mirror of
https://github.com/grafana/grafana.git
synced 2025-01-10 08:03:58 -06:00
5dca59f720
* common title handling * show labels * update comment * Update changelog for v7.0.0-beta1 (#24007) Co-Authored-By: Marcus Efraimsson <marcus.efraimsson@gmail.com> Co-Authored-By: Andrej Ocenas <mr.ocenas@gmail.com> Co-Authored-By: Hugo Häggmark <hugo.haggmark@grafana.com> Co-authored-by: Tobias Skarhed <1438972+tskarhed@users.noreply.github.com> * verify-repo-update: Fix Dockerfile.deb (#24030) Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com> * CircleCI: Upgrade build pipeline tool (#24021) * CircleCI: Upgrade build pipeline tool * Devenv: ignore enterprise (#24037) * Add header icon to Add data source page (#24033) * latest.json: Update testing version (#24038) Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com> * Fix login page redirected from password reset (#24032) * Storybook: Rewrite stories to CSF (#23989) * ColorPicker to CSF format * Convert stories to CSF * Do not export ClipboardButton * Update ConfirmButton * Remove unused imports * Fix feedback * changelog enterprise 7.0.0-beta1 (#24039) * CircleCI: Bump grafana/build-container revision (#24043) Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com> * Changelog: Updates changelog with more feature details (#24040) * Changelog: Updates changelog with more feature details * spell fix * spell fix * Updates * Readme update * Updates * Select: fixes so component loses focus on selecting value or pressing outside of input. (#24008) * changed the value container to a class component to get it to work with focus (maybe something with context?). * added e2e tests to verify that the select focus is working as it should. * fixed according to feedback. * updated snapshot. * Devenv: add remote renderer to grafana (#24050) * NewPanelEditor: minor UI twekas (#24042) * Forward ref for tabs, use html props * Inspect: add inspect label to drawer title * Add tooltips to sidebar pane tabs, copy changes * Remove unused import * Place tooltips over tabs * Inspector: dont show transformations select if there is only one data frame * Review * Changelog: Add a breaking change (#24051) Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com> * CircleCI: Unpin grafana/docs-base (#24054) Signed-off-by: Arve Knudsen <arve.knudsen@gmail.com> * Search: close overlay on Esc press (#24003) * Search: Close on Esc * Search: Increase bottom padding for the last item in section * Search: Move closing search to keybindingsSrv * Search: Fix folder view * Search: Do not move folders if already in folder * Docs: Adds deprecation notice to changelog and docs for scripted dashboards (#24060) * Update CHANGELOG.md (#24047) Fix typo Co-authored-by: Daniel Lee <dan.limerick@gmail.com> * Documentation: Alternative Team Sync Wording (#23960) * Alternative wording for team sync docs Signed-off-by: Joe Elliott <number101010@gmail.com> * Update docs/sources/auth/team-sync.md Co-Authored-By: Diana Payton <52059945+oddlittlebird@users.noreply.github.com> Co-authored-by: Diana Payton <52059945+oddlittlebird@users.noreply.github.com> * Fix misspell issues (#23905) * Fix misspell issues See, $ golangci-lint run --timeout 10m --disable-all -E misspell ./... Signed-off-by: Mario Trangoni <mjtrangoni@gmail.com> * Fix codespell issues See, $ codespell -S './.git*' -L 'uint,thru,pres,unknwon,serie,referer,uptodate,durationm' Signed-off-by: Mario Trangoni <mjtrangoni@gmail.com> * ci please? * non-empty commit - ci? * Trigger build Co-authored-by: bergquist <carl.bergquist@gmail.com> Co-authored-by: Kyle Brandt <kyle@grafana.com> * fix compile error * better series display * better display * now with prometheus and loki * a few more tests * Improvements and tests * thinking * More advanced and smart default title generation * Another fix * Progress but dam this will be hard * Reverting the time series Value field name change * revert revert going in circles * add a field state object * Use state title when converting back to legacy format * Improved the join (series to columsn) transformer * Got tests running again * Rewrite of seriesToColums that simplifies and fixing tests * Fixed the tricky problem of multiple time field when not used in join * Prometheus: Restoring prometheus formatting * Graphite: Disable Grafana's series naming * fixed imports * Fixed tests and made rename transform change title instead * Fixing more tests * fix more tests * fixed import issue * Fixed more circular dependencies * Renamed to getFieldTitle * More rename * Review feedback * Fix for showing field title in calculate field transformer * fieldOverride: Make it clear that state title after applying defaults & overrides * Fixed ts issue * Update packages/grafana-ui/src/components/TransformersUI/OrganizeFieldsTransformerEditor.tsx Co-authored-by: Marcus Efraimsson <marcus.efraimsson@gmail.com> Co-authored-by: Andrej Ocenas <mr.ocenas@gmail.com> Co-authored-by: Hugo Häggmark <hugo.haggmark@grafana.com> Co-authored-by: Tobias Skarhed <1438972+tskarhed@users.noreply.github.com> Co-authored-by: Arve Knudsen <arve.knudsen@gmail.com> Co-authored-by: Leonard Gram <leo@xlson.com> Co-authored-by: Ivana Huckova <30407135+ivanahuckova@users.noreply.github.com> Co-authored-by: Alexander Zobnin <alexanderzobnin@gmail.com> Co-authored-by: Torkel Ödegaard <torkel@grafana.com> Co-authored-by: Marcus Andersson <marcus.andersson@grafana.com> Co-authored-by: Dominik Prokop <dominik.prokop@grafana.com> Co-authored-by: Alex Khomenko <Clarity-89@users.noreply.github.com> Co-authored-by: Richard Hartmann <RichiH@users.noreply.github.com> Co-authored-by: Daniel Lee <dan.limerick@gmail.com> Co-authored-by: Joe Elliott <joe.elliott@grafana.com> Co-authored-by: Diana Payton <52059945+oddlittlebird@users.noreply.github.com> Co-authored-by: Mario Trangoni <mario@mariotrangoni.de> Co-authored-by: bergquist <carl.bergquist@gmail.com> Co-authored-by: Kyle Brandt <kyle@grafana.com>
958 lines
27 KiB
TypeScript
958 lines
27 KiB
TypeScript
