Source code for tests.system.providers.google.cloud.datafusion.example_datafusion

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"""
Example Airflow DAG that shows how to use DataFusion.
"""
from __future__ import annotations

import os
from datetime import datetime

from airflow.decorators import task
from airflow.models.dag import DAG
from airflow.providers.google.cloud.hooks.datafusion import DataFusionHook
from airflow.providers.google.cloud.operators.datafusion import (
    CloudDataFusionCreateInstanceOperator,
    CloudDataFusionCreatePipelineOperator,
    CloudDataFusionDeleteInstanceOperator,
    CloudDataFusionDeletePipelineOperator,
    CloudDataFusionGetInstanceOperator,
    CloudDataFusionListPipelinesOperator,
    CloudDataFusionRestartInstanceOperator,
    CloudDataFusionStartPipelineOperator,
    CloudDataFusionStopPipelineOperator,
    CloudDataFusionUpdateInstanceOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.sensors.datafusion import CloudDataFusionPipelineStateSensor
from airflow.utils.trigger_rule import TriggerRule

# [START howto_data_fusion_env_variables]
[docs]SERVICE_ACCOUNT = os.environ.get("GCP_DATAFUSION_SERVICE_ACCOUNT")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]LOCATION = "europe-north1"
[docs]DAG_ID = "example_datafusion"
[docs]INSTANCE_NAME = f"df-{ENV_ID}".replace("_", "-")
[docs]INSTANCE = { "type": "BASIC", "displayName": INSTANCE_NAME, "dataprocServiceAccount": SERVICE_ACCOUNT, }
[docs]BUCKET_NAME_1 = f"bucket1-{DAG_ID}-{ENV_ID}".replace("_", "-")
[docs]BUCKET_NAME_2 = f"bucket2-{DAG_ID}-{ENV_ID}".replace("_", "-")
[docs]BUCKET_NAME_1_URI = f"gs://{BUCKET_NAME_1}"
[docs]BUCKET_NAME_2_URI = f"gs://{BUCKET_NAME_2}"
[docs]PIPELINE_NAME = f"pipe-{ENV_ID}".replace("_", "-")
[docs]PIPELINE = { "artifact": { "name": "cdap-data-pipeline", "version": "{{ task_instance.xcom_pull(task_ids='get_artifacts_versions')['cdap-data-pipeline'] }}", "scope": "SYSTEM", }, "description": "Data Pipeline Application", "name": PIPELINE_NAME, "config": { "resources": {"memoryMB": 2048, "virtualCores": 1}, "driverResources": {"memoryMB": 2048, "virtualCores": 1}, "connections": [{"from": "GCS", "to": "GCS2"}], "comments": [], "postActions": [], "properties": {}, "processTimingEnabled": "true", "stageLoggingEnabled": "false", "stages": [ { "name": "GCS", "plugin": { "name": "GCSFile", "type": "batchsource", "label": "GCS", "artifact": { "name": "google-cloud", "version": "{{ task_instance.xcom_pull(task_ids='get_artifacts_versions')\ ['google-cloud'] }}", "scope": "SYSTEM", }, "properties": { "project": "auto-detect", "format": "text", "skipHeader": "false", "serviceFilePath": "auto-detect", "filenameOnly": "false", "recursive": "false", "encrypted": "false", "schema": '{"type":"record","name":"textfile","fields":[{"name"\ :"offset","type":"long"},{"name":"body","type":"string"}]}', "path": BUCKET_NAME_1_URI, "referenceName": "foo_bucket", "useConnection": "false", "serviceAccountType": "filePath", "sampleSize": "1000", "fileEncoding": "UTF-8", }, }, "outputSchema": '{"type":"record","name":"textfile","fields"\ :[{"name":"offset","type":"long"},{"name":"body","type":"string"}]}', "id": "GCS", }, { "name": "GCS2", "plugin": { "name": "GCS", "type": "batchsink", "label": "GCS2", "artifact": { "name": "google-cloud", "version": "{{ task_instance.xcom_pull(task_ids='get_artifacts_versions')\ ['google-cloud'] }}", "scope": "SYSTEM", }, "properties": { "project": "auto-detect", "suffix": "yyyy-MM-dd-HH-mm", "format": "json", "serviceFilePath": "auto-detect", "location": "us", "schema": '{"type":"record","name":"textfile","fields":[{"name"\ :"offset","type":"long"},{"name":"body","type":"string"}]}', "referenceName": "bar", "path": BUCKET_NAME_2_URI, "serviceAccountType": "filePath", "contentType": "application/octet-stream", }, }, "outputSchema": '{"type":"record","name":"textfile","fields"\ :[{"name":"offset","type":"long"},{"name":"body","type":"string"}]}', "inputSchema": [ { "name": "GCS", "schema": '{"type":"record","name":"textfile","fields":[{"name"\ :"offset","type":"long"},{"name":"body","type":"string"}]}', } ], "id": "GCS2", }, ], "schedule": "0 * * * *", "engine": "spark", "numOfRecordsPreview": 100, "description": "Data Pipeline Application", "maxConcurrentRuns": 1, }, }
# [END howto_data_fusion_env_variables] CloudDataFusionCreatePipelineOperator.template_fields += ("pipeline",) with DAG( DAG_ID, start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "datafusion"], ) as dag:
[docs] create_bucket1 = GCSCreateBucketOperator( task_id="create_bucket1", bucket_name=BUCKET_NAME_1, project_id=PROJECT_ID, )
