# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations
from datetime import datetime
from airflow.providers.amazon.aws.hooks.redshift_cluster import RedshiftHook
from airflow.providers.amazon.aws.operators.redshift_cluster import (
RedshiftCreateClusterOperator,
RedshiftDeleteClusterOperator,
)
from airflow.providers.amazon.aws.operators.redshift_data import RedshiftDataOperator
from airflow.providers.amazon.aws.operators.s3 import (
S3CreateBucketOperator,
S3CreateObjectOperator,
S3DeleteBucketOperator,
S3DeleteObjectsOperator,
)
from airflow.providers.amazon.aws.sensors.redshift_cluster import RedshiftClusterSensor
from airflow.providers.amazon.aws.transfers.s3_to_sql import S3ToSqlOperator
from airflow.providers.common.sql.operators.sql import SQLTableCheckOperator
from tests_common.test_utils.version_compat import AIRFLOW_V_3_0_PLUS
if AIRFLOW_V_3_0_PLUS:
from airflow.sdk import DAG, chain, task
else:
# Airflow 2 path
from airflow.decorators import task # type: ignore[attr-defined,no-redef]
from airflow.models.baseoperator import chain # type: ignore[attr-defined,no-redef]
from airflow.models.dag import DAG # type: ignore[attr-defined,no-redef,assignment]
try:
from airflow.sdk import TriggerRule
except ImportError:
# Compatibility for Airflow < 3.1
from airflow.utils.trigger_rule import TriggerRule # type: ignore[no-redef,attr-defined]
from system.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder
from tests_common.test_utils.api_client_helpers import create_airflow_connection
from tests_common.test_utils.watcher import watcher
# Externally fetched variables:
SECURITY_GROUP_KEY = "SECURITY_GROUP"
CLUSTER_SUBNET_GROUP_KEY = "CLUSTER_SUBNET_GROUP"
sys_test_context_task = (
SystemTestContextBuilder().add_variable(SECURITY_GROUP_KEY).add_variable(CLUSTER_SUBNET_GROUP_KEY).build()
)
DAG_ID = "example_s3_to_sql"
DB_LOGIN = "adminuser"
DB_PASS = "MyAmazonPassword1"
DB_NAME = "dev"
SQL_TABLE_NAME = "cocktails"
SQL_COLUMN_LIST = ["cocktail_id", "cocktail_name", "base_spirit"]
SAMPLE_DATA = r"""1,Caipirinha,Cachaca
2,Bramble,Gin
3,Daiquiri,Rum
"""
@task
def create_connection(conn_id_name: str, cluster_id: str):
cluster_endpoint = RedshiftHook().conn.describe_clusters(ClusterIdentifier=cluster_id)["Clusters"][0]
create_airflow_connection(
connection_id=conn_id_name,
connection_conf={
"conn_type": "redshift",
"host": cluster_endpoint["Endpoint"]["Address"],
"login": DB_LOGIN,
"schema": cluster_endpoint["DBName"],
"port": cluster_endpoint["Endpoint"]["Port"],
"password": DB_PASS,
},
)
with DAG(
dag_id=DAG_ID,
start_date=datetime(2023, 1, 1),
schedule="@once",
catchup=False,
) as dag:
test_context = sys_test_context_task()
env_id = test_context[ENV_ID_KEY]
security_group_id = test_context[SECURITY_GROUP_KEY]
cluster_subnet_group_name = test_context[CLUSTER_SUBNET_GROUP_KEY]
conn_id_name = f"{env_id}-conn-id"
redshift_cluster_identifier = f"{env_id}-redshift-cluster"
sg_name = f"{env_id}-sg"
s3_bucket_name = f"{env_id}-bucket"
s3_key = f"{env_id}/files/cocktail_list.csv"
create_cluster = RedshiftCreateClusterOperator(
task_id="create_cluster",
cluster_identifier=redshift_cluster_identifier,
vpc_security_group_ids=[security_group_id],
cluster_subnet_group_name=cluster_subnet_group_name,
publicly_accessible=False,
cluster_type="single-node",
node_type="ra3.large",
master_username=DB_LOGIN,
master_user_password=DB_PASS,
)
wait_cluster_available = RedshiftClusterSensor(
task_id="wait_cluster_available",
cluster_identifier=redshift_cluster_identifier,
target_status="available",
poke_interval=100,
timeout=60 * 30,
)
set_up_connection = create_connection(conn_id_name, cluster_id=redshift_cluster_identifier)
create_bucket = S3CreateBucketOperator(
task_id="create_bucket",
bucket_name=s3_bucket_name,
)
create_object = S3CreateObjectOperator(
task_id="create_object",
s3_bucket=s3_bucket_name,
s3_key=s3_key,
data=SAMPLE_DATA,
replace=True,
)
create_table = RedshiftDataOperator(
task_id="create_sample_table",
cluster_identifier=redshift_cluster_identifier,
database=DB_NAME,
db_user=DB_LOGIN,
sql=f"""
CREATE TABLE IF NOT EXISTS {SQL_TABLE_NAME} (
cocktail_id INT NOT NULL,
cocktail_name VARCHAR NOT NULL,
base_spirit VARCHAR NOT NULL);
""",
wait_for_completion=True,
)