import { DataFrameView, FieldCache, KeyValue, MutableDataFrame } from '@grafana/data';
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import { ElasticResponse } from '../elastic_response';
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import flatten from 'app/core/utils/flatten';
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describe('ElasticResponse', () => {
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let targets;
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let response: any;
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let result: any;
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describe('simple query and count', () => {
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beforeEach(() => {
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targets = [
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{
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refId: 'A',
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metrics: [{ type: 'count', id: '1' }],
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bucketAggs: [{ type: 'date_histogram', field: '@timestamp', id: '2' }],
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},
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];
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response = {
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responses: [
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{
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aggregations: {
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'2': {
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buckets: [
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{
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doc_count: 10,
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key: 1000,
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},
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{
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doc_count: 15,
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key: 2000,
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},
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],
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},
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},
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},
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],
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};
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result = new ElasticResponse(targets, response).getTimeSeries();
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});
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it('should return 1 series', () => {
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expect(result.data.length).toBe(1);
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expect(result.data[0].target).toBe('Count');
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expect(result.data[0].datapoints.length).toBe(2);
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expect(result.data[0].datapoints[0][0]).toBe(10);
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expect(result.data[0].datapoints[0][1]).toBe(1000);
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});
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});
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describe('simple query count & avg aggregation', () => {
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let result: any;
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beforeEach(() => {
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targets = [
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{
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refId: 'A',
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metrics: [
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{ type: 'count', id: '1' },
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{ type: 'avg', field: 'value', id: '2' },
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],
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bucketAggs: [{ type: 'date_histogram', field: '@timestamp', id: '3' }],
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},
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];
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response = {
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responses: [
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{
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aggregations: {
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'3': {
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buckets: [
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{
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'2': { value: 88 },
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doc_count: 10,
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key: 1000,
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},
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{
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'2': { value: 99 },
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doc_count: 15,
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key: 2000,
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},
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],
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},
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},
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},
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],
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};
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result = new ElasticResponse(targets, response).getTimeSeries();
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});
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it('should return 2 series', () => {
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expect(result.data.length).toBe(2);
