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Install the RAI Native App for Snowflake

Follow these steps to install and set up the RelationalAI (RAI) Native App for Snowflake.

Request Access

Section titled “Request Access”

  1. Log in to Snowsight as an ORGADMIN or ACCOUNTADMIN.

  2. View the RelationalAI marketplace listing and fill out the access request form.

  3. A RelationalAI representative will notify you when access is enabled for your account.

Install the App

Section titled “Install the App”

Once access is enabled, navigate to Data Products > Apps in the left-hand sidebar in Snowsight. You should see RelationalAI under Recently Shared with You.

  1. Click Buy to open a dialogue box with pricing details. Click the Buy button in the dialogue box to proceed. Click “View your apps” in the resulting modal to go back to the Data Products > Apps page. You should see RelationalAI listed under Installed Apps.

  2. You may see a spinner in the INSTALLED column, indicating that the app is still being installed. Wait until installation completes, at which point you’ll see a message like “1 minute ago” in that column.

  3. Click on the name of the application to open the app.

  4. Click Grant to grant the application the necessary privileges.

    • The EXECUTE TASK and EXECUTE MANAGED TASK privileges are required to share data from your Snowflake account with the RAI Native App.
    • The CREATE WAREHOUSE and CREATE COMPUTE POOL privileges are required by the RAI Native App to create and manage resources for performing service operations.
    • The optional BIND SERVICE ENDPOINT privilege is required only if you need to use certain experimental features of the RAI Native App.

  5. Click Activate to activate the application.

Set Up the App

Section titled “Set Up the App”

To finalize the installation, you need to execute a few SQL commands to set up and configure the app. You can do this in a Snowflake notebook, a SQL worksheet, or using the SnowSQL command-line client.

To complete the steps in this section:

  1. Download the installation notebook.
    View a preview of the installation notebook.

    RelationalAI Native App Setup Guide

    🚨 Note that the ACCOUNTADMIN role is used in this guide. This role is needed for Step 1 and for creating the network rule in Step 4. To manage roles specific the RelationalAI Native App, see Appendix 2 at the bottom of this notebook.

    USE ROLE ACCOUNTADMIN;

    Step 1 - Activate the RAI Native App

    The Grant button under Data Products > Apps > RelationalAI in Snowsight runs the following SQL command to grant the necessary permissions to the app. If you haven’t clicked that button yet, you can run the code here instead. It doesn’t hurt to run it again if you’re not sure.

    GRANT
          EXECUTE TASK,
          EXECUTE MANAGED TASK,
          CREATE COMPUTE POOL,
          CREATE WAREHOUSE
    ON ACCOUNT TO APPLICATION RELATIONALAI;

    Now execute the following three cells to create the RAI service (this usually takes between 5 and 15 minutes):

    import sys
    import time
    import json
    import itertools
    

    session = get_active_session()
    

    def poll(f):
    

        last_message = ""
        dots = itertools.cycle(["⠧", "⠏", "⠛", "⠹", "⠼", "⠶"])
    

        def status(message):
            spaces = " " * (len("⠿ " + last_message) - len(message))
            sys.stdout.write("\r" + message + spaces)
            sys.stdout.flush()
    

        for ctr in itertools.count():
            if ctr % 10 == 0:
                result = f()
                if isinstance(result, str):
                    message = next(dots) + " " + result
                    status(message)
                    last_message = result
                if result is True:
                    status("⠿ Done!")
                    return
            else:
                message = next(dots) + " " + last_message
                status(message)
            time.sleep(0.5)
    def activate():
        try:
            session.sql("CALL RELATIONALAI.APP.ACTIVATE();").collect()
            return True
        except Exception as e:
            if "Unknown user-defined function" in str(e):
                return "Waiting for app installation to complete..."
            else:
                raise e
    

    poll(activate)
    def check():
        result = session.sql("CALL RELATIONALAI.APP.SERVICE_STATUS();").collect()
        status = json.loads(result[0]["SERVICE_STATUS"])[0]["message"]
        if status.startswith("UNKNOWN"):
            status = "Working"
        if status.startswith("Readiness probe"):
            status = "Almost done"
        if status == "Running":
            return True
        else:
            return status + "..."
    

    poll(check)

    🚨 Note: Please review the documentation on upgrades for details about the weekly automatic upgrade schedule.

