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"""
Example Airflow DAG for Google BigQuery service.
"""
from __future__ import annotations
import os
from datetime import datetime
from providers.google.tests.system.google import DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.bigquery import (
BigQueryCheckOperator,
BigQueryColumnCheckOperator,
BigQueryCreateEmptyDatasetOperator,
BigQueryCreateEmptyTableOperator,
BigQueryDeleteDatasetOperator,
BigQueryGetDataOperator,
BigQueryInsertJobOperator,
BigQueryIntervalCheckOperator,
BigQueryTableCheckOperator,
BigQueryValueCheckOperator,
)
from airflow.providers.standard.operators.bash import BashOperator
from airflow.utils.trigger_rule import TriggerRule
[docs]
ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]
PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[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]
DAG_ID = "bigquery_queries_location"
[docs]
DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}"
[docs]
INSERT_DATE = "2030-01-01"
[docs]
INSERT_ROWS_QUERY = (
f"INSERT {DATASET_NAME}.{TABLE_1} VALUES "
f"(42, 'monty python', '{INSERT_DATE}'), "
f"(42, 'fishy fish', '{INSERT_DATE}');"
)
with DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "bigquery"],
user_defined_macros={"DATASET": DATASET_NAME, "TABLE": TABLE_1, "QUERY_SQL_PATH": QUERY_SQL_PATH},
) as dag:
[docs]
create_dataset = BigQueryCreateEmptyDatasetOperator(
task_id="create_dataset",
dataset_id=DATASET_NAME,
location=LOCATION,
)
create_table_1 = BigQueryCreateEmptyTableOperator(
task_id="create_table_1",
dataset_id=DATASET_NAME,
table_id=TABLE_1,
schema_fields=SCHEMA,
location=LOCATION,
)
create_table_2 = BigQueryCreateEmptyTableOperator(
task_id="create_table_2",
dataset_id=DATASET_NAME,
table_id=TABLE_2,
schema_fields=SCHEMA,
location=LOCATION,
)
insert_query_job = BigQueryInsertJobOperator(
task_id="insert_query_job",
configuration={
"query": {
"query": INSERT_ROWS_QUERY,
"useLegacySql": False,
"priority": "BATCH",
}
},
location=LOCATION,
)
select_query_job = BigQueryInsertJobOperator(
task_id="select_query_job",
configuration={
"query": {
"query": "{% include QUERY_SQL_PATH %}",
"useLegacySql": False,
}
},
location=LOCATION,
)
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_NAME}.{TABLE_1}",
"useLegacySql": False,
"destinationTable": {
"projectId": PROJECT_ID,
"datasetId": DATASET_NAME,
"tableId": TABLE_2,
},
}
},
location=LOCATION,
)
bigquery_execute_multi_query = BigQueryInsertJobOperator(
task_id="execute_multi_query",
configuration={
"query": {
"query": [
f"SELECT * FROM {DATASET_NAME}.{TABLE_2}",
f"SELECT COUNT(*) FROM {DATASET_NAME}.{TABLE_2}",
],
"useLegacySql": False,
}
},
location=LOCATION,
)
get_data = BigQueryGetDataOperator(
task_id="get_data",
dataset_id=DATASET_NAME,
table_id=TABLE_1,
max_results=10,
selected_fields="value,name",
location=LOCATION,
)
get_data_result = BashOperator(
task_id="get_data_result",
bash_command=f"echo {get_data.output}",
)
check_count = BigQueryCheckOperator(
task_id="check_count",
sql=f"SELECT COUNT(*) FROM {DATASET_NAME}.{TABLE_1}",
use_legacy_sql=False,
location=LOCATION,
)
check_value = BigQueryValueCheckOperator(
task_id="check_value",
sql=f"SELECT COUNT(*) FROM {DATASET_NAME}.{TABLE_1}",
pass_value=4,
use_legacy_sql=False,
location=LOCATION,
)
check_interval = BigQueryIntervalCheckOperator(
task_id="check_interval",
table=f"{DATASET_NAME}.{TABLE_1}",
days_back=1,
metrics_thresholds={"COUNT(*)": 1.5},
use_legacy_sql=False,
location=LOCATION,
)
column_check = BigQueryColumnCheckOperator(
task_id="column_check",
table=f"{DATASET_NAME}.{TABLE_1}",
column_mapping={"value": {"null_check": {"equal_to": 0}}},
)
table_check = BigQueryTableCheckOperator(
task_id="table_check",
table=f"{DATASET_NAME}.{TABLE_1}",
checks={"row_count_check": {"check_statement": "COUNT(*) = 4"}},
)
delete_dataset = BigQueryDeleteDatasetOperator(
task_id="delete_dataset",
dataset_id=DATASET_NAME,
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
execute_insert_query >> [column_check, table_check] >> delete_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)