# Copyright 2022 Google LLC
#
# 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.


from airflow import DAG
from airflow.operators import bash
from airflow.providers.google.cloud.operators import kubernetes_engine
from airflow.providers.google.cloud.transfers import gcs_to_bigquery

default_args = {
    "owner": "Google",
    "depends_on_past": False,
    "start_date": "2021-03-01",
}


with DAG(
    dag_id="imdb.reviews",
    default_args=default_args,
    max_active_runs=1,
    schedule_interval="@once",
    catchup=False,
    default_view="graph",
) as dag:
    create_cluster = kubernetes_engine.GKECreateClusterOperator(
        task_id="create_cluster",
        project_id="{{ var.value.gcp_project }}",
        location="us-central1-c",
        body={
            "name": "pdp-imdb-reviews",
            "initial_node_count": 1,
            "network": "{{ var.value.vpc_network }}",
            "node_config": {
                "machine_type": "e2-standard-16",
                "oauth_scopes": [
                    "https://www.googleapis.com/auth/devstorage.read_write",
                    "https://www.googleapis.com/auth/cloud-platform",
                ],
            },
        },
    )

    # Task to copy `reviews` to gcs
    download_zip_file = bash.BashOperator(
        task_id="download_zip_file",
        bash_command="mkdir -p $data_dir/imdb/reviews\ncurl -o $data_dir/imdb/reviews/aclImdb_v1.tar.gz -L $reviews\n",
        env={
            "data_dir": "/home/airflow/gcs/data",
            "reviews": "https://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz",
        },
    )

    # Run CSV transform within kubernetes pod
    reviews_transform_csv = kubernetes_engine.GKEStartPodOperator(
        task_id="reviews_transform_csv",
        startup_timeout_seconds=600,
        name="reviews",
        namespace="default",
        project_id="{{ var.value.gcp_project }}",
        location="us-central1-c",
        cluster_name="pdp-imdb-reviews",
        image_pull_policy="Always",
        image="{{ var.json.imdb.container_registry.run_csv_transform_kub }}",
        env_vars={
            "SOURCE_GCS_BUCKET": "{{ var.value.composer_bucket }}",
            "SOURCE_GCS_OBJECT": "data/imdb/reviews/aclImdb_v1.tar.gz",
            "SOURCE_URL": '{"title_link": "https://datasets.imdbws.com/title.basics.tsv.gz"}',
            "SOURCE_FILE": '{"user_review_data": "./files/aclImdb_v1.tar.gz", "title_data": "./files/title_basics.tsv.gz"}',
            "EXTRACT_HERE": "./files",
            "TARGET_CSV_FILE": "./files/data_output.csv",
            "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}",
            "TARGET_GCS_PATH": "data/imdb/reviews/data_output.csv",
            "PIPELINE_NAME": "reviews",
            "CSV_HEADERS": '["review", "split", "label", "movie_id", "reviewer_rating", "movie_url", "title"]',
            "RENAME_MAPPINGS": '{"review": "review", "split": "split", "label": "label", "movie_id": "movie_id", "reviewer_rating": "reviewer_rating", "movie_url": "movie_url", "title": "title"}',
        },
    )
    delete_cluster = kubernetes_engine.GKEDeleteClusterOperator(
        task_id="delete_cluster",
        project_id="{{ var.value.gcp_project }}",
        location="us-central1-c",
        name="pdp-imdb-reviews",
    )

    # Task to load CSV data to a BigQuery table
    load_reviews_to_bq = gcs_to_bigquery.GCSToBigQueryOperator(
        task_id="load_reviews_to_bq",
        bucket="{{ var.value.composer_bucket }}",
        source_objects=["data/imdb/reviews/data_output.csv"],
        source_format="CSV",
        destination_project_dataset_table="imdb.reviews",
        skip_leading_rows=1,
        allow_quoted_newlines=True,
        write_disposition="WRITE_TRUNCATE",
        schema_fields=[
            {
                "name": "review",
                "type": "STRING",
                "description": "User review's in IMDb.",
                "mode": "NULLABLE",
            },
            {
                "name": "split",
                "type": "STRING",
                "description": "It has two categories test and train.",
                "mode": "NULLABLE",
            },
            {
                "name": "label",
                "type": "STRING",
                "description": "It has three categories Negative, Positive and Unsupervised. All Unsupervised label has only split equals-to train.",
                "mode": "NULLABLE",
            },
            {
                "name": "movie_id",
                "type": "STRING",
                "description": "UniqueId for the movie in IMDb.",
                "mode": "NULLABLE",
            },
            {
                "name": "reviewer_rating",
                "type": "INTEGER",
                "description": "Reviewer rating for particular movie in IMDb. For train-unsupervised, reviewer_rating is NULL.",
                "mode": "NULLABLE",
            },
            {
                "name": "movie_url",
                "type": "STRING",
                "description": "Movie url for corresponding movie_id",
                "mode": "NULLABLE",
            },
            {
                "name": "title",
                "type": "STRING",
                "description": "Title of the movie for corresponding movie_id",
                "mode": "NULLABLE",
            },
        ],
    )

    (
        create_cluster
        >> download_zip_file
        >> reviews_transform_csv
        >> delete_cluster
        >> load_reviews_to_bq
    )