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values,
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};
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if (scopedVars) {
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timeFiled.config.custom = {
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itemInterval: scopedVars['__zbx_item_interval']?.value,
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};
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valueFiled.labels = {
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host: scopedVars['__zbx_host_name']?.value,
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item: scopedVars['__zbx_item']?.value,
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item_key: scopedVars['__zbx_item_key']?.value,
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};
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valueFiled.config.custom = {
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itemInterval: scopedVars['__zbx_item_interval']?.value,
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};
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}
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if (item) {
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// Try to use unit configured in Zabbix
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const unit = utils.convertZabbixUnit(item.units);
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if (unit) {
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console.log(`Datasource: unit detected: ${unit} (${item.units})`);
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valueFiled.config.unit = unit;
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if (unit === 'percent') {
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valueFiled.config.min = 0;
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valueFiled.config.max = 100;
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}
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}
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// Try to use value mapping from Zabbix
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const mappings = utils.getValueMapping(item, valueMappings);
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if (mappings && target.options?.useZabbixValueMapping) {
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console.log(`Datasource: using Zabbix value mapping`);
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valueFiled.config.mappings = mappings;
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}
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}
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const fields: Field[] = [ timeFiled, valueFiled ];
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const frame: DataFrame = {
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name: seriesName,
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refId: target.refId,
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fields,
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length: datapoints.length,
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};
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const mutableFrame = new MutableDataFrame(frame);
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return mutableFrame;
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}
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export function dataResponseToTimeSeries(response: DataFrameJSON[], items) {
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const series = [];
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if (response.length === 0) {
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return [];
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}
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for (const frameJSON of response) {
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const frame = dataFrameFromJSON(frameJSON);
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const { timeField, timeIndex } = getTimeField(frame);
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for (let i = 0; i < frame.fields.length; i++) {
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const field = frame.fields[i];
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if (i === timeIndex || !field.values || !field.values.length) {
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continue;
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}
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const s = [];
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for (let j = 0; j < field.values.length; j++) {
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const v = field.values.get(j);
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if (v !== null) {
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s.push({ time: timeField.values.get(j) / 1000, value: v });
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}
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}
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const itemid = field.name;
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const item = _.find(items, {'itemid': itemid});
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let interval = utils.parseItemInterval(item.delay);
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if (interval === 0) {
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interval = null;
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}
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const timeSeriesData = {
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ts: s,
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meta: {
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name: item.name,
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item,
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interval,
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}
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};
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series.push(timeSeriesData);
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}
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}
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return series;
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}
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export function isConvertibleToWide(data: DataFrame[]): boolean {
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if (!data || data.length < 2) {
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return false;
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}
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const first = data[0].fields.find(f => f.type === FieldType.time);
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if (!first) {
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return false;
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}
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for (let i = 1; i < data.length; i++) {
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const timeField = data[i].fields.find(f => f.type === FieldType.time);
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for (let j = 0; j < Math.min(data.length, 2); j++) {
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if (timeField.values.get(j) !== first.values.get(j)) {
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return false;
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}
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}
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}
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return true;
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}
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export function alignFrames(data: MutableDataFrame[]): MutableDataFrame[] {
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if (!data || data.length === 0) {
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return data;
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}
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// Get oldest time stamp for all frames
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let minTimestamp = data[0].fields.find(f => f.name === TIME_SERIES_TIME_FIELD_NAME).values.get(0);
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for (let i = 0; i < data.length; i++) {
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const timeField = data[i].fields.find(f => f.name === TIME_SERIES_TIME_FIELD_NAME);
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const firstTs = timeField.values.get(0);
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if (firstTs < minTimestamp) {
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minTimestamp = firstTs;
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}
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}
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for (let i = 0; i < data.length; i++) {
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const frame = data[i];
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const timeField = frame.fields.find(f => f.name === TIME_SERIES_TIME_FIELD_NAME);
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const valueField = frame.fields.find(f => f.name === TIME_SERIES_VALUE_FIELD_NAME);
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const firstTs = timeField.values.get(0);
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if (firstTs > minTimestamp) {
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console.log('Data frames: adding missing points');
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let timestamps = timeField.values.toArray();
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let values = valueField.values.toArray();
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const missingTimestamps = [];
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const missingValues = [];
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const frameInterval: number = timeField.config.custom?.itemInterval;
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for (let j = minTimestamp; j < firstTs; j+=frameInterval) {
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missingTimestamps.push(j);
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missingValues.push(null);
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}
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timestamps = missingTimestamps.concat(timestamps);
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values = missingValues.concat(values);
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timeField.values = new ArrayVector(timestamps);
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valueField.values = new ArrayVector(values);
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}
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}
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return data;
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}
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export function convertToWide(data: MutableDataFrame[]): DataFrame[] {
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const timeField = data[0].fields.find(f => f.type === FieldType.time);
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if (!timeField) {
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return [];
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}
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const fields: MutableField[] = [ timeField ];
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for (let i = 0; i < data.length; i++) {
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const valueField = data[i].fields.find(f => f.name === TIME_SERIES_VALUE_FIELD_NAME);
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if (!valueField) {
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continue;
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}
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valueField.name = data[i].name;
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// Add null value to the end if series is shifted by 1 time frame
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if (timeField.values.length - valueField.values.length === 1) {
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valueField.values.add(null);
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}
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fields.push(valueField);
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}
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const frame: DataFrame = {
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name: "wide",
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fields,
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length: timeField.values.length,
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};
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return [frame];
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}
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function sortTimeseries(timeseries) {
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// Sort trend data, issue #202
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_.forEach(timeseries, series => {
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series.datapoints = _.sortBy(series.datapoints, point => point[c.DATAPOINT_TS]);
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});
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return timeseries;
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}
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function handleHistory(history, items, addHostName = true) {
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return convertHistory(history, items, addHostName, convertHistoryPoint);
