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

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"""
Example Airflow DAG for Google BigQuery service testing tables.
"""
from __future__ import annotations

import os
import time
from datetime import datetime
from pathlib import Path

from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.bigquery import (
    BigQueryCreateEmptyDatasetOperator,
    BigQueryCreateEmptyTableOperator,
    BigQueryDeleteDatasetOperator,
    BigQueryDeleteTableOperator,
    BigQueryGetDatasetTablesOperator,
    BigQueryUpdateDatasetOperator,
    BigQueryUpdateTableOperator,
    BigQueryUpdateTableSchemaOperator,
    BigQueryUpsertTableOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.transfers.local_to_gcs import LocalFilesystemToGCSOperator
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "bigquery_tables"
[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"
[docs]DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}"
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]SCHEMA_JSON_LOCAL_SRC = str(Path(__file__).parent / "resources" / "update_table_schema.json")
[docs]SCHEMA_JSON_DESTINATION = "update_table_schema.json"
[docs]GCS_PATH_TO_SCHEMA_JSON = f"gs://{BUCKET_NAME}/{SCHEMA_JSON_DESTINATION}"
with DAG( DAG_ID, schedule="@once", 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 )
upload_schema_json = LocalFilesystemToGCSOperator( task_id="upload_schema_json", src=SCHEMA_JSON_LOCAL_SRC, dst=SCHEMA_JSON_DESTINATION, bucket=BUCKET_NAME, ) create_dataset = BigQueryCreateEmptyDatasetOperator(task_id="create_dataset", dataset_id=DATASET_NAME) # [START howto_operator_bigquery_create_table] create_table = BigQueryCreateEmptyTableOperator( task_id="create_table", dataset_id=DATASET_NAME, table_id="test_table", schema_fields=[ {"name": "emp_name", "type": "STRING", "mode": "REQUIRED"}, {"name": "salary", "type": "INTEGER", "mode": "NULLABLE"}, ], ) # [END howto_operator_bigquery_create_table] # [START howto_operator_bigquery_create_view] create_view = BigQueryCreateEmptyTableOperator( task_id="create_view", dataset_id=DATASET_NAME, table_id="test_view", view={ "query": f"SELECT * FROM `{PROJECT_ID}.{DATASET_NAME}.test_table`", "useLegacySql": False, }, ) # [END howto_operator_bigquery_create_view] # [START howto_operator_bigquery_create_materialized_view] create_materialized_view = BigQueryCreateEmptyTableOperator( task_id="create_materialized_view", dataset_id=DATASET_NAME, table_id="test_materialized_view", materialized_view={ "query": f"SELECT SUM(salary) AS sum_salary FROM `{PROJECT_ID}.{DATASET_NAME}.test_table`", "enableRefresh": True, "refreshIntervalMs": 2000000, }, ) # [END howto_operator_bigquery_create_materialized_view] # [START howto_operator_bigquery_delete_view] delete_view = BigQueryDeleteTableOperator( task_id="delete_view", deletion_dataset_table=f"{PROJECT_ID}.{DATASET_NAME}.test_view", ) # [END howto_operator_bigquery_delete_view] # [START howto_operator_bigquery_update_table] update_table = BigQueryUpdateTableOperator( task_id="update_table", dataset_id=DATASET_NAME, table_id="test_table", fields=["friendlyName", "description"], table_resource={ "friendlyName": "Updated Table", "description": "Updated Table", }, ) # [END howto_operator_bigquery_update_table] # [START howto_operator_bigquery_upsert_table] upsert_table = BigQueryUpsertTableOperator( task_id="upsert_table", dataset_id=DATASET_NAME, table_resource={ "tableReference": {"tableId": "test_table_id"}, "expirationTime": (int(time.time()) + 300) * 1000, }, ) # [END howto_operator_bigquery_upsert_table] # [START howto_operator_bigquery_update_table_schema] update_table_schema = BigQueryUpdateTableSchemaOperator( task_id="update_table_schema", dataset_id=DATASET_NAME, table_id="test_table", schema_fields_updates=[ {"name": "emp_name", "description": "Name of employee"}, {"name": "salary", "description": "Monthly salary in USD"}, ], ) # [END howto_operator_bigquery_update_table_schema] # [START howto_operator_bigquery_create_table_schema_json] update_table_schema_json = BigQueryCreateEmptyTableOperator( task_id="update_table_schema_json", dataset_id=DATASET_NAME, table_id="test_table", gcs_schema_object=GCS_PATH_TO_SCHEMA_JSON, ) # [END howto_operator_bigquery_create_table_schema_json] # [START howto_operator_bigquery_delete_materialized_view] delete_materialized_view = BigQueryDeleteTableOperator( task_id="delete_materialized_view", deletion_dataset_table=f"{PROJECT_ID}.{DATASET_NAME}.test_materialized_view", ) # [END howto_operator_bigquery_delete_materialized_view] # [START howto_operator_bigquery_get_dataset_tables] get_dataset_tables = BigQueryGetDatasetTablesOperator( task_id="get_dataset_tables", dataset_id=DATASET_NAME ) # [END howto_operator_bigquery_get_dataset_tables] update_dataset = BigQueryUpdateDatasetOperator( task_id="update_dataset", dataset_id=DATASET_NAME, dataset_resource={"description": "Updated dataset"}, ) # [START howto_operator_bigquery_delete_table] delete_table = BigQueryDeleteTableOperator( task_id="delete_table", deletion_dataset_table=f"{PROJECT_ID}.{DATASET_NAME}.test_table", ) # [END howto_operator_bigquery_delete_table] delete_dataset = BigQueryDeleteDatasetOperator( task_id="delete_dataset", dataset_id=DATASET_NAME, delete_contents=True ) delete_dataset.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 >> upload_schema_json # TEST BODY >> update_dataset >> create_table >> create_view >> create_materialized_view >> [ get_dataset_tables, delete_view, ] >> update_table >> upsert_table >> update_table_schema >> update_table_schema_json >> delete_materialized_view >> delete_table # TEST TEARDOWN >> delete_bucket >> 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() 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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