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expect(result.data[0].datapoints.length).toBe(2);
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expect(result.data[0].datapoints[0][0]).toBe(10);
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expect(result.data[0].datapoints[0][1]).toBe(1000);
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expect(result.data[1].target).toBe('Average value');
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expect(result.data[1].datapoints[0][0]).toBe(88);
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expect(result.data[1].datapoints[1][0]).toBe(99);
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});
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});
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describe('single group by query one metric', () => {
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let result: any;
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beforeEach(() => {
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targets = [
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{
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refId: 'A',
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metrics: [{ type: 'count', id: '1' }],
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bucketAggs: [
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{ type: 'terms', field: 'host', id: '2' },
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{ type: 'date_histogram', field: '@timestamp', id: '3' },
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],
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},
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];
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response = {
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responses: [
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{
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aggregations: {
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'2': {
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buckets: [
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{
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'3': {
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buckets: [
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{ doc_count: 1, key: 1000 },
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{ doc_count: 3, key: 2000 },
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],
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},
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doc_count: 4,
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key: 'server1',
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},
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{
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'3': {
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buckets: [
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{ doc_count: 2, key: 1000 },
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{ doc_count: 8, key: 2000 },
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],
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},
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doc_count: 10,
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key: 'server2',
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},
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],
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},
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},
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},
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],
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};
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result = new ElasticResponse(targets, response).getTimeSeries();
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});
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it('should return 2 series', () => {
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expect(result.data.length).toBe(2);
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expect(result.data[0].datapoints.length).toBe(2);
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expect(result.data[0].target).toBe('server1');
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expect(result.data[1].target).toBe('server2');
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});
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});
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describe('single group by query two metrics', () => {
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let result: any;
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beforeEach(() => {
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targets = [
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{
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refId: 'A',
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metrics: [
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{ type: 'count', id: '1' },
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{ type: 'avg', field: '@value', id: '4' },
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],
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bucketAggs: [
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{ type: 'terms', field: 'host', id: '2' },
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{ type: 'date_histogram', field: '@timestamp', id: '3' },
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],
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},
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];
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response = {
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responses: [
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{
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aggregations: {
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'2': {
