Realtime Compute for Apache Flink supports data definition language (DDL) statements for defining tables, configuring AI models, and managing catalogs. The following table summarizes the three DDL categories covered in this documentation set.
| Category | Description | Reference |
|---|---|---|
| Tables | Define source and sink tables with connector-specific options | Supported connectors |
| AI models | Create and manage AI models used in Flink jobs | Model DDLs |
| Catalogs | Create and manage catalogs that store metadata for databases, tables, and functions | Manage catalogs |
Tables
DDL statements for tables define the schema and connector configuration for source and sink tables in your Flink jobs. Realtime Compute for Apache Flink supports multiple connectors, and each connector has its own set of options.
For the full list of supported connectors and their options, see Supported connectors.
AI models
DDL statements for AI models let you create and manage models that you can call within Flink jobs. Realtime Compute for Apache Flink supports multiple AI model DDL statements, each with its own set of parameters.
For the full list of supported model DDL statements and parameters, see Model DDLs.
Catalogs
DDL statements for catalogs let you create and manage catalogs, which store metadata for your databases, tables, and functions.
For details, see Manage catalogs.