147 lines
5.5 KiB
Python
147 lines
5.5 KiB
Python
# Copyright 2022 Google LLC
|
|
#
|
|
# Licensed 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
|
|
#
|
|
# https://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.
|
|
|
|
# --------------------------------------------------------------------------------
|
|
# Load The Dependencies
|
|
# --------------------------------------------------------------------------------
|
|
|
|
import csv
|
|
import datetime
|
|
import io
|
|
import json
|
|
import logging
|
|
import os
|
|
|
|
from airflow import models
|
|
from airflow.providers.google.cloud.operators.dataflow import DataflowTemplatedJobStartOperator
|
|
from airflow.operators import dummy
|
|
from airflow.providers.google.cloud.operators.bigquery import BigQueryDeleteTableOperator
|
|
from airflow.utils.task_group import TaskGroup
|
|
|
|
# --------------------------------------------------------------------------------
|
|
# Set variables - Needed for the DEMO
|
|
# --------------------------------------------------------------------------------
|
|
BQ_LOCATION = os.environ.get("BQ_LOCATION")
|
|
DATA_CAT_TAGS = json.loads(os.environ.get("DATA_CAT_TAGS"))
|
|
DWH_LAND_PRJ = os.environ.get("DWH_LAND_PRJ")
|
|
DWH_LAND_BQ_DATASET = os.environ.get("DWH_LAND_BQ_DATASET")
|
|
DWH_LAND_GCS = os.environ.get("DWH_LAND_GCS")
|
|
DWH_CURATED_PRJ = os.environ.get("DWH_CURATED_PRJ")
|
|
DWH_CURATED_BQ_DATASET = os.environ.get("DWH_CURATED_BQ_DATASET")
|
|
DWH_CURATED_GCS = os.environ.get("DWH_CURATED_GCS")
|
|
DWH_CONFIDENTIAL_PRJ = os.environ.get("DWH_CONFIDENTIAL_PRJ")
|
|
DWH_CONFIDENTIAL_BQ_DATASET = os.environ.get("DWH_CONFIDENTIAL_BQ_DATASET")
|
|
DWH_CONFIDENTIAL_GCS = os.environ.get("DWH_CONFIDENTIAL_GCS")
|
|
DWH_PLG_PRJ = os.environ.get("DWH_PLG_PRJ")
|
|
DWH_PLG_BQ_DATASET = os.environ.get("DWH_PLG_BQ_DATASET")
|
|
DWH_PLG_GCS = os.environ.get("DWH_PLG_GCS")
|
|
GCP_REGION = os.environ.get("GCP_REGION")
|
|
DRP_PRJ = os.environ.get("DRP_PRJ")
|
|
DRP_BQ = os.environ.get("DRP_BQ")
|
|
DRP_GCS = os.environ.get("DRP_GCS")
|
|
DRP_PS = os.environ.get("DRP_PS")
|
|
LOD_PRJ = os.environ.get("LOD_PRJ")
|
|
LOD_GCS_STAGING = os.environ.get("LOD_GCS_STAGING")
|
|
LOD_NET_VPC = os.environ.get("LOD_NET_VPC")
|
|
LOD_NET_SUBNET = os.environ.get("LOD_NET_SUBNET")
|
|
LOD_SA_DF = os.environ.get("LOD_SA_DF")
|
|
ORC_PRJ = os.environ.get("ORC_PRJ")
|
|
ORC_GCS = os.environ.get("ORC_GCS")
|
|
TRF_PRJ = os.environ.get("TRF_PRJ")
|
|
TRF_GCS_STAGING = os.environ.get("TRF_GCS_STAGING")
|
|
TRF_NET_VPC = os.environ.get("TRF_NET_VPC")
|
|
TRF_NET_SUBNET = os.environ.get("TRF_NET_SUBNET")
|
|
TRF_SA_DF = os.environ.get("TRF_SA_DF")
|
|
TRF_SA_BQ = os.environ.get("TRF_SA_BQ")
|
|
DF_KMS_KEY = os.environ.get("DF_KMS_KEY", "")
|
|
DF_REGION = os.environ.get("GCP_REGION")
