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grafana/public/app/plugins/datasource/influxdb/response_parser.ts

302 lines
8.9 KiB

import { each, flatten, groupBy, isArray } from 'lodash';
import { AnnotationEvent, DataFrame, FieldType, QueryResultMeta } from '@grafana/data';
import { BackendDataSourceResponse, FetchResponse, toDataQueryResponse } from '@grafana/runtime';
import TableModel from 'app/core/TableModel';
import { InfluxQuery } from './types';
export default class ResponseParser {
parse(query: string, results: { results: any }) {
if (!results?.results || results.results.length === 0) {
return [];
}
const influxResults = results.results[0];
if (!influxResults.series) {
return [];
}
const normalizedQuery = query.toLowerCase();
const isRetentionPolicyQuery = normalizedQuery.indexOf('show retention policies') >= 0;
const isValueFirst = normalizedQuery.indexOf('show field keys') >= 0 || isRetentionPolicyQuery;
const res = new Set<string>();
each(influxResults.series, (serie) => {
each(serie.values, (value) => {
if (isArray(value)) {
// In general, there are 2 possible shapes for the returned value.
// The first one is a two-element array,
// where the first element is somewhat a metadata value:
// the tag name for SHOW TAG VALUES queries,
// the time field for SELECT queries, etc.
// The second shape is an one-element array,
// that is containing an immediate value.
// For example, SHOW FIELD KEYS queries return such shape.
// Note, pre-0.11 versions return
// the second shape for SHOW TAG VALUES queries
// (while the newer versions—first).
if (isValueFirst) {
res.add(value[0].toString());
} else if (value[1] !== undefined) {
res.add(value[1].toString());
} else {
res.add(value[0].toString());
}
} else {
res.add(value.toString());
}
});
});
// NOTE: it is important to keep the order of items in the parsed output
// the same as it was in the influxdb-response.
// we use a `Set` to collect the unique-results, and `Set` iteration
// order is insertion-order, so this should be ok.
return Array.from(res).map((v) => ({ text: v }));
}
getTable(dfs: DataFrame[], target: InfluxQuery, meta: QueryResultMeta): TableModel {
let table = new TableModel();
if (dfs.length > 0) {
table.meta = {
...meta,
executedQueryString: dfs[0].meta?.executedQueryString,
};
table.refId = target.refId;
table = getTableCols(dfs, table, target);
// if group by tag(s) added
if (dfs[0].fields[1] && dfs[0].fields[1].labels) {
let dfsByLabels = groupBy(dfs, (df: DataFrame) =>
df.fields[1].labels ? Object.values(df.fields[1].labels!) : null
);
const labels = Object.keys(dfsByLabels);
const dfsByLabelValues = Object.values(dfsByLabels);
for (let i = 0; i < dfsByLabelValues.length; i++) {
table = getTableRows(dfsByLabelValues[i], table, [...labels[i].split(',')]);
}
} else {
table = getTableRows(dfs, table, []);
}
}
return table;
}
async transformAnnotationResponse(
annotation: InfluxQuery,
data: FetchResponse<BackendDataSourceResponse>,
target: InfluxQuery
): Promise<AnnotationEvent[]> {
const rsp = toDataQueryResponse(data, [target]);
if (!rsp) {
return [];
}
const table = this.getTable(rsp.data, target, {});
const list: any[] = [];
let titleColIndex = 0;
let timeColIndex = 0;
let timeEndColIndex = 0;
let textColIndex = 0;
const tagsColIndexes: number[] = [];
each(table.columns, (column, index) => {
if (column.text.toLowerCase() === 'time') {
timeColIndex = index;
return;
}
if (column.text === annotation.titleColumn) {
titleColIndex = index;
return;
}
if (colContainsTag(column.text, annotation.tagsColumn)) {
tagsColIndexes.push(index);
return;
}
if (annotation.textColumn && column.text.includes(annotation.textColumn)) {
textColIndex = index;
return;
}
if (column.text === annotation.timeEndColumn) {
timeEndColIndex = index;
return;
}
// legacy case
if (!titleColIndex && textColIndex !== index) {
titleColIndex = index;
}
});
each(table.rows, (value) => {
const data = {
annotation: annotation,
