-
Notifications
You must be signed in to change notification settings - Fork 8.2k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
* [ML] clone analytics job * [ML] flyout clone header * [ML] improve clone action context menu item * [ML] support advanced job cloning * [ML] extractCloningConfig * [ML] fix isAdvancedSetting condition, add test * [ML] clone job header * [ML] job description placeholder * [ML] setEstimatedModelMemoryLimit on source index change * [ML] Fix types. * [ML] useUpdateEffect in create_analytics_form.tsx * [ML] setJobClone action * [ML] remove CreateAnalyticsFlyoutWrapper instance from the create_analytics_button.tsx * [ML] fix types * [ML] hack to align Clone button with the other actions * [ML] unknown props lead to advanced editor * [ML] rename maximum_number_trees ot max_trees * [ML] fix forceInput * [ML] populate excludesOptions on the first update, skip setting mml on the fist update * [ML] init functional test for cloning analytics jobs * [ML] functional tests * [ML] fix functional tests imports * [ML] fix indices names for functional tests * [ML] functional tests for outlier detection and regression jobs cloning * [ML] delete james tag * [ML] fix tests arrangement Co-authored-by: Walter Rafelsberger <[email protected]>
- Loading branch information
Showing
26 changed files
with
1,132 additions
and
105 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
254 changes: 254 additions & 0 deletions
254
...frame_analytics/pages/analytics_management/components/analytics_list/action_clone.test.ts
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,254 @@ | ||
| /* | ||
| * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one | ||
| * or more contributor license agreements. Licensed under the Elastic License; | ||
| * you may not use this file except in compliance with the Elastic License. | ||
| */ | ||
|
|
||
| import { isAdvancedConfig } from './action_clone'; | ||
|
|
||
| describe('Analytics job clone action', () => { | ||
| describe('isAdvancedConfig', () => { | ||
| test('should detect a classification job created with the form', () => { | ||
| const formCreatedClassificationJob = { | ||
| description: "Classification job with 'bank-marketing' dataset", | ||
| source: { | ||
| index: ['bank-marketing'], | ||
| query: { | ||
| match_all: {}, | ||
| }, | ||
| }, | ||
| dest: { | ||
| index: 'dest_bank_1', | ||
| results_field: 'ml', | ||
| }, | ||
| analysis: { | ||
| classification: { | ||
| dependent_variable: 'y', | ||
| num_top_classes: 2, | ||
| prediction_field_name: 'y_prediction', | ||
| training_percent: 2, | ||
| randomize_seed: 6233212276062807000, | ||
| }, | ||
| }, | ||
| analyzed_fields: { | ||
| includes: [], | ||
| excludes: [], | ||
| }, | ||
| model_memory_limit: '350mb', | ||
| allow_lazy_start: false, | ||
| }; | ||
|
|
||
| expect(isAdvancedConfig(formCreatedClassificationJob)).toBe(false); | ||
| }); | ||
|
|
||
| test('should detect a outlier_detection job created with the form', () => { | ||
| const formCreatedOutlierDetectionJob = { | ||
| description: "Outlier detection job with 'glass' dataset", | ||
| source: { | ||
| index: ['glass_withoutdupl_norm'], | ||
| query: { | ||
| match_all: {}, | ||
| }, | ||
| }, | ||
| dest: { | ||
| index: 'dest_glass_1', | ||
| results_field: 'ml', | ||
| }, | ||
| analysis: { | ||
| outlier_detection: { | ||
| compute_feature_influence: true, | ||
| outlier_fraction: 0.05, | ||
| standardization_enabled: true, | ||
| }, | ||
| }, | ||
| analyzed_fields: { | ||
| includes: [], | ||
| excludes: ['id', 'outlier'], | ||
| }, | ||
| model_memory_limit: '1mb', | ||
| allow_lazy_start: false, | ||
| }; | ||
| expect(isAdvancedConfig(formCreatedOutlierDetectionJob)).toBe(false); | ||
| }); | ||
|
|
||
| test('should detect a regression job created with the form', () => { | ||
| const formCreatedRegressionJob = { | ||
| description: "Regression job with 'electrical-grid-stability' dataset", | ||
| source: { | ||
| index: ['electrical-grid-stability'], | ||
| query: { | ||
| match_all: {}, | ||
| }, | ||
| }, | ||
| dest: { | ||
| index: 'dest_grid_1', | ||
| results_field: 'ml', | ||
| }, | ||
| analysis: { | ||
| regression: { | ||
| dependent_variable: 'stab', | ||
| prediction_field_name: 'stab_prediction', | ||
