This generator reads the specified CDC table names, keys of the specified tables and merge table name and generates a merge query and a python script for each table for Cloud Composer or Apache Airflow. We recommend reading the instructions in the parent module, the Cortex Data Foundation.

The following steps must be completed before running this generator.

• An existing BigQuery Source Dataset that holds all source tables, each of which with recordstamp and operation_flag columns. Adjust the files in the template_dag and template_sql if the fields have different names.
• A GCS bucket created for holding the DAG python scripts and SQL scripts (target bucket).
• A GCS bucket created for logs that this generator writes to (logs bucket).
• config/config.json file with the values required for SAP deployment configuration as described in the Data Foundation README.
• Replicated DD03L table

Configuration file for this repository is config/config.json.

The cloudbuild.cdc.yaml for this generator requires the following parameters:

• _GCS_BUCKET: GCS bucket created for logs that this generator writes to (logs bucket).

• Clone the repository into your Cloud Shell Editor or an IDE of your choice.
• Ensure gcloud SDK is installed, if you choose your own IDE.
• Makes changes in config/config.json as described in the Data Foundation README for SAP deployment (that README refers to config/config.json).
• Make required changes in the settings.yaml to add / delete the required tables and run frequencies. Save the file. - Adjust the sets.yaml to add / delete the required SAP datasets to be flattened and run frequencies. Save the file.

The generator can be run from the Cloud Console using the gcloud builds submit ... command or by configuring a Cloud Builds trigger that runs automatically upon push to a Cloud Source Repository branch

• The generated python scripts will be copied to gs://<targetBucket>/dags
• The generated SQL scripts will be copied to gs://<targetBucket>/data/bq_data_replication

targetBucket - is a GCS bucket created for holding the DAG python scripts and SQL scripts (targetBucket in config/config.json).