    Step 2 - Setting up Change Data Capture

    Streams share Snowflake data with the RAI Native App using change data capture (CDC) to capture source table and view changes once every minute.

    To enable CDC, run the following command:

    CALL RELATIONALAI.APP.RESUME_CDC();

    Step 3 - Creating user roles

    The RAI Native App comes with a set of Snowflake application roles for managing access to the app. Application roles can’t be granted to users directly, and must be granted to Snowflake database roles instead.

    The following SQL creates two database roles: rai_admin and rai_developer. The rai_admin role is for full admin access to the RAI Native App, while the rai_developer role is for developers who need access to the RAI Python API:

    -- Create a rai_admin role for full admin access to the RAI Native App.
    CREATE ROLE rai_admin;
    -- Link the app's `all_admin` role to the created role.
    GRANT APPLICATION ROLE relationalai.all_admin TO ROLE rai_admin;
    

    -- Create a role for developers who need access to the RAI Python API.
    CREATE ROLE rai_developer;
    -- Link the app's `rai_user` role to the created role.
    GRANT APPLICATION ROLE relationalai.rai_user TO ROLE rai_developer;

    Users granted the rai_developer role can:

    • Use the RAI Native App.
    • Create, use, and delete RAI engines.
    • Create, manage, and delete data streams.
    • Enable and disable the CDC service.

    You can grant the rai_developer role to users in your Snowflake account using the GRANT ROLE rai_developer TO USER "username"; command. For example, to grant the rai_developer role to yourself, run the following cell:

    # optional: grant the rai_developer role to yourself
    session = get_active_session()
    current_user = session.sql("SELECT CURRENT_USER() AS USERNAME;").collect()[0]["USERNAME"]
    

    session.sql(f'GRANT ROLE rai_developer TO USER "{current_user}"').collect()

    Our Simple Start notebook uses a table called RAI_DEMO.SIMPLE_START.CONNECTIONS. If you want to be able to run that notebook, either grant permissions to the rai_developer role or run the following SQL to create the table now. You can clean up this database when you’re done with the demo notebook by running DROP DATABASE RAI_DEMO CASCADE;

    CREATE DATABASE IF NOT EXISTS RAI_DEMO;
    CREATE SCHEMA IF NOT EXISTS RAI_DEMO.SIMPLE_START;
    

    CREATE OR REPLACE TABLE RAI_DEMO.SIMPLE_START.CONNECTIONS (
        STATION_1 INT,
        STATION_2 INT
    );
    

    INSERT INTO RAI_DEMO.SIMPLE_START.CONNECTIONS (STATION_1, STATION_2) VALUES
    (1, 2),
    (1, 3),
    (3, 4),
    (1, 4),
    (4, 5),
    (5, 7),
    (6, 7),
    (6, 8),
    (7, 8);
    

    GRANT USAGE ON DATABASE RAI_DEMO TO ROLE rai_developer;
    GRANT USAGE ON SCHEMA RAI_DEMO.SIMPLE_START TO ROLE rai_developer;
    GRANT SELECT ON TABLE RAI_DEMO.SIMPLE_START.CONNECTIONS TO ROLE rai_developer;
    ALTER TABLE RAI_DEMO.SIMPLE_START.CONNECTIONS SET CHANGE_TRACKING = TRUE;
    

    -- optional: give rai_developer more extensive permissions in the RAI_DEMO database
    -- this step is necessary for the user to be able to run all the demo notebooks
    GRANT CREATE SCHEMA ON DATABASE RAI_DEMO TO ROLE rai_developer;
    GRANT CREATE TABLE ON SCHEMA RAI_DEMO.SIMPLE_START TO ROLE rai_developer;
    GRANT CREATE TABLE ON FUTURE SCHEMAS IN DATABASE RAI_DEMO TO ROLE rai_developer;
    GRANT SELECT ON ALL TABLES IN SCHEMA RAI_DEMO.SIMPLE_START TO ROLE rai_developer;
    GRANT SELECT ON FUTURE TABLES IN DATABASE RAI_DEMO TO ROLE rai_developer;

    Step 4 — Setting up Snowflake Notebooks

    Snowflake offers two options when you create a new Snowflake Notebook: Run on Warehouse and Run on Container. We recommend using container notebooks because they support the use of pip to install the latest version of the RelationalAI Python library.

