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yml2ddl
Generate SQL DDL statements from Starlake YAML definitions
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Generate SQL DDL statements from Starlake YAML definitions
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
Manage GizmoSQL processes: start, stop, list, and stop-all DuckLake-backed SQL servers
Create or modify database connections in application.sl.yml
Manage Quack DuckDB query servers exposing DuckLake over a thin remote protocol — serve (foreground), start/stop/list/stop-all (background)
Automatically infer schemas and load data from the incoming directory
Data quality expectations syntax, built-in macros, and validation patterns
Apply Row Level Security (RLS) and Column Level Security (CLS) policies
| name | yml2ddl |
| description | Generate SQL DDL statements from Starlake YAML definitions |
Generates SQL DDL (Data Definition Language) statements: CREATE TABLE, ALTER TABLE, etc.: from your Starlake YAML table definitions. Supports multiple target databases through type mappings defined in types/default.sl.yml.
starlake yml2ddl [options]
--datawarehouse <value>: Target data warehouse name: must match a DDL mapping key in types/default.sl.yml (required). Examples: bigquery, snowflake, postgres, redshift, synapse, duckdb--connection <value>: JDBC connection name with read/write access (for --apply mode)--output <value>: Output directory for generated DDL files (default: ./{datawarehouse}/)--catalog <value>: Database catalog name (if applicable)--domain <value>: Generate DDL for this specific domain only (default: all domains)--schemas <value>: Comma-separated list of schemas within the domain to generate DDL for--apply: Execute the generated DDL directly against the database--parallelism <value>: Parallelism level (default: available CPU cores)--reportFormat <value>: Report output format: console, json, or htmltypes/default.sl.ymlThe DDL generation uses ddlMapping to map Starlake types to database-specific types:
# metadata/types/default.sl.yml
types:
- name: "string"
primitiveType: "string"
ddlMapping:
bigquery: "STRING"
snowflake: "VARCHAR"
postgres: "TEXT"
duckdb: "VARCHAR"
synapse: "NVARCHAR(MAX)"
- name: "long"
primitiveType: "long"
ddlMapping:
bigquery: "INT64"
snowflake: "BIGINT"
postgres: "BIGINT"
duckdb: "BIGINT"
- name: "decimal"
primitiveType: "decimal"
ddlMapping:
bigquery: "NUMERIC"
snowflake: "NUMBER(38,9)"
postgres: "NUMERIC"
starlake yml2ddl --datawarehouse bigquery
starlake yml2ddl --datawarehouse snowflake --domain starbake
starlake yml2ddl --datawarehouse postgres --connection my_pg_conn --apply
starlake yml2ddl --datawarehouse duckdb --output /tmp/ddl
starlake yml2ddl --datawarehouse snowflake --domain sales --schemas orders,customers
starlake yml2ddl --datawarehouse bigquery --parallelism 4