Run this DAG

1. Install the Astronomer CLI:Skip if you already have the CLI

2. Initate the project in a local directory:

3. Copy and paste the code below into a file in the

dags
directory.

4. Add the following to your

requirements.txt
file:

5. Run the DAG from the local directory where the project was initiated:

# 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.
"""
Example Airflow DAG that shows how to use SalesforceToGcsOperator.
"""
from __future__ import annotations
import os
from datetime import datetime
from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.bigquery import (
BigQueryCreateEmptyDatasetOperator,
BigQueryCreateEmptyTableOperator,
BigQueryDeleteDatasetOperator,
BigQueryInsertJobOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.transfers.gcs_to_bigquery import GCSToBigQueryOperator
from airflow.providers.google.cloud.transfers.salesforce_to_gcs import SalesforceToGcsOperator
GCP_PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project")
GCS_BUCKET = os.environ.get("GCS_BUCKET", "airflow-salesforce-bucket")
DATASET_NAME = os.environ.get("SALESFORCE_DATASET_NAME", "salesforce_test_dataset")
TABLE_NAME = os.environ.get("SALESFORCE_TABLE_NAME", "salesforce_test_datatable")
GCS_OBJ_PATH = os.environ.get("GCS_OBJ_PATH", "results.csv")
QUERY = "SELECT Id, Name, Company, Phone, Email, CreatedDate, LastModifiedDate, IsDeleted FROM Lead"
GCS_CONN_ID = os.environ.get("GCS_CONN_ID", "google_cloud_default")
SALESFORCE_CONN_ID = os.environ.get("SALESFORCE_CONN_ID", "salesforce_default")
with DAG(
"example_salesforce_to_gcs",
start_date=datetime(2021, 1, 1),
catchup=False,
) as dag:
create_bucket = GCSCreateBucketOperator(
task_id="create_bucket",
bucket_name=GCS_BUCKET,
project_id=GCP_PROJECT_ID,
gcp_conn_id=GCS_CONN_ID,
)
# [START howto_operator_salesforce_to_gcs]
gcs_upload_task = SalesforceToGcsOperator(
query=QUERY,
include_deleted=True,
bucket_name=GCS_BUCKET,
object_name=GCS_OBJ_PATH,
salesforce_conn_id=SALESFORCE_CONN_ID,
export_format="csv",
coerce_to_timestamp=False,
record_time_added=False,
gcp_conn_id=GCS_CONN_ID,
task_id="upload_to_gcs",
dag=dag,
)
# [END howto_operator_salesforce_to_gcs]
create_dataset = BigQueryCreateEmptyDatasetOperator(
task_id="create_dataset", dataset_id=DATASET_NAME, project_id=GCP_PROJECT_ID, gcp_conn_id=GCS_CONN_ID
)
create_table = BigQueryCreateEmptyTableOperator(
task_id="create_table",
dataset_id=DATASET_NAME,
table_id=TABLE_NAME,
schema_fields=[
{"name": "id", "type": "STRING", "mode": "NULLABLE"},
{"name": "name", "type": "STRING", "mode": "NULLABLE"},
{"name": "company", "type": "STRING", "mode": "NULLABLE"},
{"name": "phone", "type": "STRING", "mode": "NULLABLE"},
{"name": "email", "type": "STRING", "mode": "NULLABLE"},
{"name": "createddate", "type": "STRING", "mode": "NULLABLE"},
{"name": "lastmodifieddate", "type": "STRING", "mode": "NULLABLE"},
{"name": "isdeleted", "type": "BOOL", "mode": "NULLABLE"},
],
)
load_csv = GCSToBigQueryOperator(
task_id="gcs_to_bq",
bucket=GCS_BUCKET,
source_objects=[GCS_OBJ_PATH],
destination_project_dataset_table=f"{DATASET_NAME}.{TABLE_NAME}",
write_disposition="WRITE_TRUNCATE",
)
read_data_from_gcs = BigQueryInsertJobOperator(
task_id="read_data_from_gcs",
configuration={
"query": {
"query": f"SELECT COUNT(*) FROM `{GCP_PROJECT_ID}.{DATASET_NAME}.{TABLE_NAME}`",
"useLegacySql": False,
}
},
)
delete_bucket = GCSDeleteBucketOperator(
task_id="delete_bucket",
bucket_name=GCS_BUCKET,
)
delete_dataset = BigQueryDeleteDatasetOperator(
task_id="delete_dataset",
project_id=GCP_PROJECT_ID,
dataset_id=DATASET_NAME,
delete_contents=True,
)
create_bucket >> gcs_upload_task >> load_csv
create_dataset >> create_table >> load_csv
load_csv >> read_data_from_gcs
read_data_from_gcs >> delete_bucket
read_data_from_gcs >> delete_dataset