# export to new table. 

# Copyright 2020 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.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

name: Bigquery - Query
description: |
  A Kubeflow Pipeline component to submit a query to Google Cloud Bigquery 
  service and dump outputs to new table.
metadata:
  labels:
    add-pod-env: 'true'
inputs:
  - name: query
    description: 'The query used by Bigquery service to fetch the results.'
    type: String
  - name: project_id
    description: 'The project to execute the query job.'
    type: GCPProjectID
  - name: dataset_id
    description: 'The ID of the persistent dataset to keep the results of the query.'
    default: ''
    type: String
  - name: table_id
    description: >-
      The ID of the table to keep the results of the query. If absent, the operation
      will generate a random id for the table.
    default: '' 
    type: String
  - name: dataset_location
    description: 'The location to create the dataset. Defaults to `US`.'
    default: 'US'
    type: String
  - name: job_config
    description: >-
      The full config spec for the query job.See 
      [QueryJobConfig](https://googleapis.github.io/google-cloud-python/latest/bigquery/generated/google.cloud.bigquery.job.QueryJobConfig.html#google.cloud.bigquery.job.QueryJobConfig) 
      for details.
    default: ''
    type: Dict
outputs:
  - name: MLPipeline UI metadata
    type: UI metadata
implementation:
  container:
    image: gcr.io/ml-pipeline/ml-pipeline-gcp:1.7.0-rc.3
    args: [
      --ui_metadata_path, {outputPath: MLPipeline UI metadata},
      kfp_component.google.bigquery, query,
      --query, {inputValue: query},
      --project_id, {inputValue: project_id},
      --dataset_id, {inputValue: dataset_id},
      --table_id, {inputValue: table_id},
      --dataset_location, {inputValue: dataset_location},
      --job_config, {inputValue: job_config},
    ]
    env:
      KFP_POD_NAME: "{{pod.name}}"