    For more information on using RelationalAI in Snowflake Notebooks, see Using RAI in a Cloud Notebook in the RelationalAI documentation.

    Container Notebooks

    Container notebooks do require a bit of additional setup because (1) they can’t be executed with account administrator privileges, and (2) they require you to select a compute pool when creating a notebook.

    The SQL code below sets up all the necessary resources and permissions to simplify the process of using Container notebooks:

    -- create a database to contain the notebooks
    CREATE DATABASE rai_notebooks;
    

    -- create a warehouse to select when creating a notebook
    CREATE WAREHOUSE notebooks_wh;
    

    -- create a compute pool to use when creating a notebook
    CREATE COMPUTE POOL NOTEBOOK_CPU_XS
      MIN_NODES = 1
      MAX_NODES = 15
      INSTANCE_FAMILY = CPU_X64_XS
      AUTO_RESUME = true
      AUTO_SUSPEND_SECS = 1800
      COMMENT = "Pool for Snowflake Notebooks on Container Runtime";
    

    -- grant the necessary permissions to the rai_developer role
    GRANT USAGE ON DATABASE rai_notebooks TO ROLE rai_developer;
    GRANT USAGE ON SCHEMA rai_notebooks.public TO ROLE rai_developer;
    GRANT CREATE NOTEBOOK ON SCHEMA rai_notebooks.public TO ROLE rai_developer;
    GRANT USAGE ON WAREHOUSE notebooks_wh TO ROLE rai_developer;
    GRANT USAGE ON COMPUTE POOL NOTEBOOK_CPU_XS TO ROLE rai_developer;
    GRANT CREATE SERVICE ON SCHEMA rai_notebooks.public TO ROLE rai_developer;

    If you want to be able to install Python packages from PyPI in your notebooks, run the code below to set up an External Access Integration:

    If you don’t want to enable a PyPI integration, you can skip this step. Notebook users can import the RelationalAI Python library by uploading a ZIP file instead.

    -- grant the necessary permissions to the rai_developer role
    CREATE OR REPLACE NETWORK RULE pypi_network_rule
    MODE = EGRESS
    TYPE = HOST_PORT
    VALUE_LIST = ('pypi.org', 'pypi.python.org', 'pythonhosted.org',  'files.pythonhosted.org');
    

    CREATE OR REPLACE EXTERNAL ACCESS INTEGRATION pypi_access_integration
    ALLOWED_NETWORK_RULES = (pypi_network_rule)
    ENABLED = true;
    

    GRANT USAGE ON INTEGRATION pypi_access_integration TO ROLE rai_developer;

    Warehouse Notebooks

    The RelationalAI Python library requires an External Access Integration to work on notebooks that run on a warehouse. This integration allows the app to pass query results back to the notebook. Run the following code to set up the integration:

    session = get_active_session()
    

    system_allowlist = session.sql("""
    SELECT value:host AS URL
    FROM TABLE(FLATTEN(input=>parse_json(SYSTEM$ALLOWLIST())))
    WHERE value:type = 'STAGE'
    """).collect()
    

    if system_allowlist:
        urls = ", ".join(row.URL.replace('"', "'") for row in system_allowlist)
        egress_rule_commands = [
            f"""
            CREATE OR REPLACE NETWORK RULE S3_RAI_INTERNAL_BUCKET_EGRESS
            MODE = EGRESS
            TYPE = HOST_PORT
            VALUE_LIST = ({urls});
            """,
            """
            CREATE OR REPLACE EXTERNAL ACCESS INTEGRATION S3_RAI_INTERNAL_BUCKET_EGRESS_INTEGRATION
            ALLOWED_NETWORK_RULES = (S3_RAI_INTERNAL_BUCKET_EGRESS)
            ENABLED = true;
            """,
            """
            GRANT USAGE ON INTEGRATION S3_RAI_INTERNAL_BUCKET_EGRESS_INTEGRATION TO ROLE rai_developer;
            """
        ]
    

        for command in egress_rule_commands:
            session.sql(command).collect()
    

        print("Network rule set up successfully.")