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buckets: [
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{
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'3': {
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buckets: [
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{ '4': { value: 10 }, doc_count: 1, key: 1000 },
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{ '4': { value: 12 }, doc_count: 3, key: 2000 },
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],
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},
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doc_count: 4,
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key: 'server1',
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},
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{
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'3': {
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buckets: [
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{ '4': { value: 20 }, doc_count: 1, key: 1000 },
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{ '4': { value: 32 }, doc_count: 3, key: 2000 },
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],
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},
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doc_count: 10,
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key: 'server2',
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},
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],
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},
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},
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},
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],
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};
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result = new ElasticResponse(targets, response).getTimeSeries();
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});
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it('should return 2 series', () => {
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expect(result.data.length).toBe(4);
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expect(result.data[0].datapoints.length).toBe(2);
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expect(result.data[0].target).toBe('server1 Count');
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expect(result.data[1].target).toBe('server1 Average @value');
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expect(result.data[2].target).toBe('server2 Count');
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expect(result.data[3].target).toBe('server2 Average @value');
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});
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});
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describe('with percentiles ', () => {
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let result: any;
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beforeEach(() => {
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targets = [
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{
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refId: 'A',
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metrics: [{ type: 'percentiles', settings: { percents: [75, 90] }, id: '1' }],
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bucketAggs: [{ type: 'date_histogram', field: '@timestamp', id: '3' }],
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},
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];
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response = {
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responses: [
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{
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aggregations: {
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'3': {
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buckets: [
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{
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'1': { values: { '75': 3.3, '90': 5.5 } },
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doc_count: 10,
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key: 1000,
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},
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{
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'1': { values: { '75': 2.3, '90': 4.5 } },
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doc_count: 15,
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key: 2000,
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},
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],
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},
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},
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},
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],
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};
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result = new ElasticResponse(targets, response).getTimeSeries();
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});
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it('should return 2 series', () => {
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expect(result.data.length).toBe(2);
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expect(result.data[0].datapoints.length).toBe(2);
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expect(result.data[0].target).toBe('p75');
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expect(result.data[1].target).toBe('p90');
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expect(result.data[0].datapoints[0][0]).toBe(3.3);
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expect(result.data[0].datapoints[0][1]).toBe(1000);
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expect(result.data[1].datapoints[1][0]).toBe(4.5);
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});
