# Copyright 2021 The Kubeflow Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
#      http://www.apache.org/licenses/LICENSE-2.0
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# distributed under the License is distributed on an "AS IS" BASIS,
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name: bigquery_ml_arima_evaluate_job
description: |
  Launch a BigQuery ML.ARIMA_EVALUATE job and waits for it to finish.
    Args:
        project (str):
            Required. Project to run BigQuery model evaluation job.
        location (Optional[str]):
            Location to run the BigQuery model evaluation job. If not set,
            default to `US` multi-region.
            For more details, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location
        model (google.BQMLModel):
            Required. BigQuery ML model for ML.ARIMA_EVALUATE.
            For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#model_name
        show_all_candidate_models (Optional[bool]):
            You can use show_all_candidate_models to show evaluation metrics or an error message
            for either all candidate models or for only the best model with the lowest AIC. The
            value is type BOOL and is part of the settings STRUCT.
            For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#show_all_candidate_models
        query_parameters (Optional[Sequence]):
            jobs.query parameters for standard SQL queries.
            If query_parameters are both specified in here and in job_configuration_query,
            the value in here will override the other one.
        job_configuration_query (Optional[dict]):
            A json formatted string describing the rest of the job configuration.
            For more details, see https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery
        labels (Optional[dict]):
            The labels associated with this job. You can use these to organize and group your jobs.
            Label keys and values can be no longer than 63 characters, can only containlowercase
            letters, numeric characters, underscores and dashes. International characters are
            allowed. Label values are optional. Label keys must start with a letter and each label
            in the list must have a different key.
            Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
        encryption_spec_key_name(Optional[List[str]]):
            Describes the Cloud KMS encryption key that will be used to protect
            destination BigQuery table. The BigQuery Service Account associated with
            your project requires access to this encryption key.
            If encryption_spec_key_name are both specified in here and in job_configuration_query,
            the value in here will override the other one.
    Returns:
        arima_evaluation_metrics (system.Artifact):
          Describes arima metrics.
          For more details, see https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#mlarima_evaluate_output
        gcp_resources (str):
            Serialized gcp_resources proto tracking the BigQuery job.
            For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.
inputs:
  - { name: project, type: String }
  - { name: location, type: String, default: "us-central1" }
  - { name: model, type: google.BQMLModel }
  - { name: show_all_candidate_models, type: Boolean, optional: true, default: "false" }
  - { name: query_parameters, type: JsonArray, optional: true, default: '[]' }
  - { name: job_configuration_query, type: JsonObject, optional: true, default: '{}'}
  - { name: labels, type: JsonArray, optional: true, default: '[]'}
  - { name: encryption_spec_key_name, type: String, optional: true}
outputs:
  - { name: arima_evaluation_metrics, type: system.Artifact }
  - { name: gcp_resources, type: String }
implementation:
  container:
    image: gcr.io/ml-pipeline/google-cloud-pipeline-components:2.0.0b1
    command:
      [
        python3,
        -u,
        -m,
        google_cloud_pipeline_components.container.v1.bigquery.ml_arima_evaluate.launcher,
      ]
    args:
      [
        --type,
        BigqueryMLArimaEvaluateJob,
        --project,
        { inputValue: project },
        --location,
        { inputValue: location },
        --model_name,
        concat:
          [
            "{{$.inputs.artifacts['model'].metadata['projectId']}}",
            ".",
            "{{$.inputs.artifacts['model'].metadata['datasetId']}}",
            ".",
            "{{$.inputs.artifacts['model'].metadata['modelId']}}",
          ],
        --show_all_candidate_models,
        { inputValue: show_all_candidate_models },
        --payload,
        concat: [
            '{',
              '"configuration": {',
                '"query": ', {inputValue: job_configuration_query},
                ', "labels": ', {inputValue: labels},
              '}',
            '}'
        ],
        --job_configuration_query_override,
        concat: [
            '{',
              '"query_parameters": ', {inputValue: query_parameters},
              ', "destination_encryption_configuration": {',
              '"kmsKeyName": "', {inputValue: encryption_spec_key_name}, '"}',
            '}'
        ],
        --gcp_resources,
        { outputPath: gcp_resources },
        --executor_input,
        "{{$}}",
      ]