create_bucket2 = GCSCreateBucketOperator( task_id="create_bucket2", bucket_name=BUCKET_NAME_2, project_id=PROJECT_ID, ) # [START howto_cloud_data_fusion_create_instance_operator] create_instance = CloudDataFusionCreateInstanceOperator( location=LOCATION, instance_name=INSTANCE_NAME, instance=INSTANCE, task_id="create_instance", ) # [END howto_cloud_data_fusion_create_instance_operator] # [START howto_cloud_data_fusion_get_instance_operator] get_instance = CloudDataFusionGetInstanceOperator( location=LOCATION, instance_name=INSTANCE_NAME, task_id="get_instance" ) # [END howto_cloud_data_fusion_get_instance_operator] # [START howto_cloud_data_fusion_restart_instance_operator] restart_instance = CloudDataFusionRestartInstanceOperator( location=LOCATION, instance_name=INSTANCE_NAME, task_id="restart_instance" ) # [END howto_cloud_data_fusion_restart_instance_operator] # [START howto_cloud_data_fusion_update_instance_operator] update_instance = CloudDataFusionUpdateInstanceOperator( location=LOCATION, instance_name=INSTANCE_NAME, instance=INSTANCE, update_mask="", task_id="update_instance", ) # [END howto_cloud_data_fusion_update_instance_operator] @task(task_id="get_artifacts_versions") def get_artifacts_versions(ti) -> dict: hook = DataFusionHook() instance_url = ti.xcom_pull(task_ids="get_instance", key="return_value")["apiEndpoint"] artifacts = hook.get_instance_artifacts(instance_url=instance_url, namespace="default") return {item["name"]: item["version"] for item in artifacts} # [START howto_cloud_data_fusion_create_pipeline] create_pipeline = CloudDataFusionCreatePipelineOperator( location=LOCATION, pipeline_name=PIPELINE_NAME, pipeline=PIPELINE, instance_name=INSTANCE_NAME, task_id="create_pipeline", ) # [END howto_cloud_data_fusion_create_pipeline] # [START howto_cloud_data_fusion_list_pipelines] list_pipelines = CloudDataFusionListPipelinesOperator( location=LOCATION, instance_name=INSTANCE_NAME, task_id="list_pipelines" ) # [END howto_cloud_data_fusion_list_pipelines] # [START howto_cloud_data_fusion_start_pipeline] start_pipeline = CloudDataFusionStartPipelineOperator( location=LOCATION, pipeline_name=PIPELINE_NAME, instance_name=INSTANCE_NAME, task_id="start_pipeline", ) # [END howto_cloud_data_fusion_start_pipeline] # [START howto_cloud_data_fusion_start_pipeline_def] start_pipeline_def = CloudDataFusionStartPipelineOperator( location=LOCATION, pipeline_name=PIPELINE_NAME, instance_name=INSTANCE_NAME, task_id="start_pipeline_def", deferrable=True, ) # [END howto_cloud_data_fusion_start_pipeline_def] # [START howto_cloud_data_fusion_start_pipeline_async] start_pipeline_async = CloudDataFusionStartPipelineOperator( location=LOCATION, pipeline_name=PIPELINE_NAME, instance_name=INSTANCE_NAME, asynchronous=True, task_id="start_pipeline_async", ) # [END howto_cloud_data_fusion_start_pipeline_async] # [START howto_cloud_data_fusion_start_pipeline_sensor] start_pipeline_sensor = CloudDataFusionPipelineStateSensor( task_id="pipeline_state_sensor", pipeline_name=PIPELINE_NAME, pipeline_id=start_pipeline_async.output, expected_statuses=["COMPLETED"], failure_statuses=["FAILED"], instance_name=INSTANCE_NAME, location=LOCATION, ) # [END howto_cloud_data_fusion_start_pipeline_sensor] # [START howto_cloud_data_fusion_stop_pipeline] stop_pipeline = CloudDataFusionStopPipelineOperator( location=LOCATION, pipeline_name=PIPELINE_NAME, instance_name=INSTANCE_NAME, task_id="stop_pipeline", ) # [END howto_cloud_data_fusion_stop_pipeline] # [START howto_cloud_data_fusion_delete_pipeline] delete_pipeline = CloudDataFusionDeletePipelineOperator( location=LOCATION, pipeline_name=PIPELINE_NAME, instance_name=INSTANCE_NAME, task_id="delete_pipeline", trigger_rule=TriggerRule.ALL_DONE, ) # [END howto_cloud_data_fusion_delete_pipeline] # [START howto_cloud_data_fusion_delete_instance_operator] delete_instance = CloudDataFusionDeleteInstanceOperator( location=LOCATION, instance_name=INSTANCE_NAME, task_id="delete_instance", trigger_rule=TriggerRule.ALL_DONE, ) # [END howto_cloud_data_fusion_delete_instance_operator] delete_bucket1 = GCSDeleteBucketOperator( task_id="delete_bucket1", bucket_name=BUCKET_NAME_1, trigger_rule=TriggerRule.ALL_DONE ) delete_bucket2 = GCSDeleteBucketOperator( task_id="delete_bucket2", bucket_name=BUCKET_NAME_1, trigger_rule=TriggerRule.ALL_DONE ) ( # TEST SETUP [create_bucket1, create_bucket2] # TEST BODY >> create_instance >> get_instance >> get_artifacts_versions() >> restart_instance >> update_instance >> create_pipeline >> list_pipelines >> start_pipeline_def >> start_pipeline_async >> start_pipeline_sensor >> start_pipeline >> stop_pipeline >> delete_pipeline >> delete_instance # TEST TEARDOWN >> [delete_bucket1, delete_bucket2] ) 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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