mirror of
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146 lines
4.1 KiB
TypeScript
146 lines
4.1 KiB
TypeScript
import {
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LogsModel,
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GraphSeriesXY,
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DataFrame,
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FieldType,
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TimeZone,
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toDataFrame,
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getDisplayProcessor,
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ExploreMode,
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PreferredVisualisationType,
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} from '@grafana/data';
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import { ExploreItemState } from 'app/types/explore';
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import TableModel, { mergeTablesIntoModel, MutableColumn } from 'app/core/table_model';
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import { sortLogsResult, refreshIntervalToSortOrder } from 'app/core/utils/explore';
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import { dataFrameToLogsModel } from 'app/core/logs_model';
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import { getGraphSeriesModel } from 'app/plugins/panel/graph2/getGraphSeriesModel';
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import { config } from 'app/core/config';
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export class ResultProcessor {
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constructor(
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private state: ExploreItemState,
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private dataFrames: DataFrame[],
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private intervalMs: number,
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private timeZone: TimeZone
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) {}
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getGraphResult(): GraphSeriesXY[] | null {
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if (this.state.mode !== ExploreMode.Metrics) {
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return null;
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}
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const onlyTimeSeries = this.dataFrames.filter(frame => isTimeSeries(frame, this.state.datasourceInstance?.meta.id));
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const timeSeriesToShowInGraph = onlyTimeSeries.filter(frame => shouldShowInVisualisationType(frame, 'graph'));
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if (timeSeriesToShowInGraph.length === 0) {
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return null;
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}
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return getGraphSeriesModel(
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timeSeriesToShowInGraph,
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this.timeZone,
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{},
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{ showBars: false, showLines: true, showPoints: false },
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{ asTable: false, isVisible: true, placement: 'under' }
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);
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}
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getTableResult(): DataFrame | null {
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if (this.state.mode !== ExploreMode.Metrics) {
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return null;
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}
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const onlyTables = this.dataFrames.filter(frame => shouldShowInVisualisationType(frame, 'table'));
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if (onlyTables.length === 0) {
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return null;
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}
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const tables = onlyTables.map(frame => {
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const { fields } = frame;
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const fieldCount = fields.length;
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const rowCount = frame.length;
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const columns: MutableColumn[] = fields.map(field => ({
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text: field.name,
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type: field.type,
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filterable: field.config.filterable,
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custom: field.config.custom,
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}));
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const rows: any[][] = [];
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for (let i = 0; i < rowCount; i++) {
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const row: any[] = [];
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for (let j = 0; j < fieldCount; j++) {
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row.push(frame.fields[j].values.get(i));
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}
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rows.push(row);
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}
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return new TableModel({
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columns,
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rows,
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meta: frame.meta,
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});
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});
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const mergedTable = mergeTablesIntoModel(new TableModel(), ...tables);
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const data = toDataFrame(mergedTable);
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// set display processor
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for (const field of data.fields) {
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field.display = getDisplayProcessor({
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field,
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theme: config.theme,
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timeZone: this.timeZone,
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});
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}
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return data;
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}
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getLogsResult(): LogsModel | null {
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if (this.state.mode !== ExploreMode.Logs) {
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return null;
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}
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const newResults = dataFrameToLogsModel(this.dataFrames, this.intervalMs, this.timeZone);
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const sortOrder = refreshIntervalToSortOrder(this.state.refreshInterval);
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const sortedNewResults = sortLogsResult(newResults, sortOrder);
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const rows = sortedNewResults.rows;
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const series = sortedNewResults.series;
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return { ...sortedNewResults, rows, series };
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}
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}
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function isTimeSeries(frame: DataFrame, datasource?: string): boolean {
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// TEMP: Temporary hack. Remove when logs/metrics unification is done
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if (datasource && datasource === 'cloudwatch') {
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return isTimeSeriesCloudWatch(frame);
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}
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if (frame.fields.length === 2) {
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if (frame.fields[0].type === FieldType.time) {
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return true;
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}
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}
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return false;
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}
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function shouldShowInVisualisationType(frame: DataFrame, visualisation: PreferredVisualisationType) {
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if (frame.meta?.preferredVisualisationType && frame.meta?.preferredVisualisationType !== visualisation) {
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return false;
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}
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return true;
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}
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// TEMP: Temporary hack. Remove when logs/metrics unification is done
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function isTimeSeriesCloudWatch(frame: DataFrame): boolean {
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return (
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frame.fields.some(field => field.type === FieldType.time) &&
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frame.fields.some(field => field.type === FieldType.number)
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);
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}
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