Source code for tests.system.providers.google.cloud.bigquery.example_bigquery_transfer

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"""
Example Airflow DAG for Google BigQuery service.
"""

from __future__ import annotations

import os
from datetime import datetime

from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.bigquery import (
    BigQueryCreateEmptyDatasetOperator,
    BigQueryCreateEmptyTableOperator,
    BigQueryDeleteDatasetOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.transfers.bigquery_to_bigquery import BigQueryToBigQueryOperator
from airflow.providers.google.cloud.transfers.bigquery_to_gcs import BigQueryToGCSOperator
from airflow.utils.trigger_rule import TriggerRule
from tests.system.providers.google import DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID


[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")


[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID


[docs]DAG_ID = "example_bigquery_transfer"



[docs]DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}"


[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"



[docs]ORIGIN = "origin"


[docs]TARGET = "target"


with DAG(
    DAG_ID,
    schedule="@once",  # Override to match your needs
    start_date=datetime(2021, 1, 1),
    catchup=False,
    tags=["example", "bigquery"],
) as dag:

[docs]    create_bucket = GCSCreateBucketOperator(
        task_id="create_bucket", bucket_name=BUCKET_NAME, project_id=PROJECT_ID
    )


    create_dataset = BigQueryCreateEmptyDatasetOperator(task_id="create_dataset", dataset_id=DATASET_NAME)

    create_origin_table = BigQueryCreateEmptyTableOperator(
        task_id=f"create_{ORIGIN}_table",
        dataset_id=DATASET_NAME,
        table_id=ORIGIN,
        schema_fields=[
            {"name": "emp_name", "type": "STRING", "mode": "REQUIRED"},
            {"name": "salary", "type": "INTEGER", "mode": "NULLABLE"},
        ],
    )

    create_target_table = BigQueryCreateEmptyTableOperator(
        task_id=f"create_{TARGET}_table",
        dataset_id=DATASET_NAME,
        table_id=TARGET,
        schema_fields=[
            {"name": "emp_name", "type": "STRING", "mode": "REQUIRED"},
            {"name": "salary", "type": "INTEGER", "mode": "NULLABLE"},
        ],
    )

    copy_selected_data = BigQueryToBigQueryOperator(
        task_id="copy_selected_data",
        source_project_dataset_tables=f"{DATASET_NAME}.{ORIGIN}",
        destination_project_dataset_table=f"{DATASET_NAME}.{TARGET}",
    )

    bigquery_to_gcs = BigQueryToGCSOperator(
        task_id="bigquery_to_gcs",
        source_project_dataset_table=f"{DATASET_NAME}.{ORIGIN}",
        destination_cloud_storage_uris=[f"gs://{BUCKET_NAME}/export-bigquery.csv"],
    )

    delete_dataset = BigQueryDeleteDatasetOperator(
        task_id="delete_dataset",
        dataset_id=DATASET_NAME,
        delete_contents=True,
        trigger_rule=TriggerRule.ALL_DONE,
    )

    delete_bucket = GCSDeleteBucketOperator(
        task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE
    )

    (
        # TEST SETUP
        create_bucket
        >> create_dataset
        >> create_origin_table
        >> create_target_table
        # TEST BODY
        >> copy_selected_data
        >> bigquery_to_gcs
        # TEST TEARDOWN
        >> delete_dataset
        >> delete_bucket
    )

    from tests.system.utils.watcher import watcher

    # This test needs watcher in order to properly mark success/failure
    # when "tearDown" task with trigger rule is part of the DAG
    list(dag.tasks) >> watcher()

from tests.system.utils import get_test_run  # noqa: E402

# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)

[docs]test_run = get_test_run(dag)

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