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feat: Onboard advertiser_geo_spend table under Google political Ads d…
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…ataset (#154)
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dipannitab2392 committed Aug 31, 2021
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/**
* Copyright 2021 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
*
* 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.
*/


resource "google_bigquery_table" "advertiser_geo_spend" {
project = var.project_id
dataset_id = "google_political_ads"
table_id = "advertiser_geo_spend"

description = "This file contains total US advertiser spend on political ads, per US state and the District of Columbia."




depends_on = [
google_bigquery_dataset.google_political_ads
]
}

output "bigquery_table-advertiser_geo_spend-table_id" {
value = google_bigquery_table.advertiser_geo_spend.table_id
}

output "bigquery_table-advertiser_geo_spend-id" {
value = google_bigquery_table.advertiser_geo_spend.id
}
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# Copyright 2021 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
#
# 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 airflow import DAG
from airflow.contrib.operators import gcs_to_bq, kubernetes_pod_operator

default_args = {
"owner": "Google",
"depends_on_past": False,
"start_date": "2021-03-01",
}


with DAG(
dag_id="google_political_ads.advertiser_geo_spend",
default_args=default_args,
max_active_runs=1,
schedule_interval="@daily",
catchup=False,
default_view="graph",
) as dag:

# Run CSV transform within kubernetes pod
advertiser_geo_spend_transform_csv = kubernetes_pod_operator.KubernetesPodOperator(
task_id="advertiser_geo_spend_transform_csv",
startup_timeout_seconds=600,
name="advertiser_geo_spend",
namespace="default",
image_pull_policy="Always",
image="{{ var.json.google_political_ads.container_registry.run_csv_transform_kub }}",
env_vars={
"SOURCE_URL": "https://storage.googleapis.com/transparencyreport/google-political-ads-transparency-bundle.zip",
"SOURCE_FILE": "files/data.zip",
"FILE_NAME": "google-political-ads-transparency-bundle/google-political-ads-advertiser-geo-spend.csv",
"TARGET_FILE": "files/data_output.csv",
"TARGET_GCS_BUCKET": "{{ var.json.shared.composer_bucket }}",
"TARGET_GCS_PATH": "data/google_political_ads/advertiser_geo_spend/data_output.csv",
"PIPELINE_NAME": "advertiser_geo_spend",
"CSV_HEADERS": '["advertiser_id","advertiser_name","country","country_subdivision_primary","spend_usd","spend_eur","spend_inr","spend_bgn","spend_hrk","spend_czk","spend_dkk","spend_huf","spend_pln","spend_ron","spend_sek","spend_gbp","spend_nzd"]',
"RENAME_MAPPINGS": '{"Advertiser_ID" : "advertiser_id" ,"Advertiser_Name" : "advertiser_name" ,"Country" : "country" ,"Country_Subdivision_Primary" : "country_subdivision_primary" ,"Spend_USD" : "spend_usd" ,"Spend_EUR" : "spend_eur" ,"Spend_INR" : "spend_inr" ,"Spend_BGN" : "spend_bgn" ,"Spend_HRK" : "spend_hrk" ,"Spend_CZK" : "spend_czk" ,"Spend_DKK" : "spend_dkk" ,"Spend_HUF" : "spend_huf" ,"Spend_PLN" : "spend_pln" ,"Spend_RON" : "spend_ron" ,"Spend_SEK" : "spend_sek" ,"Spend_GBP" : "spend_gbp" ,"Spend_NZD" : "spend_nzd"}',
},
resources={"request_memory": "2G", "request_cpu": "1"},
)

