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"""
Example Airflow DAG for Google Cloud Dataflow 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,
BigQueryDeleteTableOperator,
BigQueryInsertJobOperator,
)
from airflow.providers.google.cloud.operators.dataflow import DataflowStartSqlJobOperator
from airflow.utils.trigger_rule import TriggerRule
from providers.tests.system.google import DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]LOCATION = "europe-west3"
[docs]DATAFLOW_SQL_JOB_NAME = f"{DAG_ID}_{ENV_ID}".replace("_", "-")
[docs]BQ_SQL_DATASET = f"{DAG_ID}_{ENV_ID}".replace("-", "_")
[docs]BQ_SQL_TABLE_OUTPUT = f"output_{ENV_ID}".replace("-", "_")
[docs]INSERT_ROWS_QUERY = (
f"INSERT {BQ_SQL_DATASET}.{BQ_SQL_TABLE_INPUT} VALUES "
"('John Doe', 900), "
"('Alice Storm', 1200),"
"('Bob Max', 1000),"
"('Peter Jackson', 800),"
"('Mia Smith', 1100);"
)
with DAG(
dag_id=DAG_ID,
start_date=datetime(2021, 1, 1),
schedule="@once",
catchup=False,
tags=["example", "dataflow-sql"],
) as dag:
[docs] create_bq_dataset = BigQueryCreateEmptyDatasetOperator(
task_id="create_bq_dataset",
dataset_id=BQ_SQL_DATASET,
location=LOCATION,
)
create_bq_table = BigQueryCreateEmptyTableOperator(
task_id="create_bq_table",
dataset_id=BQ_SQL_DATASET,
table_id=BQ_SQL_TABLE_INPUT,
schema_fields=[
{"name": "emp_name", "type": "STRING", "mode": "REQUIRED"},
{"name": "salary", "type": "INTEGER", "mode": "NULLABLE"},
],
)
insert_query_job = BigQueryInsertJobOperator(
task_id="insert_query_job",
configuration={
"query": {
"query": INSERT_ROWS_QUERY,
"useLegacySql": False,
"priority": "BATCH",
}
},
location=LOCATION,
)
# [START howto_operator_start_sql_job]
start_sql = DataflowStartSqlJobOperator(
task_id="start_sql_query",
job_name=DATAFLOW_SQL_JOB_NAME,
query=f"""
SELECT
emp_name as employee,
salary as employee_salary
FROM
bigquery.table.`{PROJECT_ID}`.`{BQ_SQL_DATASET}`.`{BQ_SQL_TABLE_INPUT}`
WHERE salary >= 1000;
""",
options={
"bigquery-project": PROJECT_ID,
"bigquery-dataset": BQ_SQL_DATASET,
"bigquery-table": BQ_SQL_TABLE_OUTPUT,
},
location=LOCATION,
do_xcom_push=True,
)
# [END howto_operator_start_sql_job]
delete_bq_table = BigQueryDeleteTableOperator(
task_id="delete_bq_table",
deletion_dataset_table=f"{PROJECT_ID}.{BQ_SQL_DATASET}.{BQ_SQL_TABLE_INPUT}",
trigger_rule=TriggerRule.ALL_DONE,
)
delete_bq_dataset = BigQueryDeleteDatasetOperator(
task_id="delete_bq_dataset",
dataset_id=BQ_SQL_DATASET,
delete_contents=True,
trigger_rule=TriggerRule.ALL_DONE,
)
(
# TEST SETUP
create_bq_dataset
>> create_bq_table
>> insert_query_job
# TEST BODY
>> start_sql
# TEST TEARDOWN
>> delete_bq_table
>> delete_bq_dataset
)
from tests_common.test_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_common.test_utils.system_tests 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)