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}
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function handleTrends(history, items, valueType, addHostName = true) {
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const convertPointCallback = _.partial(convertTrendPoint, valueType);
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return convertHistory(history, items, addHostName, convertPointCallback);
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}
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function handleText(history, items, target, addHostName = true) {
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const convertTextCallback = _.partial(convertText, target);
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return convertHistory(history, items, addHostName, convertTextCallback);
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}
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function handleHistoryAsTable(history, items, target) {
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const table: any = new TableModel();
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table.addColumn({text: 'Host'});
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table.addColumn({text: 'Item'});
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table.addColumn({text: 'Key'});
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table.addColumn({text: 'Last value'});
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const grouped_history = _.groupBy(history, 'itemid');
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_.each(items, (item) => {
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const itemHistory = grouped_history[item.itemid] || [];
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const lastPoint = _.last(itemHistory);
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let lastValue = lastPoint ? lastPoint.value : null;
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if (target.options.skipEmptyValues && (!lastValue || lastValue === '')) {
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return;
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}
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// Regex-based extractor
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if (target.textFilter) {
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lastValue = extractText(lastValue, target.textFilter, target.useCaptureGroups);
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}
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let host: any = _.first(item.hosts);
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host = host ? host.name : "";
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table.rows.push([
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host, item.name, item.key_, lastValue
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]);
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});
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return table;
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}
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function convertText(target, point) {
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let value = point.value;
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// Regex-based extractor
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if (target.textFilter) {
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value = extractText(point.value, target.textFilter, target.useCaptureGroups);
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}
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return [
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value,
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point.clock * 1000 + Math.round(point.ns / 1000000)
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];
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}
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function extractText(str, pattern, useCaptureGroups) {
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const extractPattern = new RegExp(pattern);
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const extractedValue = extractPattern.exec(str);
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if (extractedValue) {
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if (useCaptureGroups) {
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return extractedValue[1];
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} else {
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return extractedValue[0];
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}
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}
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return "";
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}
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function handleSLAResponse(itservice, slaProperty, slaObject) {
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const targetSLA = slaObject[itservice.serviceid].sla;
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if (slaProperty.property === 'status') {
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const targetStatus = parseInt(slaObject[itservice.serviceid].status, 10);
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return {
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target: itservice.name + ' ' + slaProperty.name,
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datapoints: [
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[targetStatus, targetSLA[0].to * 1000]
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]
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};
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} else {
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let i;
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const slaArr = [];
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for (i = 0; i < targetSLA.length; i++) {
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if (i === 0) {
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slaArr.push([targetSLA[i][slaProperty.property], targetSLA[i].from * 1000]);
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}
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slaArr.push([targetSLA[i][slaProperty.property], targetSLA[i].to * 1000]);
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}
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return {
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target: itservice.name + ' ' + slaProperty.name,
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datapoints: slaArr
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};
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}
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}
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function handleTriggersResponse(triggers, groups, timeRange) {
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if (!_.isArray(triggers)) {
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let triggersCount = null;
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try {
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triggersCount = Number(triggers);
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} catch (err) {
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console.log("Error when handling triggers count: ", err);
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}
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return {
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target: "triggers count",
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datapoints: [
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[triggersCount, timeRange[1] * 1000]
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]
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};
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} else {
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const stats = getTriggerStats(triggers);
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const groupNames = _.map(groups, 'name');
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const table: any = new TableModel();
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table.addColumn({text: 'Host group'});
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_.each(_.orderBy(c.TRIGGER_SEVERITY, ['val'], ['desc']), (severity) => {
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table.addColumn({text: severity.text});
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});
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_.each(stats, (severity_stats, group) => {
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if (_.includes(groupNames, group)) {
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let row = _.map(_.orderBy(_.toPairs(severity_stats), (s) => s[0], ['desc']), (s) => s[1]);
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row = _.concat([group], ...row);
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table.rows.push(row);
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}
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});
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return table;
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}
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}
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function getTriggerStats(triggers) {
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const groups = _.uniq(_.flattenDeep(_.map(triggers, (trigger) => _.map(trigger.groups, 'name'))));
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// let severity = _.map(c.TRIGGER_SEVERITY, 'text');
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const stats = {};
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_.each(groups, (group) => {
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stats[group] = {0: 0, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0}; // severity:count
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});
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_.each(triggers, (trigger) => {
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_.each(trigger.groups, (group) => {
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stats[group.name][trigger.priority]++;
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});
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});
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return stats;
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}
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function convertHistoryPoint(point) {
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// Value must be a number for properly work
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return [
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Number(point.value),
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point.clock * 1000 + Math.round(point.ns / 1000000)
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];
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}
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function convertTrendPoint(valueType, point) {
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let value;
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switch (valueType) {
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case "min":
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value = point.value_min;
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break;
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case "max":
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value = point.value_max;
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break;
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case "avg":
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value = point.value_avg;
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break;
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case "sum":
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value = point.value_avg * point.num;
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break;
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case "count":
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value = point.num;
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break;
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default:
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value = point.value_avg;
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}
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return [
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Number(value),
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point.clock * 1000
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];
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}
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export default {
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handleHistory,
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convertHistory,
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handleTrends,
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handleText,
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handleHistoryAsTable,
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handleSLAResponse,
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handleTriggersResponse,
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sortTimeseries,
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seriesToDataFrame,
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dataResponseToTimeSeries,
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isConvertibleToWide,
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convertToWide,
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alignFrames,
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};
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