Files
signoz/frontend/src/lib/uPlotLib/utils/getUplotChartData.ts
Vinicius Lourenço c64cd0b692 fix(alert-rules): disable clickhouse/prompql for anomaly detection (#11038)
* refactor(alert-rules): disable clickhouse/prompql for anomaly detection

* fix(query-section): try fix issue with timing/useEffect delay

* fix(getUploadChartData): ensure there's no way to crash due to bad sync state

* fix(get-upload-chart-data): render as empty instead of skip series to be more safer
2026-04-22 13:01:42 +00:00

197 lines
5.7 KiB
TypeScript

import { themeColors } from 'constants/theme';
import getLabelName from 'lib/getLabelName';
import { isUndefined } from 'lodash-es';
import { MetricRangePayloadProps } from 'types/api/metrics/getQueryRange';
import { QueryData } from 'types/api/widgets/getQuery';
import { normalizePlotValue } from './dataUtils';
import { generateColor } from './generateColor';
function getXAxisTimestamps(seriesList: QueryData[]): number[] {
const timestamps = new Set<number>();
seriesList.forEach((series: { values?: [number, string][] }) => {
if (series?.values) {
series.values.forEach((value) => {
timestamps.add(value[0]);
});
}
});
const timestampsArr = Array.from(timestamps);
timestampsArr.sort((a, b) => a - b);
return timestampsArr;
}
// eslint-disable-next-line sonarjs/cognitive-complexity
function fillMissingXAxisTimestamps(
timestampArr: number[],
data: Array<{ values?: [number, string][] }>,
): (number | null)[][] {
// Generate a set of all timestamps in the range
const allTimestampsSet = new Set(timestampArr);
const result: (number | null)[][] = [];
// Process each series entry
for (let i = 0; i < data.length; i++) {
const entry = data[i];
if (!entry?.values) {
result.push([]);
} else {
// Build Set of existing timestamps directly (avoid intermediate array)
const existingTimestamps = new Set<number>();
const valuesMap = new Map<number, number | null>();
for (let j = 0; j < entry.values.length; j++) {
const [timestamp, value] = entry.values[j];
existingTimestamps.add(timestamp);
valuesMap.set(timestamp, normalizePlotValue(value));
}
// Find missing timestamps by iterating Set directly (avoid Array.from + filter)
const missingTimestamps: number[] = [];
const allTimestampsArray = Array.from(allTimestampsSet);
for (let k = 0; k < allTimestampsArray.length; k++) {
const timestamp = allTimestampsArray[k];
if (!existingTimestamps.has(timestamp)) {
missingTimestamps.push(timestamp);
}
}
// Add missing timestamps to map
for (let j = 0; j < missingTimestamps.length; j++) {
valuesMap.set(missingTimestamps[j], null);
}
// Build sorted array of values
const sortedTimestamps = Array.from(valuesMap.keys()).sort((a, b) => a - b);
const yValues = sortedTimestamps.map((timestamp) => {
const value = valuesMap.get(timestamp);
return value !== undefined ? value : null;
});
result.push(yValues);
}
}
return result;
}
function getStackedSeries(val: (number | null)[][]): (number | null)[][] {
const series = val ? val.map((row: (number | null)[]) => [...row]) : [];
for (let i = series.length - 2; i >= 0; i--) {
for (let j = 0; j < series[i].length; j++) {
series[i][j] = (series[i][j] || 0) + (series[i + 1][j] || 0);
}
}
return series;
}
export const getUPlotChartData = (
apiResponse?: MetricRangePayloadProps,
fillSpans?: boolean,
stackedBarChart?: boolean,
hiddenGraph?: {
[key: string]: boolean;
},
): any[] => {
const seriesList = apiResponse?.data?.result || [];
const timestampArr = getXAxisTimestamps(seriesList);
const yAxisValuesArr = fillMissingXAxisTimestamps(timestampArr, seriesList);
return [
timestampArr,
...(stackedBarChart && isUndefined(hiddenGraph)
? getStackedSeries(yAxisValuesArr)
: yAxisValuesArr),
];
};
const processAnomalyDetectionData = (
anomalyDetectionData: any,
isDarkMode: boolean,
// eslint-disable-next-line sonarjs/cognitive-complexity
): Record<string, { data: number[][]; color: string }> => {
if (!anomalyDetectionData) {
return {};
}
const processedData: Record<
string,
{ data: number[][]; color: string; legendLabel: string }
> = {};
for (
let queryIndex = 0;
queryIndex < anomalyDetectionData.length;
queryIndex++
) {
const queryData = anomalyDetectionData[queryIndex];
const {
series,
predictedSeries,
upperBoundSeries,
lowerBoundSeries,
queryName,
legend,
} = queryData;
for (let index = 0; index < series?.length; index++) {
const label = getLabelName(
series[index].labels,
queryName || '', // query
legend || '',
);
const objKey =
anomalyDetectionData.length > 1 ? `${queryName}-${label}` : label;
// Single iteration instead of 5 separate map operations
const { values: seriesValues } = series[index] || { values: [] };
const { values: predictedValues } = predictedSeries[index] || { values: [] };
const { values: upperBoundValues } = upperBoundSeries[index] || {
values: [],
};
const { values: lowerBoundValues } = lowerBoundSeries[index] || {
values: [],
};
const length = seriesValues.length;
const timestamps: number[] = new Array(length);
const values: number[] = new Array(length);
const predicted: number[] = new Array(length);
const upperBound: number[] = new Array(length);
const lowerBound: number[] = new Array(length);
for (let i = 0; i < length; i++) {
timestamps[i] = seriesValues[i].timestamp / 1000;
values[i] = seriesValues[i]?.value ?? null;
predicted[i] = predictedValues[i]?.value ?? null;
upperBound[i] = upperBoundValues[i]?.value ?? null;
lowerBound[i] = lowerBoundValues[i]?.value ?? null;
}
processedData[objKey] = {
data: [timestamps, values, predicted, upperBound, lowerBound],
color: generateColor(
objKey,
isDarkMode ? themeColors.chartcolors : themeColors.lightModeColor,
),
legendLabel: label,
};
}
}
return processedData;
};
export const getUplotChartDataForAnomalyDetection = (
apiResponse: MetricRangePayloadProps,
isDarkMode: boolean,
): Record<string, { [x: string]: any; data: number[][]; color: string }> => {
const anomalyDetectionData = apiResponse?.data?.newResult?.data?.result;
return processAnomalyDetectionData(anomalyDetectionData, isDarkMode);
};