Catalogs provide metadata, such as databases, tables, partitions, views, and functions and information needed to access data stored in a database or other external systems.
One of the most crucial aspects of data processing is managing metadata. It may be transient metadata like temporary tables, or UDFs registered against the table environment. Or permanent metadata, like that in a Hive Metastore. Catalogs provide a unified API for managing metadata and making it accessible from the Table API and SQL Queries.
Flink sessions always have a built-in
default_catalog, which has a built-in default database named
All temporary metadata, such tables defined using
TableEnvironment#registerTable is registered to this catalog.
HiveCatalog serves two purposes; as persistent storage for pure Flink metadata, and as an interface for reading and writing existing Hive metadata.
Flink’s Hive documentation provides full details on setting up the catalog and interfacing with an existing Hive installation.
Warning The Hive Metastore stores all meta-object names in lower case. This is unlike
GenericInMemoryCatalog which is case-sensitive
Catalogs are pluggable and users can develop custom catalogs by implementing the
To use custom catalogs in SQL CLI, users should develop both a catalog and its corresponding catalog factory by implementing the
The catalog factory defines a set of properties for configuring the catalog when the SQL CLI bootstraps.
The set of properties will be passed to a discovery service where the service tries to match the properties to a
CatalogFactory and initiate a corresponding catalog instance.
Users can register additional catalogs into an existing Flink session.
All catalogs defined using YAML must provide a
type property that specifies the type of catalog.
The following types are supported out of the box.
Flink will always search for tables, views, and UDF’s in the current catalog and database.
Metadata from catalogs that are not the current catalog are accessible by providing fully qualified names in the form