// Profile dimensions in the semantic layer to discover data values, ranges, and cardinality. Use when the user wants to understand what data is in a dimension, find valid filter values, or validate view definitions against actual data.
| name | profile |
| description | Profile dimensions in the semantic layer to discover data values, ranges, and cardinality. Use when the user wants to understand what data is in a dimension, find valid filter values, or validate view definitions against actual data. |
You are running type-aware data profiling through airlayer to discover what's in the database.
# Profile all dimensions in a view
airlayer inspect --profile <view_name> --config <config.yml>
# Profile a single dimension
airlayer inspect --profile <view_name>.<dimension_name> --config <config.yml>
String dimensions (cardinality ≤ 100 → full value list; >100 → top 20):
{
"member": "orders.status",
"type": "string",
"profile": {
"cardinality": 4,
"total_rows": 1000,
"null_count": 0,
"values": ["completed", "pending", "cancelled", "returned"],
"top_values": [
{"value": "completed", "count": 650},
{"value": "pending", "count": 200},
{"value": "cancelled", "count": 100},
{"value": "returned", "count": 50}
]
}
}
Number dimensions:
{
"member": "orders.amount",
"type": "number",
"profile": {
"min": 0, "max": 999.99, "mean": 45.67,
"distinct_count": 150, "null_count": 5, "total_rows": 1000
}
}
Date/datetime dimensions:
{
"member": "orders.created_at",
"type": "datetime",
"profile": {
"min": "2024-01-01T00:00:00Z", "max": "2025-06-15T23:59:59Z",
"null_count": 0, "total_rows": 1000
}
}
Boolean dimensions:
{
"member": "orders.is_active",
"type": "boolean",
"profile": {
"true_count": 800, "false_count": 195,
"null_count": 5, "total_rows": 1000
}
}
expr from the view, so it reflects any transformations (e.g., LOWER(status))--config) and an exec-* feature flagRun a semantic query against the database via airlayer. Use when the user wants to query data through the semantic layer, test view definitions, or debug query results.
Bootstrap a semantic layer from a database. Use when the user wants to create .view.yml files from their warehouse schema, or when starting a new airlayer project from scratch.
Migrate a Cube.js semantic layer to airlayer .view.yml files. Use when the user has existing Cube.js schema files (.js or .yml) they want to convert to airlayer format.
Inspect semantic layer views, dimensions, measures, and entities. Use when the user wants to explore what's available in their .view.yml files or understand the schema structure.
Compile a semantic query to SQL using airlayer. Use when the user wants to generate SQL from .view.yml schemas, test a query against their semantic layer, or translate dimensions/measures/filters into dialect-specific SQL.
Validate .view.yml semantic layer files using airlayer. Use when the user creates or modifies view files and wants to check for errors.