    Congratulations! Your RelationalAI app is now ready to use.

    Next Steps

    To get up and running with RelationalAI in Snowflake Notebooks, download the Simple Start Snowflake Notebook, upload it to your Snowflake account (https://app.snowflake.com > + icon in left sidebar > Notebooks > Import .ipynb file), and follow the instructions in the notebook.

    To use a local Python installation instead, download the Simple Start Jupyter notebook and follow the instructions for running the notebook.

    For a more detailed example and more information about the RelationalAI Python library, check out the Getting Started guide.

    Links:

    APPENDIX 1 - Deactivate the RAI Native App

    To reduce costs when you are not using the RAI Native App, suspend CDC, and delete all engines.

    🚨 Note that this task requires the app_admin application role.

    session = get_active_session()
    # note: the use of `skip_appendix` in the Appendices makes the notebook's
    # "Run All" action skip these cells
    skip_appendix = True
    

    # Deactivate the app
    if not skip_appendix:
        session.sql("CALL RELATIONALAI.APP.DEACTIVATE();").collect()
    

    # To re-activate the app:
    # session.sql("CALL RELATIONALAI.APP.ACTIVATE();").collect()

    APPENDIX 2 - App Upgrades

    Your RAI Native App is automatically upgraded every Monday at 10:00 UTC. During upgrades, the application cannot process RAI transactions.

    If you prefer to schedule upgrades for a different day and time, use the schedule_upgrade() procedure:

    if not skip_appendix:
        # Schedule upgrades for Wednesdays at 15:00 UTC. Times are in 24-hour format.
        session.sql("CALL relationalai.app.schedule_upgrade('WEDNESDAY', '15:00');").collect()
  2. Go to https://app.snowflake.com and select + Create Projects > Notebook > Import .ipynb File at the top of the left sidebar.
  3. Upload the relationalai-installation.ipynb file.
  4. Choose a database and schema to save the notebook in.
    • Any database and schema will do — you can delete the notebook after installation.
    • If you don’t have any database available in the dropdown, you can create one by doing create database <name>; from a SQL worksheet.
  5. Choose Run on warehouse and click Create.
  6. Click the Run All button or run the cells one at a time.

Run a Demo Notebook (Optional)

Section titled “Run a Demo Notebook (Optional)”

If, after completing the installation steps above, you want to run a demo notebook in Snowsight, then:

  1. Download the Simple Start Notebook
  2. Refresh the browser page and use the account menu button in the bottom-left corner to switch your role to RAI_USER.
  3. Repeat the notebook import process (+ Create Projects > Notebook > Import .ipynb File) and select simple-start-snowflake.ipynb. This time choose Run on container, and select the compute pool you created in the installation notebook (NOTEBOOK_CPU_XS).
  4. Follow the instructions in the demo notebook:
    1. From the vertical ellipsis icon (⋮) in the top-right corner, do Notebook settings > External access and toggle the PYPI_ACCESS_INTEGRATION switch to the on position.
    2. Execute the cells in the notebook. The first one installs the RelationalAI library as well as the other two libraries used in the notebook (matplotlib and networkx).

Install the RAI CLI (Optional)

Section titled “Install the RAI CLI (Optional)”

Although you may manage the RAI Native App using SQL procedures, the RAI command-line interface (CLI) provides a more streamlined experience for common management tasks.

The RAI CLI is included in the relationalai Python package, which supports Python 3.9, 3.10, and 3.11.

Besides the CLI, the relationalai package serves as the main interface for creating and managing models in RAI and accessing the advanced features of the RAI Native App.

To install the package, follow the installation instructions.