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Unity Catalog metric views: define, create, query, and manage governed business metrics in YAML. Use when building standardized KPIs, revenue metrics, order analytics, or any reusable business metrics that need consistent definitions across teams and tools.
npx skill4agent add databricks-solutions/ai-dev-kit metric-viewsCAN USESELECTCREATE TABLEUSE SCHEMACREATE OR REPLACE VIEW catalog.schema.orders_metrics
WITH METRICS
LANGUAGE YAML
AS $$
version: 1.1
comment: "Orders KPIs for sales analysis"
source: catalog.schema.orders
filter: order_date > '2020-01-01'
dimensions:
- name: Order Month
expr: DATE_TRUNC('MONTH', order_date)
comment: "Month of order"
- name: Order Status
expr: CASE
WHEN status = 'O' THEN 'Open'
WHEN status = 'P' THEN 'Processing'
WHEN status = 'F' THEN 'Fulfilled'
END
comment: "Human-readable order status"
measures:
- name: Order Count
expr: COUNT(1)
- name: Total Revenue
expr: SUM(total_price)
comment: "Sum of total price"
- name: Revenue per Customer
expr: SUM(total_price) / COUNT(DISTINCT customer_id)
comment: "Average revenue per unique customer"
$$MEASURE()SELECT *SELECT
`Order Month`,
`Order Status`,
MEASURE(`Total Revenue`) AS total_revenue,
MEASURE(`Order Count`) AS order_count
FROM catalog.schema.orders_metrics
WHERE extract(year FROM `Order Month`) = 2024
GROUP BY ALL
ORDER BY ALL| Topic | File | Description |
|---|---|---|
| YAML Syntax | yaml-reference.md | Complete YAML spec: dimensions, measures, joins, materialization |
| Patterns & Examples | patterns.md | Common patterns: star schema, snowflake, filtered measures, window measures, ratios |
manage_metric_views| Action | Description |
|---|---|
| Create a metric view with dimensions and measures |
| Update a metric view's YAML definition |
| Get the full definition and metadata |
| Query measures grouped by dimensions |
| Drop a metric view |
| Grant SELECT privileges to users/groups |
manage_metric_views(
action="create",
full_name="catalog.schema.orders_metrics",
source="catalog.schema.orders",
or_replace=True,
comment="Orders KPIs for sales analysis",
filter_expr="order_date > '2020-01-01'",
dimensions=[
{"name": "Order Month", "expr": "DATE_TRUNC('MONTH', order_date)", "comment": "Month of order"},
{"name": "Order Status", "expr": "status"},
],
measures=[
{"name": "Order Count", "expr": "COUNT(1)"},
{"name": "Total Revenue", "expr": "SUM(total_price)", "comment": "Sum of total price"},
],
)manage_metric_views(
action="query",
full_name="catalog.schema.orders_metrics",
query_measures=["Total Revenue", "Order Count"],
query_dimensions=["Order Month"],
where="extract(year FROM `Order Month`) = 2024",
order_by="ALL",
limit=100,
)manage_metric_views(
action="describe",
full_name="catalog.schema.orders_metrics",
)manage_metric_views(
action="grant",
full_name="catalog.schema.orders_metrics",
principal="data-consumers",
privileges=["SELECT"],
)version: 1.1 # Required: "1.1" for DBR 17.2+
comment: "Description" # Optional: metric view description
source: catalog.schema.table # Required: source table/view
filter: column > value # Optional: global WHERE filter
dimensions: # Required: at least one
- name: Display Name # Backtick-quoted in queries
expr: sql_expression # Column ref or SQL transformation
comment: "Description" # Optional (v1.1+)
measures: # Required: at least one
- name: Display Name # Queried via MEASURE(`name`)
expr: AGG_FUNC(column) # Must be an aggregate expression
comment: "Description" # Optional (v1.1+)
joins: # Optional: star/snowflake schema
- name: dim_table
source: catalog.schema.dim_table
on: source.fk = dim_table.pk
materialization: # Optional (experimental)
schedule: every 6 hours
mode: relaxed| Dimensions | Measures | |
|---|---|---|
| Purpose | Categorize and group data | Aggregate numeric values |
| Examples | Region, Date, Status | SUM(revenue), COUNT(orders) |
| In queries | Used in SELECT and GROUP BY | Wrapped in |
| SQL expressions | Any SQL expression | Must use aggregate functions |
| Feature | Standard Views | Metric Views |
|---|---|---|
| Aggregation locked at creation | Yes | No - flexible at query time |
| Safe re-aggregation of ratios | No | Yes |
| Star/snowflake schema joins | Manual | Declarative in YAML |
| Materialization | Separate MV needed | Built-in |
| AI/BI Genie integration | Limited | Native |
| Issue | Solution |
|---|---|
| SELECT * not supported | Must explicitly list dimensions and use MEASURE() for measures |
| "Cannot resolve column" | Dimension/measure names with spaces need backtick quoting |
| JOIN at query time fails | Joins must be in the YAML definition, not in the SELECT query |
| MEASURE() required | All measure references must be wrapped: |
| DBR version error | Requires Runtime 17.2+ for YAML v1.1, or 16.4+ for v0.1 |
| Materialization not working | Requires serverless compute enabled; currently experimental |