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

from google_cloud_pipeline_components.container.v1.bigquery.utils import bigquery_util


def bigquery_ml_recommend_job(
    type,
    project,
    location,
    model_name,
    table_name,
    query_statement,
    payload,
    job_configuration_query_override,
    gcp_resources,
    executor_input,
):
  """Create and poll bigquery ML Recommend 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 model ML Recommend 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 recommendation evaluation. For more
        details, see
      https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-recommend#recommend_model_name
      table_name: BigQuery table id of the input table that contains the user
        and/or item data. For more details, see
        https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-recommend#recommend_table_name
      query_statement: query statement string used to generate the evaluation
        data. For more details, see
        https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-recommend#recommend_query_statement
      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 query_statement and table_name:
    raise ValueError(
        'One and only one of query_statement and table_name should be '
        'populated for BigQuery ML Recommend job.'
    )

  input_data_sql = ''
  if table_name:
    input_data_sql = ', TABLE %s' % bigquery_util.back_quoted_if_needed(
        table_name
    )
  if query_statement:
    input_data_sql = ', (%s)' % query_statement

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

  return bigquery_util.bigquery_query_job(
      type,
      project,
      location,
      payload,
      json.dumps(job_configuration_query_override_json),
      gcp_resources,
      executor_input,
  )