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});
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describe('with extended_stats', () => {
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let result: any;
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beforeEach(() => {
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targets = [
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{
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refId: 'A',
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metrics: [
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{
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type: 'extended_stats',
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meta: { max: true, std_deviation_bounds_upper: true },
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id: '1',
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},
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],
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bucketAggs: [
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{ type: 'terms', field: 'host', id: '3' },
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{ type: 'date_histogram', id: '4' },
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],
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},
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];
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response = {
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responses: [
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{
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aggregations: {
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'3': {
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buckets: [
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{
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key: 'server1',
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'4': {
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buckets: [
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{
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'1': {
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max: 10.2,
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min: 5.5,
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std_deviation_bounds: { upper: 3, lower: -2 },
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},
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doc_count: 10,
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key: 1000,
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},
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],
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},
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},
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{
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key: 'server2',
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'4': {
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buckets: [
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{
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'1': {
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max: 10.2,
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min: 5.5,
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std_deviation_bounds: { upper: 3, lower: -2 },
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},
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doc_count: 10,
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key: 1000,
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},
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],
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},
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},
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],
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},
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},
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},
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],
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};
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result = new ElasticResponse(targets, response).getTimeSeries();
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});
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it('should return 4 series', () => {
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expect(result.data.length).toBe(4);
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expect(result.data[0].datapoints.length).toBe(1);
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expect(result.data[0].target).toBe('server1 Max');
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expect(result.data[1].target).toBe('server1 Std Dev Upper');
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expect(result.data[0].datapoints[0][0]).toBe(10.2);
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expect(result.data[1].datapoints[0][0]).toBe(3);
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});
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});
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describe('single group by with alias pattern', () => {
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let result: any;
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beforeEach(() => {
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targets = [
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{
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refId: 'A',
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metrics: [{ type: 'count', id: '1' }],
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alias: '{{term @host}} {{metric}} and {{not_exist}} {{@host}}',
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bucketAggs: [
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{ type: 'terms', field: '@host', id: '2' },
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{ type: 'date_histogram', field: '@timestamp', id: '3' },
