SYSTEM$CREATE_SEMANTIC_VIEW_FROM_OSI_YAML¶

Creates a semantic view from a semantic model specification written in Open Semantic Interchange (OSI) YAML format.

OSI is an open standard for representing semantic models that enables interoperability across AI and BI tools. This stored procedure accepts an OSI YAML document, converts it to the Snowflake semantic model format, and creates the corresponding semantic view in the specified schema. If a semantic view with the same name already exists, the procedure attempts to replace it while preserving existing grants. This has the same effect as running CREATE OR REPLACE SEMANTIC VIEW … COPY GRANTS.

See also:

SYSTEM$READ_OSI_YAML_FROM_SEMANTIC_VIEW , SYSTEM$CREATE_SEMANTIC_VIEW_FROM_YAML , CREATE SEMANTIC VIEW

Syntax¶

SYSTEM$CREATE_SEMANTIC_VIEW_FROM_OSI_YAML(
  '<fully_qualified_schema_name>' ,
  '<osi_yaml_specification>'
)

Arguments¶

'fully_qualified_schema_name'

Fully qualified name of the schema where you want to create the semantic view, in the form database_name.schema_name.

You must qualify the schema name with the database name (for example, my_db.my_schema). Otherwise, an error occurs.

'osi_yaml_specification'

The semantic model definition as a YAML string conforming to the OSI Core Metadata Spec.

If the specification contains quotes, backslashes, or newlines, you can use a dollar-quoted string constant for this argument.

Returns¶

On success, returns the following VARCHAR string:

Semantic view was successfully created from OSI YAML.

If the OSI YAML is invalid, the schema isn’t found, column references can’t be resolved, or any other validation error occurs, the procedure raises an exception with a descriptive error message.

Access control requirements¶

OSI YAML specification¶

The top-level fields that Snowflake recognizes in the OSI YAML are:

Dataset fields¶

Each entry in datasets maps to a table in the Snowflake semantic view.

Field classification¶

Each entry in datasets[*].fields is converted to one of three Snowflake column types based on its dimension marker:

Each field must specify an expression with at least one supported dialect entry:

expression:
  dialects:
    - dialect: SNOWFLAKE
      expression: "order_date"
    - dialect: ANSI_SQL
      expression: "order_date"

Snowflake prefers the SNOWFLAKE dialect. If not present, it falls back to ANSI_SQL. Fields that have no SNOWFLAKE or ANSI_SQL dialect expression are silently skipped during conversion.

Relationship fields¶

Metric fields¶

Metrics without a SNOWFLAKE or ANSI_SQL dialect expression are silently skipped.

Usage notes¶

• The version field in the OSI YAML must be a supported version. Currently supported: 0.1.1. Unsupported versions cause the procedure to raise an error listing the supported values.
• The semantic view name is taken from the name field in the OSI YAML. The view is created in the schema identified by fully_qualified_schema_name.
• Expression dialect priority: SNOWFLAKE is used when present; otherwise ANSI_SQL is used as a fallback. Fields or metrics that have only non-supported dialects are silently omitted from the created view.
• Dataset source values are parsed as follows:
  • A string starting with SELECT or WITH is treated as an inline subquery and mapped to base_table.definition.
  • A dotted identifier such as sales_db.public.orders is resolved to base_table.database / schema / table.
  • Unrecognized source strings are ignored (no base_table is set).
• OSI metadata not natively represented in Snowflake’s semantic view format (ai_context, custom_extensions, version) is preserved in the view’s extension metadata.

If the name of the database or schema is a double-quoted identifier (for example, if the name contains spaces), you must include double quotes around the name. For example:

CALL SYSTEM$CREATE_SEMANTIC_VIEW_FROM_OSI_YAML(
  '"my database"."my schema"',
  ...
);

OSI field-to-Snowflake mapping reference¶

Examples¶

Create a semantic view from a minimal OSI YAML¶

CALL SYSTEM$CREATE_SEMANTIC_VIEW_FROM_OSI_YAML(
  'my_db.my_schema',
  $$
  version: "0.1.1"
  name: sales_model
  description: "Core sales semantic model"
  datasets:
    - name: orders
      source: my_db.public.orders
      description: "Order fact table"
      primary_key:
        - order_id
      fields:
        - name: order_id
          expression:
            dialects:
              - dialect: SNOWFLAKE
                expression: order_id
          dimension:
            is_time: false
        - name: order_date
          expression:
            dialects:
              - dialect: SNOWFLAKE
                expression: order_date
          dimension:
            is_time: true
        - name: total_amount
          expression:
            dialects:
              - dialect: SNOWFLAKE
                expression: total_amount
  metrics:
    - name: total_revenue
      description: "Sum of all order amounts"
      expression:
        dialects:
          - dialect: SNOWFLAKE
            expression: "SUM(total_amount)"
  $$
);

Create a semantic view with multiple datasets and a relationship¶

CALL SYSTEM$CREATE_SEMANTIC_VIEW_FROM_OSI_YAML(
  'my_db.my_schema',
  $$
  version: "0.1.1"
  name: ecommerce_model
  description: "E-commerce semantic model with orders and customers"
  datasets:
    - name: orders
      source: my_db.public.orders
      primary_key:
        - order_id
      fields:
        - name: order_id
          expression:
            dialects:
              - dialect: SNOWFLAKE
                expression: order_id
          dimension:
            is_time: false
        - name: order_date
          expression:
            dialects:
              - dialect: SNOWFLAKE
                expression: order_date
          dimension:
            is_time: true
        - name: revenue
          expression:
            dialects:
              - dialect: SNOWFLAKE
                expression: total_amount
    - name: customers
      source: my_db.public.customers
      primary_key:
        - customer_id
      fields:
        - name: customer_id
          expression:
            dialects:
              - dialect: SNOWFLAKE
                expression: customer_id
          dimension:
            is_time: false
        - name: customer_name
          expression:
            dialects:
              - dialect: SNOWFLAKE
                expression: "first_name || ' ' || last_name"
          dimension:
            is_time: false
  relationships:
    - name: orders_to_customers
      from: orders
      to: customers
      from_columns:
        - customer_id
      to_columns:
        - customer_id
  metrics:
    - name: total_revenue
      expression:
        dialects:
          - dialect: SNOWFLAKE
            expression: "SUM(total_amount)"
  $$
);

Use a subquery as a dataset source¶

CALL SYSTEM$CREATE_SEMANTIC_VIEW_FROM_OSI_YAML(
  'my_db.my_schema',
  $$
  version: "0.1.1"
  name: active_orders_model
  datasets:
    - name: active_orders
      source: "SELECT * FROM my_db.public.orders WHERE status = 'active'"
      fields:
        - name: order_id
          expression:
            dialects:
              - dialect: SNOWFLAKE
                expression: order_id
          dimension:
            is_time: false
  $$
);