# Task to load CSV data to a BigQuery table
load_advertiser_geo_spend_to_bq = gcs_to_bq.GoogleCloudStorageToBigQueryOperator(
task_id="load_advertiser_geo_spend_to_bq",
bucket="{{ var.json.shared.composer_bucket }}",
source_objects=[
"data/google_political_ads/advertiser_geo_spend/data_output.csv"
],
source_format="CSV",
destination_project_dataset_table="google_political_ads.advertiser_geo_spend",
skip_leading_rows=1,
write_disposition="WRITE_TRUNCATE",
schema_fields=[
{
"name": "advertiser_id",
"type": "string",
"description": "Unique ID for an advertiser verified to run election ads on Google Ads Services.",
"mode": "nullable",
},
{
"name": "advertiser_name",
"type": "string",
"description": "Name of the advertiser.",
"mode": "nullable",
},
{
"name": "country",
"type": "string",
"description": 'The country where election ads were served specified in the ISO 3166-1 alpha-2 standard code. For example: "US" for United States.',
"mode": "nullable",
},
{
"name": "country_subdivision_primary",
"type": "string",
"description": 'The primary subdivision of the country where election ads were served specified by the ISO 3166-2 standard code. For example: "US-CA" for California state in United States',
"mode": "nullable",
},
{
"name": "spend_usd",
"type": "integer",
"description": "Total amount in USD spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_eur",
"type": "integer",
"description": "Total amount in EUR spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_inr",
"type": "integer",
"description": "Total amount in INR spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_bgn",
"type": "integer",
"description": "Total amount in BGN spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_hrk",
"type": "integer",
"description": "Total amount in HRK spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_czk",
"type": "integer",
"description": "Total amount in CZK spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_dkk",
"type": "integer",
"description": "Total amount in DKK spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_huf",
"type": "integer",
"description": "Total amount in HUF spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_pln",
"type": "integer",
"description": "Total amount in PLN spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_ron",
"type": "integer",
"description": "Total amount in RON spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_sek",
"type": "integer",
"description": "Total amount in SEK spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_gbp",
"type": "integer",
"description": "Total amount in GBP spent on election ads in this region.",
"mode": "nullable",
},
{
"name": "spend_nzd",
"type": "integer",
"description": "Total amount in NZD spent on election ads in this region.",
"mode": "nullable",
},
],
)

advertiser_geo_spend_transform_csv >> load_advertiser_geo_spend_to_bq
181 changes: 181 additions & 0 deletions datasets/google_political_ads/advertiser_geo_spend/pipeline.yaml
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# Copyright 2021 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
#
# 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.

---
resources:

- type: bigquery_table
# Required Properties:
table_id: advertiser_geo_spend

# Description of the table
description: "This file contains total US advertiser spend on political ads, per US state and the District of Columbia."

dag:
airflow_version: 1
initialize:
dag_id: advertiser_geo_spend
default_args:
owner: "Google"

# When set to True, keeps a task from getting triggered if the previous schedule for the task hasn’t succeeded
depends_on_past: False
start_date: "2021-03-01"
max_active_runs: 1
schedule_interval: "@daily"
catchup: False
default_view: graph

tasks:
- operator: "KubernetesPodOperator"

# Task description
description: "Run CSV transform within kubernetes pod"

args:

task_id: "advertiser_geo_spend_transform_csv"

startup_timeout_seconds: 600

# The name of the pod in which the task will run. This will be used (plus a random suffix) to generate a pod id
name: "advertiser_geo_spend"

# The namespace to run within Kubernetes. Always set its value to "default" because we follow the guideline that KubernetesPodOperator will only be used for very light workloads, i.e. use the Cloud Composer environment"s resources without starving other pipelines.
namespace: "default"

image_pull_policy: "Always"

# Docker images will be built and pushed to GCR by default whenever the `scripts/generate_dag.py` is run. To skip building and pushing images, use the optional `--skip-builds` flag.
image: "{{ var.json.google_political_ads.container_registry.run_csv_transform_kub }}"

# Set the environment variables you need initialized in the container. Use these as input variables for the script your container is expected to perform.
env_vars:
SOURCE_URL: "https://storage.googleapis.com/transparencyreport/google-political-ads-transparency-bundle.zip"
SOURCE_FILE: "files/data.zip"
FILE_NAME: "google-political-ads-transparency-bundle/google-political-ads-advertiser-geo-spend.csv"
TARGET_FILE: "files/data_output.csv"
TARGET_GCS_BUCKET: "{{ var.json.shared.composer_bucket }}"
TARGET_GCS_PATH: "data/google_political_ads/advertiser_geo_spend/data_output.csv"
PIPELINE_NAME: "advertiser_geo_spend"
CSV_HEADERS: >-
["advertiser_id","advertiser_name","country","country_subdivision_primary","spend_usd","spend_eur","spend_inr","spend_bgn","spend_hrk","spend_czk","spend_dkk","spend_huf","spend_pln","spend_ron","spend_sek","spend_gbp","spend_nzd"]
RENAME_MAPPINGS: >-
{"Advertiser_ID" : "advertiser_id" ,"Advertiser_Name" : "advertiser_name" ,"Country" : "country" ,"Country_Subdivision_Primary" : "country_subdivision_primary" ,"Spend_USD" : "spend_usd" ,"Spend_EUR" : "spend_eur" ,"Spend_INR" : "spend_inr" ,"Spend_BGN" : "spend_bgn" ,"Spend_HRK" : "spend_hrk" ,"Spend_CZK" : "spend_czk" ,"Spend_DKK" : "spend_dkk" ,"Spend_HUF" : "spend_huf" ,"Spend_PLN" : "spend_pln" ,"Spend_RON" : "spend_ron" ,"Spend_SEK" : "spend_sek" ,"Spend_GBP" : "spend_gbp" ,"Spend_NZD" : "spend_nzd"}
# Set resource limits for the pod here. For resource units in Kubernetes, see https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#resource-units-in-kubernetes
resources:
request_memory: "2G"
request_cpu: "1"