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],
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},
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];
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response = {
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responses: [
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{
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aggregations: {
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'2': {
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buckets: [
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{
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'3': {
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buckets: [
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{ doc_count: 1, key: 1000 },
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{ doc_count: 3, key: 2000 },
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],
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},
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doc_count: 4,
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key: 'server1',
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},
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{
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'3': {
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buckets: [
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{ doc_count: 2, key: 1000 },
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{ doc_count: 8, key: 2000 },
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],
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},
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doc_count: 10,
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key: 'server2',
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},
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{
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'3': {
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buckets: [
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{ doc_count: 2, key: 1000 },
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{ doc_count: 8, key: 2000 },
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],
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},
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doc_count: 10,
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key: 0,
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},
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],
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},
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},
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},
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],
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};
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result = new ElasticResponse(targets, response).getTimeSeries();
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});
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it('should return 2 series', () => {
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expect(result.data.length).toBe(3);
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expect(result.data[0].datapoints.length).toBe(2);
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expect(result.data[0].target).toBe('server1 Count and {{not_exist}} server1');
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expect(result.data[1].target).toBe('server2 Count and {{not_exist}} server2');
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expect(result.data[2].target).toBe('0 Count and {{not_exist}} 0');
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});
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});
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describe('histogram response', () => {
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let result: any;
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beforeEach(() => {
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targets = [
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{
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refId: 'A',
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metrics: [{ type: 'count', id: '1' }],
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bucketAggs: [{ type: 'histogram', field: 'bytes', id: '3' }],
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},
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];
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response = {
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responses: [
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{
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aggregations: {
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'3': {
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buckets: [
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{ doc_count: 1, key: 1000 },
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{ doc_count: 3, key: 2000 },
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{ doc_count: 2, key: 1000 },
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],
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},
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},
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},
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],
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};
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result = new ElasticResponse(targets, response).getTimeSeries();
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});
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it('should return table with byte and count', () => {
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expect(result.data[0].rows.length).toBe(3);
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expect(result.data[0].columns).toEqual([{ text: 'bytes', filterable: true }, { text: 'Count' }]);
