@grafana/data#TimeSeries TypeScript Examples

parseTimeSeriesResult(query: { refId: string; query: any }, columns: any[], rows: any): TimeSeries[] {
    const data: TimeSeries[] = [];
    let timeIndex = -1;
    let metricIndex = -1;
    let valueIndex = -1;

    for (let i = 0; i < columns.length; i++) {
      if (timeIndex === -1 && columns[i].type === 'datetime') {
        timeIndex = i;
      }

      if (metricIndex === -1 && columns[i].type === 'string') {
        metricIndex = i;
      }

      if (valueIndex === -1 && ['int', 'long', 'real', 'double'].indexOf(columns[i].type) > -1) {
        valueIndex = i;
      }
    }

    if (timeIndex === -1) {
      throw new Error('No datetime column found in the result. The Time Series format requires a time column.');
    }

    _.forEach(rows, row => {
      const epoch = ResponseParser.dateTimeToEpoch(row[timeIndex]);
      const metricName = metricIndex > -1 ? row[metricIndex] : columns[valueIndex].name;
      const bucket = ResponseParser.findOrCreateBucket(data, metricName);
      bucket.datapoints.push([row[valueIndex], epoch]);
      bucket.refId = query.refId;
      bucket.meta = {
        query: query.query,
      };
    });

    return data;
  }

static findOrCreateBucket(data: TimeSeries[], target: any): TimeSeries {
    let dataTarget: any = _.find(data, ['target', target]);
    if (!dataTarget) {
      dataTarget = { target: target, datapoints: [], refId: '', query: '' };
      data.push(dataTarget);
    }

    return dataTarget;
  }

export function rangeQueryResponseToTimeSeries(
  response: LokiResponse,
  query: LokiRangeQueryRequest,
  target: LokiQuery,
  responseListLength: number
): TimeSeries[] {
  const transformerOptions: TransformerOptions = {
    format: target.format,
    legendFormat: target.legendFormat,
    start: query.start,
    end: query.end,
    step: query.step,
    query: query.query,
    responseListLength,
    refId: target.refId,
    valueWithRefId: target.valueWithRefId,
  };

  switch (response.data.resultType) {
    case LokiResultType.Vector:
      return response.data.result.map(vecResult =>
        lokiMatrixToTimeSeries({ metric: vecResult.metric, values: [vecResult.value] }, transformerOptions)
      );
    case LokiResultType.Matrix:
      return response.data.result.map(matrixResult => lokiMatrixToTimeSeries(matrixResult, transformerOptions));
    default:
      return [];
  }
}

private panelsQuery(queries: PromQueryRequest[], activeTargets: PromQuery[], end: number, requestId: string) {
    const observables: Array<Observable<Array<TableModel | TimeSeries>>> = queries.map((query, index) => {
      const target = activeTargets[index];
      let observable: Observable<any> = null;

      if (query.instant) {
        observable = from(this.performInstantQuery(query, end));
      } else {
        observable = from(this.performTimeSeriesQuery(query, query.start, query.end));
      }

      return observable.pipe(
        filter((response: any) => (response.cancelled ? false : true)),
        map((response: any) => {
          const data = this.processResult(response, query, target, queries.length);
          return data;
        })
      );
    });

    return forkJoin(observables).pipe(
      map((results: Array<Array<TableModel | TimeSeries>>) => {
        const data = results.reduce((result, current) => {
          return [...result, ...current];
        }, []);
        return {
          data,
          key: requestId,
          state: LoadingState.Done,
        };
      })
    );
  }

transform(response: any, options: any): Array<TableModel | TimeSeries> {
    const prometheusResult = response.data.data.result;

    if (options.format === 'table') {
      return [
        this.transformMetricDataToTable(
          prometheusResult,
          options.responseListLength,
          options.refId,
          options.valueWithRefId
        ),
      ];
    } else if (prometheusResult && options.format === 'heatmap') {
      let seriesList = [];
      for (const metricData of prometheusResult) {
        seriesList.push(this.transformMetricData(metricData, options, options.start, options.end));
      }
      seriesList.sort(sortSeriesByLabel);
      seriesList = this.transformToHistogramOverTime(seriesList);
      return seriesList;
    } else if (prometheusResult) {
      const seriesList = [];
      for (const metricData of prometheusResult) {
        if (response.data.data.resultType === 'matrix') {
          seriesList.push(this.transformMetricData(metricData, options, options.start, options.end));
        } else if (response.data.data.resultType === 'vector') {
          seriesList.push(this.transformInstantMetricData(metricData, options));
        }
      }
      return seriesList;
    }
    return [];
  }

