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"""
Example Airflow DAG for Google Vertex AI service testing Pipeline Job operations.
"""
from __future__ import annotations
import os
from datetime import datetime
from google.cloud.aiplatform import schema
from google.protobuf.json_format import ParseDict
from google.protobuf.struct_pb2 import Value
from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.gcs import (
GCSCreateBucketOperator,
GCSDeleteBucketOperator,
GCSDeleteObjectsOperator,
GCSListObjectsOperator,
GCSSynchronizeBucketsOperator,
)
from airflow.providers.google.cloud.operators.vertex_ai.dataset import CreateDatasetOperator
from airflow.providers.google.cloud.operators.vertex_ai.pipeline_job import (
DeletePipelineJobOperator,
GetPipelineJobOperator,
ListPipelineJobOperator,
RunPipelineJobOperator,
)
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", "default")
[docs]
DAG_ID = "vertex_ai_pipeline_job_operations"
[docs]
DISPLAY_NAME = f"pipeline-job-{ENV_ID}"
[docs]
RESOURCE_DATA_BUCKET = "airflow-system-tests-resources"
[docs]
DATA_SAMPLE_GCS_BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}".replace("_", "-")
[docs]
TEMPLATE_PATH = "https://us-kfp.pkg.dev/ml-pipeline/google-cloud-registry/get-vertex-dataset/sha256:f4eb4a2b0aab482c487c1cd62b3c735baaf914be8fa8c4687c06077c1d815a5d"
[docs]
OUTPUT_BUCKET = f"gs://{DATA_SAMPLE_GCS_BUCKET_NAME}"
[docs]
PARAMETER_VALUES = {
"dataset_resource_name": f"projects/{PROJECT_ID}/locations/{REGION}/datasets/tabular-dataset-{ENV_ID}",
}
[docs]
DATA_SAMPLE_GCS_OBJECT_NAME = "vertex-ai/california_housing_train.csv"
[docs]
TABULAR_DATASET = {
"display_name": f"tabular-dataset-{ENV_ID}",
"metadata_schema_uri": schema.dataset.metadata.tabular,
"metadata": ParseDict(
{
"input_config": {
"gcs_source": {"uri": [f"gs://{DATA_SAMPLE_GCS_BUCKET_NAME}/{DATA_SAMPLE_GCS_OBJECT_NAME}"]}
}
},
Value(),
),
}
with DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "vertex_ai", "pipeline_job"],
) as dag:
[docs]
create_bucket = GCSCreateBucketOperator(
task_id="create_bucket",
bucket_name=DATA_SAMPLE_GCS_BUCKET_NAME,
storage_class="REGIONAL",
location=REGION,
)
move_dataset_files = GCSSynchronizeBucketsOperator(
task_id="move_dataset_files_to_bucket",
source_bucket=RESOURCE_DATA_BUCKET,
source_object="vertex-ai/california-housing-data",
destination_bucket=DATA_SAMPLE_GCS_BUCKET_NAME,
destination_object="vertex-ai",
recursive=True,
)
create_dataset = CreateDatasetOperator(
task_id="tabular_dataset",
dataset=TABULAR_DATASET,
region=REGION,
project_id=PROJECT_ID,
)
# [START how_to_cloud_vertex_ai_run_pipeline_job_operator]
run_pipeline_job = RunPipelineJobOperator(
task_id="run_pipeline_job",
display_name=DISPLAY_NAME,
template_path=TEMPLATE_PATH,
parameter_values=PARAMETER_VALUES,
region=REGION,
project_id=PROJECT_ID,
)
# [END how_to_cloud_vertex_ai_run_pipeline_job_operator]
# [START how_to_cloud_vertex_ai_get_pipeline_job_operator]
get_pipeline_job = GetPipelineJobOperator(
task_id="get_pipeline_job",
project_id=PROJECT_ID,
region=REGION,
pipeline_job_id="{{ task_instance.xcom_pull("
"task_ids='run_pipeline_job', key='pipeline_job_id') }}",
)
# [END how_to_cloud_vertex_ai_get_pipeline_job_operator]
# [START how_to_cloud_vertex_ai_delete_pipeline_job_operator]
delete_pipeline_job = DeletePipelineJobOperator(
task_id="delete_pipeline_job",
project_id=PROJECT_ID,
region=REGION,
pipeline_job_id="{{ task_instance.xcom_pull("
"task_ids='run_pipeline_job', key='pipeline_job_id') }}",
trigger_rule=TriggerRule.ALL_DONE,
)
# [END how_to_cloud_vertex_ai_delete_pipeline_job_operator]
# [START how_to_cloud_vertex_ai_list_pipeline_job_operator]
list_pipeline_job = ListPipelineJobOperator(
task_id="list_pipeline_job",
region=REGION,
project_id=PROJECT_ID,
)
# [END how_to_cloud_vertex_ai_list_pipeline_job_operator]
list_buckets = GCSListObjectsOperator(task_id="list_buckets", bucket=DATA_SAMPLE_GCS_BUCKET_NAME)
delete_files = GCSDeleteObjectsOperator(
task_id="delete_files", bucket_name=DATA_SAMPLE_GCS_BUCKET_NAME, objects=list_buckets.output
)
delete_bucket = GCSDeleteBucketOperator(
task_id="delete_bucket",
bucket_name=DATA_SAMPLE_GCS_BUCKET_NAME,
trigger_rule=TriggerRule.ALL_DONE,
)
(
# TEST SETUP
create_bucket
>> move_dataset_files
>> create_dataset
# TEST BODY
>> run_pipeline_job
>> get_pipeline_job
>> delete_pipeline_job
>> list_pipeline_job
# TEST TEARDOWN
>> list_buckets
>> delete_files
>> delete_bucket
)
# ### Everything below this line is not part of example ###
# ### Just for system tests purpose ###
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)