- operator: "GoogleCloudStorageToBigQueryOperator"
description: "Task to load CSV data to a BigQuery table"

args:
task_id: "load_advertiser_geo_spend_to_bq"

# The GCS bucket where the CSV file is located in.
bucket: "{{ var.json.shared.composer_bucket }}"

# The GCS object path for the CSV file
source_objects: ["data/google_political_ads/advertiser_geo_spend/data_output.csv"]
source_format: "CSV"
destination_project_dataset_table: "google_political_ads.advertiser_geo_spend"

# Use this if your CSV file contains a header row
skip_leading_rows: 1

# How to write data to the table: overwrite, append, or write if empty
# See https://cloud.google.com/bigquery/docs/reference/auditlogs/rest/Shared.Types/WriteDisposition
write_disposition: "WRITE_TRUNCATE"

# The BigQuery table schema based on the CSV file. For more info, see
# https://cloud.google.com/bigquery/docs/schemas.
# Always use snake_case and lowercase for column names, and be explicit,
# i.e. specify modes for all columns.

schema_fields:
- name: "advertiser_id"
type: "string"
description: "Unique ID for an advertiser verified to run election ads on Google Ads Services."
mode: "nullable"
- name: "advertiser_name"
type: "string"
description: "Name of the advertiser."
mode: "nullable"
- name: "country"
type: "string"
description: "The country where election ads were served specified in the ISO 3166-1 alpha-2 standard code. For example: \"US\" for United States."
mode: "nullable"
- name: "country_subdivision_primary"
type: "string"
description: "The primary subdivision of the country where election ads were served specified by the ISO 3166-2 standard code. For example: \"US-CA\" for California state in United States"
mode: "nullable"
- name: "spend_usd"
type: "integer"
description: "Total amount in USD spent on election ads in this region."
mode: "nullable"
- name: "spend_eur"
type: "integer"
description: "Total amount in EUR spent on election ads in this region."
mode: "nullable"
- name: "spend_inr"
type: "integer"
description: "Total amount in INR spent on election ads in this region."
mode: "nullable"
- name: "spend_bgn"
type: "integer"
description: "Total amount in BGN spent on election ads in this region."
mode: "nullable"
- name: "spend_hrk"
type: "integer"
description: "Total amount in HRK spent on election ads in this region."
mode: "nullable"
- name: "spend_czk"
type: "integer"
description: "Total amount in CZK spent on election ads in this region."
mode: "nullable"
- name: "spend_dkk"
type: "integer"
description: "Total amount in DKK spent on election ads in this region."
mode: "nullable"
- name: "spend_huf"
type: "integer"
description: "Total amount in HUF spent on election ads in this region."
mode: "nullable"
- name: "spend_pln"
type: "integer"
description: "Total amount in PLN spent on election ads in this region."
mode: "nullable"
- name: "spend_ron"
type: "integer"
description: "Total amount in RON spent on election ads in this region."
mode: "nullable"
- name: "spend_sek"
type: "integer"
description: "Total amount in SEK spent on election ads in this region."
mode: "nullable"
- name: "spend_gbp"
type: "integer"
description: "Total amount in GBP spent on election ads in this region."
mode: "nullable"
- name: "spend_nzd"
type: "integer"
description: "Total amount in NZD spent on election ads in this region."
mode: "nullable"


graph_paths:
- "advertiser_geo_spend_transform_csv >> load_advertiser_geo_spend_to_bq"

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