transformToHistogramOverTime(seriesList: TimeSeries[]) {
    /*      t1 = timestamp1, t2 = timestamp2 etc.
            t1  t2  t3          t1  t2  t3
    le10    10  10  0     =>    10  10  0
    le20    20  10  30    =>    10  0   30
    le30    30  10  35    =>    10  0   5
    */
    for (let i = seriesList.length - 1; i > 0; i--) {
      const topSeries = seriesList[i].datapoints;
      const bottomSeries = seriesList[i - 1].datapoints;
      if (!topSeries || !bottomSeries) {
        throw new Error('Prometheus heatmap transform error: data should be a time series');
      }

      for (let j = 0; j < topSeries.length; j++) {
        const bottomPoint = bottomSeries[j] || [0];
        topSeries[j][0] -= bottomPoint[0];
      }
    }

    return seriesList;
  }

function sortSeriesByLabel(s1: TimeSeries, s2: TimeSeries): number {
  let le1, le2;

  try {
    // fail if not integer. might happen with bad queries
    le1 = parseHistogramLabel(s1.target);
    le2 = parseHistogramLabel(s2.target);
  } catch (err) {
    console.log(err);
    return 0;
  }

  if (le1 > le2) {
    return 1;
  }

  if (le1 < le2) {
    return -1;
  }

  return 0;
}

onDataReceived(dataList: TimeSeries[]) {
    const series = dataList.find((item: any) => item.refId === this.props.target.refId);
    if (series) {
      this.setState({
        lastQuery: decodeURIComponent(series.meta.rawQuery),
        lastQueryError: '',
        usedAlignmentPeriod: series.meta.alignmentPeriod,
      });
    }
  }

testContext = (options: any = {}) => {
  const timeSeries = toDataFrame({
    name: 'A-series',
    refId: 'A',
    fields: [
      { name: 'A-series', type: FieldType.number, values: [4, 5, 6] },
      { name: 'time', type: FieldType.time, values: [100, 200, 300] },
    ],
  });

  const table = toDataFrame({
    name: 'table-res',
    refId: 'A',
    fields: [
      { name: 'value', type: FieldType.number, values: [4, 5, 6] },
      { name: 'time', type: FieldType.time, values: [100, 200, 300] },
      { name: 'message', type: FieldType.string, values: ['this is a message', 'second message', 'third'] },
    ],
  });

  const emptyTable = toDataFrame({ name: 'empty-table', refId: 'A', fields: [] });

  const defaultOptions = {
    mode: ExploreMode.Metrics,
    dataFrames: [timeSeries, table, emptyTable],
    graphResult: [] as TimeSeries[],
    tableResult: new TableModel(),
    logsResult: { hasUniqueLabels: false, rows: [] as LogRowModel[] },
  };

  const combinedOptions = { ...defaultOptions, ...options };

  const state = ({
    mode: combinedOptions.mode,
    graphResult: combinedOptions.graphResult,
    tableResult: combinedOptions.tableResult,
    logsResult: combinedOptions.logsResult,
    queryIntervals: { intervalMs: 10 },
  } as any) as ExploreItemState;

  const resultProcessor = new ResultProcessor(state, combinedOptions.dataFrames, 60000, 'utc');

  return {
    dataFrames: combinedOptions.dataFrames,
    resultProcessor,
  };
}

async query(options: DataQueryRequest<AzureMonitorQuery>): Promise<DataQueryResponseData[]> {
    const queries = _.filter(options.targets, item => {
      return item.hide !== true;
    }).map((target: AzureMonitorQuery) => {
      const item = target.appInsights;
      let query: any;
      if (item.rawQuery) {
        query = this.createRawQueryRequest(item, options, target);
      } else {
        query = this.createMetricsRequest(item, options, target);
      }
      query.refId = target.refId;
      query.intervalMs = options.intervalMs;
      query.datasourceId = this.id;
      query.queryType = 'Application Insights';
      return query;
    });

    if (!queries || queries.length === 0) {
      // @ts-ignore
      return;
    }

    const { data } = await getBackendSrv().datasourceRequest({
      url: '/api/tsdb/query',
      method: 'POST',
      data: {
        from: options.range.from.valueOf().toString(),
        to: options.range.to.valueOf().toString(),
        queries,
      },
    });

    const result: DataQueryResponseData[] = [];
    if (data.results) {
      Object.values(data.results).forEach((queryRes: any) => {
        if (queryRes.meta && queryRes.meta.columns) {
          const columnNames = queryRes.meta.columns as string[];
          this.logAnalyticsColumns[queryRes.refId] = _.map(columnNames, n => ({ text: n, value: n }));
        }