# [START howto_transfer_s3_to_sql]
#
# This operator requires a parser method. The Parser should take a filename as input
# and return an iterable of rows.
# This example parser uses the builtin csv library and returns a list of rows
#
def parse_csv_to_list(filepath):
import csv
with open(filepath, newline="") as file:
return list(csv.reader(file))
wait_cluster_available_before_transfer = RedshiftClusterSensor(
task_id="wait_cluster_available_before_transfer",
cluster_identifier=redshift_cluster_identifier,
target_status="available",
poke_interval=100,
timeout=60 * 30,
)
transfer_s3_to_sql = S3ToSqlOperator(
task_id="transfer_s3_to_sql",
s3_bucket=s3_bucket_name,
s3_key=s3_key,
table=SQL_TABLE_NAME,
column_list=SQL_COLUMN_LIST,
parser=parse_csv_to_list,
sql_conn_id=conn_id_name,
)
# [END howto_transfer_s3_to_sql]
# [START howto_transfer_s3_to_sql_generator]
#
# As the parser can return any kind of iterator, a generator is also allowed.
# This example parser returns a generator which prevents python from loading
# the whole file into memory.
#
def parse_csv_to_generator(filepath):
import csv
with open(filepath, newline="") as file:
yield from csv.reader(file)
transfer_s3_to_sql_generator = S3ToSqlOperator(
task_id="transfer_s3_to_sql_paser_to_generator",
s3_bucket=s3_bucket_name,
s3_key=s3_key,
table=SQL_TABLE_NAME,
column_list=SQL_COLUMN_LIST,
parser=parse_csv_to_generator,
sql_conn_id=conn_id_name,
)
# [END howto_transfer_s3_to_sql_generator]
check_table = SQLTableCheckOperator(
task_id="check_table",
conn_id=conn_id_name,
table=SQL_TABLE_NAME,
checks={
"row_count_check": {"check_statement": "COUNT(*) = 6"},
},
)
drop_table = RedshiftDataOperator(
task_id="drop_table",
cluster_identifier=redshift_cluster_identifier,
database=DB_NAME,
db_user=DB_LOGIN,
sql=f"DROP TABLE {SQL_TABLE_NAME}",
wait_for_completion=True,
)
delete_s3_objects = S3DeleteObjectsOperator(
trigger_rule=TriggerRule.ALL_DONE,
task_id="delete_objects",
bucket=s3_bucket_name,
keys=s3_key,
)
delete_s3_bucket = S3DeleteBucketOperator(
trigger_rule=TriggerRule.ALL_DONE,
task_id="delete_bucket",
bucket_name=s3_bucket_name,
force_delete=True,
)
delete_cluster = RedshiftDeleteClusterOperator(
task_id="delete_cluster",
cluster_identifier=redshift_cluster_identifier,
trigger_rule=TriggerRule.ALL_DONE,
max_attempts=50,
)
chain(
# TEST SETUP
test_context,
create_cluster,
wait_cluster_available,
set_up_connection,
create_bucket,
create_object,
create_table,
# TEST BODY
wait_cluster_available_before_transfer,
transfer_s3_to_sql,
transfer_s3_to_sql_generator,
check_table,
# TEST TEARDOWN
drop_table,
delete_s3_objects,
delete_s3_bucket,
delete_cluster,
)
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: contributing-docs/testing/system_tests.rst)
test_run = get_test_run(dag)