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});
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});
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describe('with two filters agg', () => {
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let result: any;
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beforeEach(() => {
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targets = [
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{
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refId: 'A',
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|
metrics: [{ type: 'count', id: '1' }],
|
|
bucketAggs: [
|
|
{
|
|
id: '2',
|
|
type: 'filters',
|
|
settings: {
|
|
filters: [{ query: '@metric:cpu' }, { query: '@metric:logins.count' }],
|
|
},
|
|
},
|
|
{ type: 'date_histogram', field: '@timestamp', id: '3' },
|
|
],
|
|
},
|
|
];
|
|
response = {
|
|
responses: [
|
|
{
|
|
aggregations: {
|
|
'2': {
|
|
buckets: {
|
|
'@metric:cpu': {
|
|
'3': {
|
|
buckets: [
|
|
{ doc_count: 1, key: 1000 },
|
|
{ doc_count: 3, key: 2000 },
|
|
],
|
|
},
|
|
},
|
|
'@metric:logins.count': {
|
|
'3': {
|
|
buckets: [
|
|
{ doc_count: 2, key: 1000 },
|
|
{ doc_count: 8, key: 2000 },
|
|
],
|
|
},
|
|
},
|
|
},
|
|
},
|
|
},
|
|
},
|
|
],
|
|
};
|
|
|
|
result = new ElasticResponse(targets, response).getTimeSeries();
|
|
});
|
|
|
|
it('should return 2 series', () => {
|
|
expect(result.data.length).toBe(2);
|
|
expect(result.data[0].datapoints.length).toBe(2);
|
|
expect(result.data[0].target).toBe('@metric:cpu');
|
|
expect(result.data[1].target).toBe('@metric:logins.count');
|
|
});
|
|
});
|
|
|
|
describe('with dropfirst and last aggregation', () => {
|
|
beforeEach(() => {
|
|
targets = [
|
|
{
|
|
refId: 'A',
|
|
metrics: [{ type: 'avg', id: '1' }, { type: 'count' }],
|
|
bucketAggs: [
|
|
{
|
|
id: '2',
|
|
type: 'date_histogram',
|
|
field: 'host',
|
|
settings: { trimEdges: 1 },
|
|
},
|
|
],
|
|
},
|
|
];
|
|
|
|
response = {
|
|
responses: [
|
|
{
|
|
aggregations: {
|
|
'2': {
|
|
buckets: [
|
|
{
|
|
'1': { value: 1000 },
|
|
key: 1,
|
|
doc_count: 369,
|
|
},
|
|
{
|
|
'1': { value: 2000 },
|
|
key: 2,
|
|
doc_count: 200,
|
|
},
|
|
{
|
|
'1': { value: 2000 },
|
|
key: 3,
|
|
doc_count: 200,
|
|
},
|
|
],
|
|
},
|
|
},
|
|
},
|
|
],
|
|
};
|
|
|
|
result = new ElasticResponse(targets, response).getTimeSeries();
|
|
});
|
|
|
|
it('should remove first and last value', () => {
|
|
expect(result.data.length).toBe(2);
|
|
expect(result.data[0].datapoints.length).toBe(1);
|
|
});
|
|
});
|
|
|
|
describe('No group by time', () => {
|
|
beforeEach(() => {
|
|
targets = [
|
|
{
|
|
refId: 'A',
|
|
metrics: [{ type: 'avg', id: '1' }, { type: 'count' }],
|
|
bucketAggs: [{ id: '2', type: 'terms', field: 'host' }],
|
|
},
|
|
];
|
|
|
|
response = {
|
|
responses: [
|
|
{
|
|
aggregations: {
|
|
'2': {
|
|
buckets: [
|
|
{
|
|
'1': { value: 1000 },
|
|
key: 'server-1',
|
|
doc_count: 369,
|
|
},
|
|
{
|
|
'1': { value: 2000 },
|
|
key: 'server-2',
|
|
doc_count: 200,
|
|
},
|
|
],
|
|
},
|
|
},
|
|
},
|
|
],
|
|
};
|
|
|
|
result = new ElasticResponse(targets, response).getTimeSeries();
|
|
});
|
|
|
|
it('should return table', () => {
|
|
expect(result.data.length).toBe(1);
|
|
expect(result.data[0].type).toBe('table');
|
|
expect(result.data[0].rows.length).toBe(2);
|
|
expect(result.data[0].rows[0][0]).toBe('server-1');
|
|
expect(result.data[0].rows[0][1]).toBe(1000);
|
|
expect(result.data[0].rows[0][2]).toBe(369);
|
|
|
|
expect(result.data[0].rows[1][0]).toBe('server-2');
|
|
expect(result.data[0].rows[1][1]).toBe(2000);
|
|
});
|
|
});
|
|
|
|
describe('No group by time with percentiles ', () => {
|
|
let result: any;
|
|
|
|
beforeEach(() => {
|
|
targets = [
|
|
{
|
|
refId: 'A',
|
|
metrics: [{ type: 'percentiles', field: 'value', settings: { percents: [75, 90] }, id: '1' }],
|
|
bucketAggs: [{ type: 'term', field: 'id', id: '3' }],
|
|
},
|
|
];
|
|
response = {
|
|
responses: [
|
|
{
|
|
aggregations: {
|
|
'3': {
|
|
buckets: [
|
|
{
|
|
'1': { values: { '75': 3.3, '90': 5.5 } },
|
|
doc_count: 10,
|
|
key: 'id1',
|
|
},
|
|
{
|
|
'1': { values: { '75': 2.3, '90': 4.5 } },
|
|
doc_count: 15,
|
|
key: 'id2',
|
|
},
|
|
],
|
|
},
|
|
},
|
|
},
|
|
],
|
|
};
|
|
|
|
result = new ElasticResponse(targets, response).getTimeSeries();
|
|
});
|
|
|
|
it('should return table', () => {
|
|
expect(result.data.length).toBe(1);
|
|
expect(result.data[0].type).toBe('table');
|
|
expect(result.data[0].columns[0].text).toBe('id');
|
|
expect(result.data[0].columns[1].text).toBe('p75 value');
|
|
expect(result.data[0].columns[2].text).toBe('p90 value');
|
|
expect(result.data[0].rows.length).toBe(2);
|
|
expect(result.data[0].rows[0][0]).toBe('id1');
|
|
expect(result.data[0].rows[0][1]).toBe(3.3);
|
|
expect(result.data[0].rows[0][2]).toBe(5.5);
|
|
expect(result.data[0].rows[1][0]).toBe('id2');
|
|
expect(result.data[0].rows[1][1]).toBe(2.3);
|
|
expect(result.data[0].rows[1][2]).toBe(4.5);
|
|
});
|
|
});
|
|
|
|
describe('Multiple metrics of same type', () => {
|
|
beforeEach(() => {
|
|
targets = [
|
|
{
|
|
refId: 'A',
|
|
metrics: [
|
|
{ type: 'avg', id: '1', field: 'test' },
|
|
{ type: 'avg', id: '2', field: 'test2' },
|
|
],
|
|
bucketAggs: [{ id: '2', type: 'terms', field: 'host' }],
|
|
},
|
|
];
|
|
|
|
response = {
|
|
responses: [
|
|
{
|
|
aggregations: {
|
|
'2': {
|
|
buckets: [
|
|
{
|
|
'1': { value: 1000 },
|
|
'2': { value: 3000 },
|
|
key: 'server-1',
|
|
doc_count: 369,
|
|
},
|
|
],
|
|
},
|
|
},
|
|
},
|
|
],
|
|
};
|
|
|
|
result = new ElasticResponse(targets, response).getTimeSeries();
|
|
});
|
|
|
|
it('should include field in metric name', () => {
|
|
expect(result.data[0].type).toBe('table');
|
|
expect(result.data[0].rows[0][1]).toBe(1000);
|
|
expect(result.data[0].rows[0][2]).toBe(3000);
|
|
});
|
|
});
|
|
|
|
describe('Raw documents query', () => {
|
|
beforeEach(() => {
|
|
targets = [
|
|
{
|
|
refId: 'A',
|
|
metrics: [{ type: 'raw_document', id: '1' }],
