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"""
Example Airflow DAG for Google BigQuery service.
"""
import os
from datetime import datetime
from airflow import models
from airflow.operators.bash import BashOperator
from airflow.providers.google.cloud.operators.bigquery import (
BigQueryCheckOperator,
BigQueryCreateEmptyDatasetOperator,
BigQueryCreateEmptyTableOperator,
BigQueryDeleteDatasetOperator,
BigQueryGetDataOperator,
BigQueryInsertJobOperator,
BigQueryIntervalCheckOperator,
BigQueryValueCheckOperator,
)
from airflow.utils.trigger_rule import TriggerRule
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]QUERY_SQL_PATH = "resources/example_bigquery_query.sql"
[docs]SCHEMA = [
{"name": "value", "type": "INTEGER", "mode": "REQUIRED"},
{"name": "name", "type": "STRING", "mode": "NULLABLE"},
{"name": "ds", "type": "DATE", "mode": "NULLABLE"},
]
[docs]locations = [None, LOCATION]
for index, location in enumerate(locations, 1):
[docs] DAG_ID = "bigquery_queries_location" if location else "bigquery_queries"
DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}"
DATASET = f"{DATASET_NAME}{index}"
INSERT_DATE = datetime.now().strftime("%Y-%m-%d")
# [START howto_operator_bigquery_query]
INSERT_ROWS_QUERY = (
f"INSERT {DATASET}.{TABLE_1} VALUES "
f"(42, 'monty python', '{INSERT_DATE}'), "
f"(42, 'fishy fish', '{INSERT_DATE}');"
)
# [END howto_operator_bigquery_query]
with models.DAG(
DAG_ID,
schedule_interval="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "bigquery"],
user_defined_macros={"DATASET": DATASET, "TABLE": TABLE_1, "QUERY_SQL_PATH": QUERY_SQL_PATH},
) as dag:
create_dataset = BigQueryCreateEmptyDatasetOperator(
task_id="create_dataset",
dataset_id=DATASET,
location=location,
)
create_table_1 = BigQueryCreateEmptyTableOperator(
task_id="create_table_1",
dataset_id=DATASET,
table_id=TABLE_1,
schema_fields=SCHEMA,
location=location,
)
create_table_2 = BigQueryCreateEmptyTableOperator(
task_id="create_table_2",
dataset_id=DATASET,
table_id=TABLE_2,
schema_fields=SCHEMA,
location=location,
)
# [START howto_operator_bigquery_insert_job]
insert_query_job = BigQueryInsertJobOperator(
task_id="insert_query_job",
configuration={
"query": {
"query": INSERT_ROWS_QUERY,
"useLegacySql": False,
}
},
location=location,
)
# [END howto_operator_bigquery_insert_job]
# [START howto_operator_bigquery_select_job]
select_query_job = BigQueryInsertJobOperator(
task_id="select_query_job",
configuration={
"query": {
"query": "{% include QUERY_SQL_PATH %}",
"useLegacySql": False,
}
},
location=location,
)
# [END howto_operator_bigquery_select_job]
execute_insert_query = BigQueryInsertJobOperator(
task_id="execute_insert_query",
configuration={
"query": {
"query": INSERT_ROWS_QUERY,
"useLegacySql": False,
}
},
location=location,
)
execute_query_save = BigQueryInsertJobOperator(
task_id="execute_query_save",
configuration={
"query": {
"query": f"SELECT * FROM {DATASET}.{TABLE_1}",
"useLegacySql": False,
"destinationTable": {
'projectId': PROJECT_ID,
'datasetId': DATASET,
'tableId': TABLE_2,
},
}
},
location=location,
)
bigquery_execute_multi_query = BigQueryInsertJobOperator(
task_id="execute_multi_query",
configuration={
"query": {
"query": [
f"SELECT * FROM {DATASET}.{TABLE_2}",
f"SELECT COUNT(*) FROM {DATASET}.{TABLE_2}",
],
"useLegacySql": False,
}
},
location=location,
)
# [START howto_operator_bigquery_get_data]
get_data = BigQueryGetDataOperator(
task_id="get_data",
dataset_id=DATASET,
table_id=TABLE_1,
max_results=10,
selected_fields="value,name",
location=location,
)
# [END howto_operator_bigquery_get_data]
get_data_result = BashOperator(
task_id="get_data_result",
bash_command=f"echo {get_data.output}",
)
# [START howto_operator_bigquery_check]
check_count = BigQueryCheckOperator(
task_id="check_count",
sql=f"SELECT COUNT(*) FROM {DATASET}.{TABLE_1}",
use_legacy_sql=False,
location=location,
)
# [END howto_operator_bigquery_check]
# [START howto_operator_bigquery_value_check]
check_value = BigQueryValueCheckOperator(
task_id="check_value",
sql=f"SELECT COUNT(*) FROM {DATASET}.{TABLE_1}",
pass_value=4,
use_legacy_sql=False,
location=location,
)
# [END howto_operator_bigquery_value_check]
# [START howto_operator_bigquery_interval_check]
check_interval = BigQueryIntervalCheckOperator(
task_id="check_interval",
table=f"{DATASET}.{TABLE_1}",
days_back=1,
metrics_thresholds={"COUNT(*)": 1.5},
use_legacy_sql=False,
location=location,
)
# [END howto_operator_bigquery_interval_check]
delete_dataset = BigQueryDeleteDatasetOperator(
task_id="delete_dataset",
dataset_id=DATASET,
delete_contents=True,
trigger_rule=TriggerRule.ALL_DONE,
)
# TEST SETUP
create_dataset >> [create_table_1, create_table_2]
# TEST BODY
[create_table_1, create_table_2] >> insert_query_job >> [select_query_job, execute_insert_query]
execute_insert_query >> get_data >> get_data_result >> delete_dataset
execute_insert_query >> execute_query_save >> bigquery_execute_multi_query >> delete_dataset
execute_insert_query >> [check_count, check_value, check_interval] >> delete_dataset
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()
DAGS_LIST.append(dag)
globals()[DAG_ID] = dag
for dag in DAGS_LIST:
from tests.system.utils import get_test_run
# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs] test_run = get_test_run(dag)
