1. Configuring External Stages for Snowflake ML Data Ingestion


    When ingesting machine learning (ML) data into Snowflake, the use of external stages is common. External stages in Snowflake are references to external storage systems where you can stage data files to be loaded into Snowflake tables. Pulumi can be used to automate the configuration of these stages as part of your infrastructure as code.

    In this context, I'll guide you through the process of configuring an external stage for Snowflake using the Pulumi Snowflake provider in Python. Here's what you'll accomplish with the program:

    1. Create a Snowflake Stage, which acts as a referenced storage location.
    2. Grant necessary permissions to the stage for data ingestion.
    3. Finally, I will explain how to execute simple data ingestion commands (through Snowflake SQL, which will be outside the scope of Pulumi).

    We'll be using the snowflake.Stage and snowflake.StageGrant resources to create the external stage and manage its access respectively.

    Below is the detailed Pulumi program in Python to accomplish this:

    import pulumi import pulumi_snowflake as snowflake # Replace these variables with your specific values STAGE_NAME = "my_ml_data_stage" # Name of the Snowflake stage to create DATABASE_NAME = "my_ml_db" # Name of the Snowflake database SCHEMA_NAME = "public" # Schema where the stage will reside URL = "s3://my-ml-data-bucket" # URL of the external storage (e.g., S3 bucket) STORAGE_INTEGRATION_NAME = "my_aws_integration" # Name of the storage integration in Snowflake # Create a Snowflake Stage resource ml_data_stage = snowflake.Stage("mlDataStage", name=STAGE_NAME, database=DATABASE_NAME, schema=SCHEMA_NAME, url=URL, storage_integration=STORAGE_INTEGRATION_NAME, comment="Stage for ML data ingestion") # Grant USAGE on the external stage to specific Snowflake role(s) stage_grant = snowflake.StageGrant("mlDataStageGrant", database_name=DATABASE_NAME, schema_name=SCHEMA_NAME, stage_name=ml_data_stage.name, privilege="USAGE", roles=["MY_SNOWFLAKE_ROLE"]) # Replace with actual roles needing access # pulumi.export to output the name of the stage pulumi.export('stage_name', ml_data_stage.name)

    Here's what each section accomplishes:

    • The snowflake.Stage resource creates an external stage within a specified database and schema. It references an external storage location (like an AWS S3 bucket provided in the URL) and can be linked to a storage integration for credentials management.
    • The snowflake.StageGrant resource is then used to grant the USAGE privilege to the stage for particular roles, which will allow them to interact with the stage to load data into Snowflake.

    You will need to replace the placeholder values like STAGE_NAME, DATABASE_NAME, SCHEMA_NAME, URL, and STORAGE_INTEGRATION_NAME with your actual Snowflake configuration details.

    After you have this program, run it using the Pulumi CLI to deploy these resources to Snowflake. Make sure you've configured Pulumi with the necessary Snowflake credentials and permissions to create stages and grant permissions.

    Please note that actual data ingestion commands to load data from the stage into Snowflake tables will involve the execution of SQL commands within Snowflake (COPY INTO commands). These operations can be automated with Pulumi in conjunction with other tools or scripts that execute SQL commands but typically are managed separately from the infrastructure code.