|
|
DF_ZONE = os.environ.get("GCP_REGION") + "-b"
|
|
|
|
# --------------------------------------------------------------------------------
|
|
# Set default arguments
|
|
# --------------------------------------------------------------------------------
|
|
|
|
# If you are running Airflow in more than one time zone
|
|
# see https://airflow.apache.org/docs/apache-airflow/stable/timezone.html
|
|
# for best practices
|
|
yesterday = datetime.datetime.now() - datetime.timedelta(days=1)
|
|
|
|
default_args = {
|
|
'owner': 'airflow',
|
|
'start_date': yesterday,
|
|
'depends_on_past': False,
|
|
'email': [''],
|
|
'email_on_failure': False,
|
|
'email_on_retry': False,
|
|
'retries': 1,
|
|
'retry_delay': datetime.timedelta(minutes=5),
|
|
'dataflow_default_options': {
|
|
'location': DF_REGION,
|
|
'zone': DF_ZONE,
|
|
'stagingLocation': LOD_GCS_STAGING,
|
|
'tempLocation': LOD_GCS_STAGING + "/tmp",
|
|
'serviceAccountEmail': LOD_SA_DF,
|
|
'subnetwork': LOD_NET_SUBNET,
|
|
'ipConfiguration': "WORKER_IP_PRIVATE",
|
|
'kmsKeyName' : DF_KMS_KEY
|
|
},
|
|
}
|
|
|
|
# --------------------------------------------------------------------------------
|
|
# Main DAG
|
|
# --------------------------------------------------------------------------------
|
|
|
|
with models.DAG(
|
|
'delete_tables_dag',
|
|
default_args=default_args,
|
|
schedule_interval=None) as dag:
|
|
start = dummy.DummyOperator(
|
|
task_id='start',
|
|
trigger_rule='all_success'
|
|
)
|
|
|
|
end = dummy.DummyOperator(
|
|
task_id='end',
|
|
trigger_rule='all_success'
|
|
)
|
|
|
|
# Bigquery Tables deleted here for demo porpuse.
|
|
# Consider a dedicated pipeline or tool for a real life scenario.
|
|
with TaskGroup('delete_table') as delte_table:
|
|
delete_table_customers = BigQueryDeleteTableOperator(
|
|
task_id="delete_table_customers",
|
|
deletion_dataset_table=DWH_LAND_PRJ+"."+DWH_LAND_BQ_DATASET+".customers",
|
|
impersonation_chain=[TRF_SA_DF]
|
|
)
|
|
|
|
delete_table_purchases = BigQueryDeleteTableOperator(
|
|
task_id="delete_table_purchases",
|
|
deletion_dataset_table=DWH_LAND_PRJ+"."+DWH_LAND_BQ_DATASET+".purchases",
|
|
impersonation_chain=[TRF_SA_DF]
|
|
)
|
|
|
|
delete_table_customer_purchase_curated = BigQueryDeleteTableOperator(
|
|
task_id="delete_table_customer_purchase_curated",
|
|
deletion_dataset_table=DWH_CURATED_PRJ+"."+DWH_CURATED_BQ_DATASET+".customer_purchase",
|
|
impersonation_chain=[TRF_SA_DF]
|
|
)
|
|
|
|
delete_table_customer_purchase_confidential = BigQueryDeleteTableOperator(
|
|
task_id="delete_table_customer_purchase_confidential",
|
|
deletion_dataset_table=DWH_CONFIDENTIAL_PRJ+"."+DWH_CONFIDENTIAL_BQ_DATASET+".customer_purchase",
|
|
impersonation_chain=[TRF_SA_DF]
|
|
)
|
|
|
|
start >> delte_table >> end
|