|
|
bucketAggs: [],
|
|
},
|
|
];
|
|
response = {
|
|
responses: [
|
|
{
|
|
hits: {
|
|
total: 100,
|
|
hits: [
|
|
{
|
|
_id: '1',
|
|
_type: 'type',
|
|
_index: 'index',
|
|
_source: { sourceProp: 'asd' },
|
|
fields: { fieldProp: 'field' },
|
|
},
|
|
{
|
|
_source: { sourceProp: 'asd2' },
|
|
fields: { fieldProp: 'field2' },
|
|
},
|
|
],
|
|
},
|
|
},
|
|
],
|
|
};
|
|
|
|
result = new ElasticResponse(targets, response).getTimeSeries();
|
|
});
|
|
|
|
it('should return docs', () => {
|
|
expect(result.data.length).toBe(1);
|
|
expect(result.data[0].type).toBe('docs');
|
|
expect(result.data[0].total).toBe(100);
|
|
expect(result.data[0].datapoints.length).toBe(2);
|
|
expect(result.data[0].datapoints[0].sourceProp).toBe('asd');
|
|
expect(result.data[0].datapoints[0].fieldProp).toBe('field');
|
|
});
|
|
});
|
|
|
|
describe('with bucket_script ', () => {
|
|
let result: any;
|
|
|
|
beforeEach(() => {
|
|
targets = [
|
|
{
|
|
refId: 'A',
|
|
metrics: [
|
|
{ id: '1', type: 'sum', field: '@value' },
|
|
{ id: '3', type: 'max', field: '@value' },
|
|
{
|
|
id: '4',
|
|
field: 'select field',
|
|
pipelineVariables: [
|
|
{ name: 'var1', pipelineAgg: '1' },
|
|
{ name: 'var2', pipelineAgg: '3' },
|
|
],
|
|
settings: { script: 'params.var1 * params.var2' },
|
|
type: 'bucket_script',
|
|
},
|
|
],
|
|
bucketAggs: [{ type: 'date_histogram', field: '@timestamp', id: '2' }],
|
|
},
|
|
];
|
|
response = {
|
|
responses: [
|
|
{
|
|
aggregations: {
|
|
'2': {
|
|
buckets: [
|
|
{
|
|
1: { value: 2 },
|
|
3: { value: 3 },
|
|
4: { value: 6 },
|
|
doc_count: 60,
|
|
key: 1000,
|
|
},
|
|
{
|
|
1: { value: 3 },
|
|
3: { value: 4 },
|
|
4: { value: 12 },
|
|
doc_count: 60,
|
|
key: 2000,
|
|
},
|
|
],
|
|
},
|
|
},
|
|
},
|
|
],
|
|
};
|
|
|
|
result = new ElasticResponse(targets, response).getTimeSeries();
|
|
});
|
|
|
|
it('should return 3 series', () => {
|
|
expect(result.data.length).toBe(3);
|
|
expect(result.data[0].datapoints.length).toBe(2);
|
|
expect(result.data[0].target).toBe('Sum @value');
|
|
expect(result.data[1].target).toBe('Max @value');
|
|
expect(result.data[2].target).toBe('Sum @value * Max @value');
|
|
expect(result.data[0].datapoints[0][0]).toBe(2);
|
|
expect(result.data[1].datapoints[0][0]).toBe(3);
|
|
expect(result.data[2].datapoints[0][0]).toBe(6);
|
|
expect(result.data[0].datapoints[1][0]).toBe(3);
|
|
expect(result.data[1].datapoints[1][0]).toBe(4);
|
|
expect(result.data[2].datapoints[1][0]).toBe(12);
|
|
});
|
|
});
|
|
|
|
describe('simple logs query and count', () => {
|
|
const targets: any = [
|
|
{
|
|
refId: 'A',
|
|
metrics: [{ type: 'count', id: '1' }],
|
|
bucketAggs: [{ type: 'date_histogram', settings: { interval: 'auto' }, id: '2' }],
|
|
context: 'explore',
|
|
interval: '10s',
|
|
isLogsQuery: true,
|
|
key: 'Q-1561369883389-0.7611823271062786-0',
|
|
liveStreaming: false,
|
|
maxDataPoints: 1620,
|
|
query: '',
|
|
timeField: '@timestamp',
|
|
},
|
|
];
|
|
const response = {
|
|
responses: [
|
|
{
|
|
aggregations: {
|
|
'2': {
|
|
buckets: [
|
|
{
|
|
doc_count: 10,
|
|
key: 1000,
|
|
},
|
|
{
|
|
doc_count: 15,
|
|
key: 2000,
|
|
},
|
|
],
|
|
},
|
|
},
|
|
hits: {
|
|
hits: [
|
|
{
|
|
_id: 'fdsfs',
|
|
_type: '_doc',
|
|
_index: 'mock-index',
|
|
_source: {
|
|
'@timestamp': '2019-06-24T09:51:19.765Z',
|
|
host: 'djisaodjsoad',
|
|
message: 'hello, i am a message',
|
|
level: 'debug',
|
|
fields: {
|
|
lvl: 'debug',
|
|
},
|
|
},
|
|
},
|
|
{
|
|
_id: 'kdospaidopa',
|
|
_type: '_doc',
|
|
_index: 'mock-index',
|
|
_source: {
|
|
'@timestamp': '2019-06-24T09:52:19.765Z',
|
|
host: 'dsalkdakdop',
|
|
message: 'hello, i am also message',
|
|
level: 'error',
|
|
fields: {
|
|
lvl: 'info',
|
|
},
|
|
},
|
|
},
|
|
],
|
|
},
|
|
},
|
|
],
|
|
};
|
|
|
|
it('should return histogram aggregation and documents', () => {
|
|
const result = new ElasticResponse(targets, response).getLogs();
|
|
expect(result.data.length).toBe(2);
|
|
const logResults = result.data[0] as MutableDataFrame;
|
|
const fields = logResults.fields.map(f => {
|
|
return {
|
|
name: f.name,
|
|
type: f.type,
|
|
};
|
|
});
|
|
|
|
expect(fields).toContainEqual({ name: '@timestamp', type: 'time' });
|
|
expect(fields).toContainEqual({ name: 'host', type: 'string' });
|
|
expect(fields).toContainEqual({ name: 'message', type: 'string' });
|
|
|
|
let rows = new DataFrameView(logResults);
|
|
for (let i = 0; i < rows.length; i++) {
|
|
const r = rows.get(i);
|
|
expect(r._id).toEqual(response.responses[0].hits.hits[i]._id);
|
|
expect(r._type).toEqual(response.responses[0].hits.hits[i]._type);
|
|
expect(r._index).toEqual(response.responses[0].hits.hits[i]._index);
|
|
expect(r._source).toEqual(
|
|
flatten(
|
|
response.responses[0].hits.hits[i]._source,
|
|
(null as unknown) as { delimiter?: any; maxDepth?: any; safe?: any }
|
|
)
|
|
);
|
|
}
|
|
|
|
// Make a map from the histogram results
|
|
const hist: KeyValue<number> = {};
|
|
const histogramResults = new MutableDataFrame(result.data[1]);
|
|
rows = new DataFrameView(histogramResults);
|
|
|
|
for (let i = 0; i < rows.length; i++) {
|
|
const row = rows.get(i);
|
|
hist[row.Time] = row.Value;
|
|
}
|
|
|
|
response.responses[0].aggregations['2'].buckets.forEach((bucket: any) => {
|
|
expect(hist[bucket.key]).toEqual(bucket.doc_count);
|
|
});
|
|
});
|
|
|
|
it('should map levels field', () => {
|
|
const result = new ElasticResponse(targets, response).getLogs(undefined, 'level');
|
|
const fieldCache = new FieldCache(result.data[0]);
|
|
const field = fieldCache.getFieldByName('level');
|
|
expect(field?.values.toArray()).toEqual(['debug', 'error']);
|
|
});
|
|
|
|
it('should re map levels field to new field', () => {
|
|
const result = new ElasticResponse(targets, response).getLogs(undefined, 'fields.lvl');
|
|
const fieldCache = new FieldCache(result.data[0]);
|
|
const field = fieldCache.getFieldByName('level');
|
|
expect(field?.values.toArray()).toEqual(['debug', 'info']);
|
|
});
|
|
});
|
|
});
|