| training_percent: 20, | ||
| randomize_seed: -2228827740028660200, | ||
| }, | ||
| }, | ||
| analyzed_fields: { | ||
| includes: [], | ||
| excludes: [], | ||
| }, | ||
| model_memory_limit: '150mb', | ||
| allow_lazy_start: false, | ||
| }; | ||
|
|
||
| expect(isAdvancedConfig(formCreatedRegressionJob)).toBe(false); | ||
| }); | ||
|
|
||
| test('should detect advanced classification job', () => { | ||
| const advancedClassificationJob = { | ||
| description: "Classification job with 'bank-marketing' dataset", | ||
| source: { | ||
| index: ['bank-marketing'], | ||
| query: { | ||
| match_all: {}, | ||
| }, | ||
| }, | ||
| dest: { | ||
| index: 'dest_bank_1', | ||
| results_field: 'CUSTOM_RESULT_FIELD', | ||
| }, | ||
| analysis: { | ||
| classification: { | ||
| dependent_variable: 'y', | ||
| num_top_classes: 2, | ||
| prediction_field_name: 'y_prediction', | ||
| training_percent: 2, | ||
| randomize_seed: 6233212276062807000, | ||
| }, | ||
| }, | ||
| analyzed_fields: { | ||
| includes: [], | ||
| excludes: [], | ||
| }, | ||
| model_memory_limit: '350mb', | ||
| allow_lazy_start: false, | ||
| }; | ||
|
|
||
| expect(isAdvancedConfig(advancedClassificationJob)).toBe(true); | ||
| }); | ||
|
|
||
| test('should detect advanced outlier_detection job', () => { | ||
| const advancedOutlierDetectionJob = { | ||
| description: "Outlier detection job with 'glass' dataset", | ||
| source: { | ||
| index: ['glass_withoutdupl_norm'], | ||
| query: { | ||
| // TODO check default for `match` | ||
| match_all: {}, | ||
| }, | ||
| }, | ||
| dest: { | ||
| index: 'dest_glass_1', | ||
| results_field: 'ml', | ||
| }, | ||
| analysis: { | ||
| outlier_detection: { | ||
| compute_feature_influence: false, | ||
| outlier_fraction: 0.05, | ||
| standardization_enabled: true, | ||
| }, | ||
| }, | ||
| analyzed_fields: { | ||
| includes: [], | ||
| excludes: ['id', 'outlier'], | ||
| }, | ||
| model_memory_limit: '1mb', | ||
| allow_lazy_start: false, | ||
| }; | ||
| expect(isAdvancedConfig(advancedOutlierDetectionJob)).toBe(true); | ||
| }); | ||
|
|
||
| test('should detect a custom query', () => { | ||
| const advancedRegressionJob = { | ||
| description: "Regression job with 'electrical-grid-stability' dataset", | ||
| source: { | ||
| index: ['electrical-grid-stability'], | ||
| query: { | ||
| match: { | ||
| custom_field: 'custom_match', | ||
| }, | ||
| }, | ||
| }, | ||
| dest: { | ||
| index: 'dest_grid_1', | ||
| results_field: 'ml', | ||
| }, | ||
| analysis: { | ||
| regression: { | ||
| dependent_variable: 'stab', | ||
| prediction_field_name: 'stab_prediction', | ||
| training_percent: 20, | ||
| randomize_seed: -2228827740028660200, | ||
| }, | ||
| }, | ||
| analyzed_fields: { | ||
| includes: [], | ||
| excludes: [], | ||
| }, | ||
| model_memory_limit: '150mb', | ||
| allow_lazy_start: false, | ||
| }; | ||
|
|
||
| expect(isAdvancedConfig(advancedRegressionJob)).toBe(true); | ||
| }); | ||
|
|
||
| test('should detect custom analysis settings', () => { | ||
| const config = { | ||
| description: "Classification clone with 'bank-marketing' dataset", | ||
| source: { | ||
| index: 'bank-marketing', | ||
| }, | ||
| dest: { | ||
| index: 'bank_classification4', | ||
| }, | ||
| analyzed_fields: { | ||
| excludes: [], | ||
| }, | ||
| analysis: { | ||
| classification: { | ||
| dependent_variable: 'y', | ||
| training_percent: 71, | ||
| max_trees: 1500, | ||
| }, | ||
| }, | ||
| model_memory_limit: '400mb', | ||
| }; | ||
|
|
||
| expect(isAdvancedConfig(config)).toBe(true); | ||
| }); | ||
|
|
||
| test('should detect as advanced if the prop is unknown', () => { | ||
| const config = { | ||
| description: "Classification clone with 'bank-marketing' dataset", | ||
| source: { | ||
| index: 'bank-marketing', | ||
| }, | ||
| dest: { | ||
| index: 'bank_classification4', | ||
| }, | ||
| analyzed_fields: { | ||
| excludes: [], | ||
| }, | ||
| analysis: { | ||
| classification: { | ||
| dependent_variable: 'y', | ||
| training_percent: 71, | ||
| maximum_number_trees: 1500, | ||
| }, | ||
| }, | ||
| model_memory_limit: '400mb', | ||
| }; | ||
|
|
||
| expect(isAdvancedConfig(config)).toBe(true); | ||
| }); | ||
| }); | ||
| }); |
Oops, something went wrong.