        if (!queryRes.series) {
          return;
        }

        queryRes.series.forEach((series: any) => {
          const timeSerie: TimeSeries = {
            target: series.name,
            datapoints: series.points,
            refId: queryRes.refId,
            meta: queryRes.meta,
          };
          result.push(toDataFrame(timeSerie));
        });
      });
      return result;
    }

    return Promise.resolve([]);
  }

function isTimeSeries(data: any): data is TimeSeries {
  return data.hasOwnProperty('datapoints');
}

function lokiMatrixToTimeSeries(matrixResult: LokiMatrixResult, options: TransformerOptions): TimeSeries {
  return {
    target: createMetricLabel(matrixResult.metric, options),
    datapoints: lokiPointsToTimeseriesPoints(matrixResult.values, options),
    tags: matrixResult.metric,
  };
}

async query(options: DataQueryRequest<AzureMonitorQuery>): Promise<DataQueryResponseData[]> {
    const queries = _.filter(options.targets, item => {
      return (
        item.hide !== true &&
        item.azureMonitor.resourceGroup &&
        item.azureMonitor.resourceGroup !== this.defaultDropdownValue &&
        item.azureMonitor.resourceName &&
        item.azureMonitor.resourceName !== this.defaultDropdownValue &&
        item.azureMonitor.metricDefinition &&
        item.azureMonitor.metricDefinition !== this.defaultDropdownValue &&
        item.azureMonitor.metricName &&
        item.azureMonitor.metricName !== this.defaultDropdownValue
      );
    }).map(target => {
      const item = target.azureMonitor;

      // fix for timeGrainUnit which is a deprecated/removed field name
      if (item.timeGrainUnit && item.timeGrain !== 'auto') {
        item.timeGrain = TimegrainConverter.createISO8601Duration(item.timeGrain, item.timeGrainUnit);
      }

      const subscriptionId = this.templateSrv.replace(target.subscription || this.subscriptionId, options.scopedVars);
      const resourceGroup = this.templateSrv.replace(item.resourceGroup, options.scopedVars);
      const resourceName = this.templateSrv.replace(item.resourceName, options.scopedVars);
      const metricNamespace = this.templateSrv.replace(item.metricNamespace, options.scopedVars);
      const metricDefinition = this.templateSrv.replace(item.metricDefinition, options.scopedVars);
      const timeGrain = this.templateSrv.replace((item.timeGrain || '').toString(), options.scopedVars);
      const aggregation = this.templateSrv.replace(item.aggregation, options.scopedVars);
      const top = this.templateSrv.replace(item.top || '', options.scopedVars);

      return {
        refId: target.refId,
        intervalMs: options.intervalMs,
        datasourceId: this.id,
        subscription: subscriptionId,
        queryType: 'Azure Monitor',
        type: 'timeSeriesQuery',
        raw: false,
        azureMonitor: {
          resourceGroup: resourceGroup,
          resourceName: resourceName,
          metricDefinition: metricDefinition,
          timeGrain: timeGrain,
          allowedTimeGrainsMs: item.allowedTimeGrainsMs,
          metricName: this.templateSrv.replace(item.metricName, options.scopedVars),
          metricNamespace:
            metricNamespace && metricNamespace !== this.defaultDropdownValue ? metricNamespace : metricDefinition,
          aggregation: aggregation,
          dimension: this.templateSrv.replace(item.dimension, options.scopedVars),
          top: top || '10',
          dimensionFilter: this.templateSrv.replace(item.dimensionFilter, options.scopedVars),
          alias: item.alias,
          format: target.format,
        },
      };
    });

    if (!queries || queries.length === 0) {
      return Promise.resolve([]);
    }

    const { data } = await getBackendSrv().datasourceRequest({
      url: '/api/tsdb/query',
      method: 'POST',
      data: {
        from: options.range.from.valueOf().toString(),
        to: options.range.to.valueOf().toString(),
        queries,
      },
    });

    const result: DataQueryResponseData[] = [];
    if (data.results) {
      Object['values'](data.results).forEach((queryRes: any) => {
        if (!queryRes.series) {
          return;
        }
        queryRes.series.forEach((series: any) => {
          const timeSerie: TimeSeries = {
            target: series.name,
            datapoints: series.points,
            refId: queryRes.refId,
            meta: queryRes.meta,
          };
          result.push(toDataFrame(timeSerie));
        });
      });
      return result;
    }

    return Promise.resolve([]);
  }