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# Licensed under the Apache License, Version 2.0 (the "License");
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import json
import logging

import google.auth
import google.auth.transport.requests
from google_cloud_pipeline_components.container.utils import artifact_utils
from google_cloud_pipeline_components.container.v1.bigquery.utils import bigquery_util


def bigquery_ml_arima_evaluate_job(
    type,
    project,
    location,
    model_name,
    show_all_candidate_models,
    payload,
    job_configuration_query_override,
    gcp_resources,
    executor_input,
):
  """Create and poll BigQuery ML.ARIMA_EVALUATE job till it reaches a final state.

  This follows the typical launching logic:
  1. Read if the bigquery job already exists in gcp_resources
     - If already exists, jump to step 3 and poll the job status. This happens
     if the launcher container experienced unexpected termination, such as
     preemption
  2. Deserialize the payload into the job spec and create the bigquery job
  3. Poll the bigquery job status every
  job_remote_runner._POLLING_INTERVAL_IN_SECONDS seconds
     - If the bigquery job is succeeded, return succeeded
     - If the bigquery job is pending/running, continue polling the status

  Also retry on ConnectionError up to
  job_remote_runner._CONNECTION_ERROR_RETRY_LIMIT times during the poll.


  Args:
      type: BigQuery ML.ARIMA_EVALUATE job type.
      project: Project to launch the query job.
      location: location to launch the query job. For more details, see
        https://cloud.google.com/bigquery/docs/locations#specifying_your_location
      model_name: BigQuery ML model name for prediction. For more details, see
        https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-predict#predict_model_name
      show_all_candidate_models: 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. For more details, see
        https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-arima-evaluate#show_all_candidate_models
      payload: A json serialized Job proto. For more details, see
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job
      job_configuration_query_override: A json serialized JobConfigurationQuery
        proto. For more details, see
        https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobConfigurationQuery
      gcp_resources: File path for storing `gcp_resources` output parameter.
      executor_input:A json serialized pipeline executor input.
  """
  if show_all_candidate_models:
    show_all_candidate_models_sql = (
        ', STRUCT(%s AS show_all_candidate_models)' % show_all_candidate_models
    )

  job_configuration_query_override_json = json.loads(
      job_configuration_query_override, strict=False
  )
  job_configuration_query_override_json['query'] = (
      'SELECT * FROM ML.ARIMA_EVALUATE(MODEL %s%s)'
      % (
          bigquery_util.back_quoted_if_needed(model_name),
          show_all_candidate_models_sql,
      )
  )

  creds, _ = google.auth.default()
  job_uri = bigquery_util.check_if_job_exists(gcp_resources)
  if job_uri is None:
    job_uri = bigquery_util.create_query_job(
        project,
        location,
        payload,
        json.dumps(job_configuration_query_override_json),
        creds,
        gcp_resources,
    )

  # Poll bigquery job status until finished.
  job = bigquery_util.poll_job(job_uri, creds)
  logging.info('Getting query result for job ' + job['id'])
  _, job_id = job['id'].split('.')
  query_results = bigquery_util.get_query_results(
      project, job_id, location, creds
  )
  artifact_utils.update_output_artifact(
      executor_input,
      'arima_evaluation_metrics',
      '',
      {
          bigquery_util.ARTIFACT_PROPERTY_KEY_SCHEMA: query_results[
              bigquery_util.ARTIFACT_PROPERTY_KEY_SCHEMA
          ],
          bigquery_util.ARTIFACT_PROPERTY_KEY_ROWS: query_results[
              bigquery_util.ARTIFACT_PROPERTY_KEY_ROWS
          ],
      },
  )