time: +new Date(value[timeColIndex]),
title: value[titleColIndex],
timeEnd: value[timeEndColIndex],
// Remove empty values, then split in different tags for comma separated values
tags: flatten(
tagsColIndexes
.filter((t) => {
return value[t];
})
.map((t) => {
return value[t].split(',');
})
),
text: value[textColIndex],
};
list.push(data);
});
return list;
}
}
function colContainsTag(colText: string, tagsColumn?: string): boolean {
const tags = (tagsColumn || '').replace(' ', '').split(',');
for (const tag of tags) {
if (tag !== '' && colText.includes(tag)) {
return true;
}
}
return false;
}
function getTableCols(dfs: DataFrame[], table: TableModel, target: InfluxQuery): TableModel {
const selectedParams = getSelectedParams(target);
dfs[0].fields.forEach((field) => {
// Time col
if (field.name.toLowerCase() === 'time') {
table.columns.push({ text: 'Time', type: FieldType.time });
}
// Group by (label) column(s)
else if (field.name.toLowerCase() === 'value') {
if (field.labels) {
Object.keys(field.labels).forEach((key) => {
table.columns.push({ text: key });
});
}
}
});
// Get cols for annotationQuery
if (dfs[0].refId === 'metricFindQuery') {
dfs.forEach((field) => {
if (field.name) {
table.columns.push({ text: field.name });
}
});
}
// Select (metric) column(s)
for (let i = 0; i < selectedParams.length; i++) {
table.columns.push({ text: selectedParams[i] });
}
// ISSUE: https://github.com/grafana/grafana/issues/63842
// if rawQuery and
// has other selected fields in the query and
// dfs field names are in the rawQuery but
// the selected params object doesn't exist in the query then
// add columns to the table
if (
target.rawQuery &&
selectedParams.length === 0 &&
rawQuerySelectedFieldsInDataframe(target.query, dfs) &&
dfs[0].refId !== 'metricFindQuery'
) {
dfs.map((df) => {
if (df.name) {
table.columns.push({ text: df.name });
}
});
}
return table;
}
function getTableRows(dfs: DataFrame[], table: TableModel, labels: string[]): TableModel {
const values = dfs[0].fields[0].values;
for (let i = 0; i < values.length; i++) {
const time = values[i];
const metrics = dfs.map((df: DataFrame) => {
return df.fields[1] ? df.fields[1].values[i] : null;
});
if (metrics.indexOf(null) < 0) {
table.rows.push([time, ...labels, ...metrics]);
}
}
return table;
}
export function getSelectedParams(target: InfluxQuery): string[] {
let allParams: string[] = [];
target.select?.forEach((select) => {
const selector = select.filter((x) => x.type !== 'field');
if (selector.length > 0) {
const aliasIfExist = selector.find((s) => s.type === 'alias');
if (aliasIfExist) {
allParams.push(aliasIfExist.params?.[0].toString() ?? '');
} else {
allParams.push(selector[0].type);
}
} else {
if (select[0] && select[0].params && select[0].params[0]) {
allParams.push(select[0].params[0].toString());
}
}
});
let uniqueParams: string[] = [];
allParams.forEach((param) => {
uniqueParams.push(incrementName(param, param, uniqueParams, 0));
});
return uniqueParams;
}
function incrementName(name: string, nameIncrement: string, params: string[], index: number): string {
if (params.indexOf(nameIncrement) > -1) {
index++;
return incrementName(name, name + '_' + index, params, index);
}
return nameIncrement;
}
function rawQuerySelectedFieldsInDataframe(query: string | undefined, dfs: DataFrame[]) {
const names: Array<string | undefined> = dfs.map((df: DataFrame) => df.name);
const colsInRawQuery = names.every((name: string | undefined) => {
if (name && query) {
// table name and field, i.e. cpu.usage_guest_nice becomes ['cpu', 'usage_guest_nice']
const nameParts = name.split('.');
return nameParts.every((np) => query.toLowerCase().includes(np.toLowerCase()));
}
return false;
});
const queryChecks = ['*', 'SHOW'];
const otherChecks: boolean = queryChecks.some((qc: string) => {
if (query) {
return query.toLowerCase().includes(qc.toLowerCase());
}
return false;
});
return colsInRawQuery || otherChecks;
}