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[ML] Trained models list: disables 'View training data' action if data frame analytics job no longer exists #171061

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merged 8 commits into from
Nov 21, 2023
Merged

[ML] Trained models list: disables 'View training data' action if data frame analytics job no longer exists #171061

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a407ee2
disable View Training Data if original job no longer exists
alvarezmelissa87 Nov 10, 2023
7c06abd
check all jobs exist at once. check permissions
alvarezmelissa87 Nov 13, 2023
6d8a4e5
create ViewTrainingData to wrap disabled action in tooltip
alvarezmelissa87 Nov 13, 2023
12f1a01
Merge branch 'main' into ml-dfa-view-training
kibanamachine Nov 13, 2023
50ffcfd
refactor origin_job_exists check
alvarezmelissa87 Nov 15, 2023
8c7094d
update types and fix action in column
alvarezmelissa87 Nov 15, 2023
3bc2c8d
Merge branch 'main' into ml-dfa-view-training
kibanamachine Nov 15, 2023
73216d0
ensure job id string is corrrect
alvarezmelissa87 Nov 16, 2023
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1 change: 1 addition & 0 deletions x-pack/plugins/ml/common/types/trained_models.ts
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Expand Up @@ -98,6 +98,7 @@ export type TrainedModelConfigResponse = estypes.MlTrainedModelConfig & {
* Associated pipelines. Extends response from the ES endpoint.
*/
pipelines?: Record<string, PipelineDefinition> | null;
origin_job_exists?: boolean;
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@jgowdyelastic jgowdyelastic Nov 13, 2023 •
edited
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I don't think this needs to be optional route param. We should always perform this check when retrieving the models as it's useful information.

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Updated in 7c06abd


metadata?: {
analytics_config: DataFrameAnalyticsConfig;
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6 changes: 3 additions & 3 deletions x-pack/plugins/ml/public/application/model_management/model_actions.tsx
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Expand Up @@ -130,18 +130,19 @@ export function useModelActions({
return useMemo(
() => [
{
name: i18n.translate('xpack.ml.trainedModels.modelsList.viewTrainingDataActionLabel', {
name: i18n.translate('xpack.ml.trainedModels.modelsList.viewTrainingDataNameActionLabel', {
defaultMessage: 'View training data',
}),
description: i18n.translate(
'xpack.ml.trainedModels.modelsList.viewTrainingDataActionLabel',
{
defaultMessage: 'View training data',
defaultMessage: 'Training data can be viewed when data frame analytics job exists.',
}
),
icon: 'visTable',
type: 'icon',
available: (item) => !!item.metadata?.analytics_config?.id,
enabled: (item) => item.origin_job_exists === true,
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Can you add a tooltip to show why the action is disabled.

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@alvarezmelissa87 alvarezmelissa87 Nov 13, 2023 •
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Added in 6d8a4e5
Happy to get suggestions on the copy to use.
image

onClick: async (item) => {
if (item.metadata?.analytics_config === undefined) return;

Expand All @@ -164,7 +165,6 @@ export function useModelActions({

await navigateToUrl(url);
},
isPrimary: true,
},
{
name: i18n.translate('xpack.ml.inference.modelsList.analyticsMapActionLabel', {
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1 change: 1 addition & 0 deletions x-pack/plugins/ml/public/application/model_management/models_list.tsx
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Expand Up @@ -79,6 +79,7 @@ export type ModelItem = TrainedModelConfigResponse & {
type?: string[];
stats?: Stats & { deployment_stats: TrainedModelDeploymentStatsResponse[] };
pipelines?: ModelPipelines['pipelines'] | null;
origin_job_exists?: boolean;
deployment_ids: string[];
putModelConfig?: object;
state: ModelState;
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42 changes: 34 additions & 8 deletions x-pack/plugins/ml/server/routes/trained_models.ts
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Expand Up @@ -29,20 +29,19 @@ import {
createIngestPipelineSchema,
modelDownloadsQuery,
} from './schemas/inference_schema';
import type {
import {
PipelineDefinition,
TrainedModelConfigResponse,
type TrainedModelConfigResponse,
} from '../../common/types/trained_models';
import { mlLog } from '../lib/log';
import { forceQuerySchema } from './schemas/anomaly_detectors_schema';
import { modelsProvider } from '../models/model_management';

export const DEFAULT_TRAINED_MODELS_PAGE_SIZE = 10000;

export function filterForEnabledFeatureModels(
models: TrainedModelConfigResponse[] | estypes.MlTrainedModelConfig[],
enabledFeatures: MlFeatures
) {
export function filterForEnabledFeatureModels<
T extends TrainedModelConfigResponse | estypes.MlTrainedModelConfig
>(models: T[], enabledFeatures: MlFeatures) {
let filteredModels = models;
if (enabledFeatures.nlp === false) {
filteredModels = filteredModels.filter((m) => m.model_type === 'tree_ensemble');
Expand Down Expand Up @@ -191,10 +190,37 @@ export function trainedModelsRoutes(
mlLog.debug(e);
}

const body = filterForEnabledFeatureModels(result, getEnabledFeatures());
const filteredModels = filterForEnabledFeatureModels(result, getEnabledFeatures());

try {
const jobIdsString = filteredModels.reduce((jobIdsStr, currentModel, idx) => {
let id = currentModel.metadata?.analytics_config?.id ?? '';
if (id !== '') {
id = `${idx > 0 ? ',' : ''}${id}*`;
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@jgowdyelastic jgowdyelastic Nov 16, 2023 •
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This has a bug where if idx is > 0 but no dfa jobs have yet to be found it'll add a comma to the front of the string which then causes the loading of dfa jobs to fail.
Rather than looking for idx > 0, it should to checking to see if jobIdsStr is empty.
I know it was my suggestion to use a reduce but I think it was bad advice as it has caused this bug due to the code being hard to read. For the sake of easy to read code maybe we should revert back to a map, filter, join.

Something like

const jobIds = filteredModels
  .map((m) => m.metadata?.analytics_config?.id)
  .filter(isDefined)
  .map((id) => `${id}*`);

if (jobIds.length) {
  const { data_frame_analytics: jobs } = await mlClient.getDataFrameAnalytics({
    id: jobIds.join(','),
    allow_no_match: true,
  });

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Agree - updated in 73216d0

}
return `${jobIdsStr}${id}`;
}, '');

if (jobIdsString !== '') {
const { data_frame_analytics: jobs } = await mlClient.getDataFrameAnalytics({
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id: jobIdsString,
allow_no_match: true,
});

filteredModels.forEach((model) => {
const dfaId = model?.metadata?.analytics_config?.id;
if (dfaId !== undefined) {
// if this is a dfa model, set origin_job_exists
model.origin_job_exists = jobs.find((job) => job.id === dfaId) !== undefined;
}
});
}
} catch (e) {
// Swallow error to prevent blocking trained models result
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}

return response.ok({
body,
body: filteredModels,
});
} catch (e) {
return response.customError(wrapError(e));
Expand Down