Source code for tests.system.amazon.aws.example_s3_to_sql

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from __future__ import annotations

from datetime import datetime

from airflow import settings
from airflow.decorators import task
from airflow.models import Connection
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
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 airflow.utils.trigger_rule import TriggerRule

from providers.tests.system.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder
from tests_common.test_utils.watcher import watcher

# Externally fetched variables:
[docs]SECURITY_GROUP_KEY = "SECURITY_GROUP"
[docs]CLUSTER_SUBNET_GROUP_KEY = "CLUSTER_SUBNET_GROUP"
[docs]sys_test_context_task = ( SystemTestContextBuilder().add_variable(SECURITY_GROUP_KEY).add_variable(CLUSTER_SUBNET_GROUP_KEY).build() )
[docs]DAG_ID = "example_s3_to_sql"
[docs]DB_LOGIN = "adminuser"
[docs]DB_PASS = "MyAmazonPassword1"
[docs]DB_NAME = "dev"
[docs]SQL_TABLE_NAME = "cocktails"
[docs]SQL_COLUMN_LIST = ["cocktail_id", "cocktail_name", "base_spirit"]
[docs]SAMPLE_DATA = r"""1,Caipirinha,Cachaca 2,Bramble,Gin 3,Daiquiri,Rum """
@task
[docs]def create_connection(conn_id_name: str, cluster_id: str): cluster_endpoint = RedshiftHook().conn.describe_clusters(ClusterIdentifier=cluster_id)["Clusters"][0] conn = Connection( conn_id=conn_id_name, conn_type="redshift", host=cluster_endpoint["Endpoint"]["Address"], login=DB_LOGIN, password=DB_PASS, port=cluster_endpoint["Endpoint"]["Port"], schema=cluster_endpoint["DBName"], ) session = settings.Session() session.add(conn) session.commit()
with DAG( dag_id=DAG_ID, start_date=datetime(2023, 1, 1), schedule="@once", catchup=False, tags=["example"], ) as dag:
[docs] 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, cluster_type="single-node", node_type="dc2.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=5, 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)) 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, ) chain( # TEST SETUP test_context, create_cluster, wait_cluster_available, set_up_connection, create_bucket, create_object, create_table, # TEST BODY 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: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)

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