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import json
from datetime import datetime
import boto3
from airflow import DAG
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.providers.amazon.aws.operators.quicksight import QuickSightCreateIngestionOperator
from airflow.providers.amazon.aws.operators.s3 import (
S3CreateBucketOperator,
S3CreateObjectOperator,
S3DeleteBucketOperator,
)
from airflow.providers.amazon.aws.sensors.quicksight import QuickSightSensor
from airflow.utils.trigger_rule import TriggerRule
from tests.system.providers.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder
"""
Prerequisites:
1. The account which runs this test must manually be activated in Quicksight here:
https://quicksight.aws.amazon.com/sn/console/signup?#
2. The activation process creates an IAM Role called `aws-quicksight-service-role-v0`.
You have to add a policy named 'AWSQuickSightS3Policy' with the S3 access permissions.
The policy name is enforced, and the permissions json can be copied from `AmazonS3FullAccess`.
NOTES: If Create Ingestion fails for any reason, that ingestion name will remain in use and
future runs will stall with the sensor returning a status of QUEUED "forever". If you run
into this behavior, changing the template for the ingestion name or the ENV_ID and re-running
the test should resolve the issue.
"""
[docs]DAG_ID = 'example_quicksight'
[docs]sys_test_context_task = SystemTestContextBuilder().build()
[docs]SAMPLE_DATA_COLUMNS = ['Project', 'Year']
[docs]SAMPLE_DATA = """'Airflow','2015'
'OpenOffice','2012'
'Subversion','2000'
'NiFi','2006'
"""
@task
[docs]def get_aws_account_id() -> int:
return boto3.client('sts').get_caller_identity()['Account']
@task
[docs]def create_quicksight_data_source(
aws_account_id: str, datasource_name: str, bucket: str, manifest_key: str
) -> str:
response = boto3.client('quicksight').create_data_source(
AwsAccountId=aws_account_id,
DataSourceId=datasource_name,
Name=datasource_name,
Type='S3',
DataSourceParameters={
'S3Parameters': {'ManifestFileLocation': {'Bucket': bucket, 'Key': manifest_key}}
},
)
return response['Arn']
@task
[docs]def create_quicksight_dataset(aws_account_id: int, dataset_name: str, data_source_arn: str) -> None:
table_map = {
'default': {
'S3Source': {
'DataSourceArn': data_source_arn,
'InputColumns': [{'Name': name, 'Type': 'STRING'} for name in SAMPLE_DATA_COLUMNS],
}
}
}
boto3.client('quicksight').create_data_set(
AwsAccountId=aws_account_id,
DataSetId=dataset_name,
Name=dataset_name,
PhysicalTableMap=table_map,
ImportMode='SPICE',
)
@task(trigger_rule=TriggerRule.ALL_DONE)
[docs]def delete_quicksight_data_source(aws_account_id: str, datasource_name: str):
boto3.client('quicksight').delete_data_source(AwsAccountId=aws_account_id, DataSourceId=datasource_name)
@task(trigger_rule=TriggerRule.ALL_DONE)
[docs]def delete_dataset(aws_account_id: str, dataset_name: str):
boto3.client('quicksight').delete_data_set(AwsAccountId=aws_account_id, DataSetId=dataset_name)
@task(trigger_rule=TriggerRule.ALL_DONE)
[docs]def delete_ingestion(aws_account_id: str, dataset_name: str, ingestion_name: str) -> None:
client = boto3.client('quicksight')
try:
client.cancel_ingestion(
AwsAccountId=aws_account_id,
DataSetId=dataset_name,
IngestionId=ingestion_name,
)
except client.exceptions.ResourceNotFoundException:
# Ingestion has already terminated on its own.
pass
with DAG(
dag_id=DAG_ID,
schedule='@once',
start_date=datetime(2021, 1, 1),
tags=["example"],
catchup=False,
) as dag:
[docs] test_context = sys_test_context_task()
account_id = get_aws_account_id()
env_id = test_context[ENV_ID_KEY]
bucket_name = f'{env_id}-quicksight-bucket'
data_filename = 'sample_data.csv'
dataset_id = f'{env_id}-data-set'
datasource_id = f'{env_id}-data-source'
ingestion_id = f'{env_id}-ingestion'
manifest_filename = f'{env_id}-manifest.json'
manifest_contents = {'fileLocations': [{'URIs': [f's3://{bucket_name}/{data_filename}']}]}
create_s3_bucket = S3CreateBucketOperator(task_id='create_s3_bucket', bucket_name=bucket_name)
upload_manifest_file = S3CreateObjectOperator(
task_id='upload_manifest_file',
s3_bucket=bucket_name,
s3_key=manifest_filename,
data=json.dumps(manifest_contents),
replace=True,
)
upload_sample_data = S3CreateObjectOperator(
task_id='upload_sample_data',
s3_bucket=bucket_name,
s3_key=data_filename,
data=SAMPLE_DATA,
replace=True,
)
data_source = create_quicksight_data_source(
aws_account_id=account_id,
datasource_name=datasource_id,
bucket=bucket_name,
manifest_key=manifest_filename,
)
create_dataset = create_quicksight_dataset(account_id, dataset_id, data_source)
# [START howto_operator_quicksight_create_ingestion]
create_ingestion = QuickSightCreateIngestionOperator(
task_id='create_ingestion',
data_set_id=dataset_id,
ingestion_id=ingestion_id,
# Waits by default, setting as False to demonstrate the Sensor below.
wait_for_completion=False,
)
# [END howto_operator_quicksight_create_ingestion]
# If this sensor appears to freeze with a "QUEUED" status, see note above.
# [START howto_sensor_quicksight]
await_job = QuickSightSensor(
task_id='await_job',
data_set_id=dataset_id,
ingestion_id=ingestion_id,
)
# [END howto_sensor_quicksight]
delete_bucket = S3DeleteBucketOperator(
task_id='delete_s3_bucket',
trigger_rule=TriggerRule.ALL_DONE,
bucket_name=bucket_name,
force_delete=True,
)
chain(
# TEST SETUP
test_context,
account_id,
create_s3_bucket,
upload_manifest_file,
upload_sample_data,
data_source,
create_dataset,
# TEST BODY
create_ingestion,
await_job,
# TEST TEARDOWN
delete_dataset(account_id, dataset_id),
delete_quicksight_data_source(account_id, datasource_id),
delete_ingestion(account_id, dataset_id, ingestion_id),
delete_bucket,
)
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)
