pub trait CatalogProvider:
Debug
+ Sync
+ Send {
// Required methods
fn as_any(&self) -> &(dyn Any + 'static);
fn schema_names(&self) -> Vec<String>;
fn schema(&self, name: &str) -> Option<Arc<dyn SchemaProvider>>;
// Provided methods
fn register_schema(
&self,
name: &str,
schema: Arc<dyn SchemaProvider>,
) -> Result<Option<Arc<dyn SchemaProvider>>, DataFusionError> { ... }
fn deregister_schema(
&self,
_name: &str,
_cascade: bool,
) -> Result<Option<Arc<dyn SchemaProvider>>, DataFusionError> { ... }
}Expand description
Represents a catalog, comprising a number of named schemas.
§Catalog Overview
To plan and execute queries, DataFusion needs a “Catalog” that provides metadata such as which schemas and tables exist, their columns and data types, and how to access the data.
The Catalog API consists:
CatalogProviderList: a collection ofCatalogProvidersCatalogProvider: a collection ofSchemaProviders (sometimes called a “database” in other systems)SchemaProvider: a collection ofTableProviders (often called a “schema” in other systems)TableProvider: individual tables
§Implementing Catalogs
To implement a catalog, you implement at least one of the CatalogProviderList,
CatalogProvider and SchemaProvider traits and register them
appropriately in the SessionContext.
DataFusion comes with a simple in-memory catalog implementation,
MemoryCatalogProvider, that is used by default and has no persistence.
DataFusion does not include more complex Catalog implementations because
catalog management is a key design choice for most data systems, and thus
it is unlikely that any general-purpose catalog implementation will work
well across many use cases.
§Implementing “Remote” catalogs
See remote_catalog for an end to end example of how to implement a
remote catalog.
Sometimes catalog information is stored remotely and requires a network call to retrieve. For example, the Delta Lake table format stores table metadata in files on S3 that must be first downloaded to discover what schemas and tables exist.
The CatalogProvider can support this use case, but it takes some care.
The planning APIs in DataFusion are not async and thus network IO can not
be performed “lazily” / “on demand” during query planning. The rationale for
this design is that using remote procedure calls for all catalog accesses
required for query planning would likely result in multiple network calls
per plan, resulting in very poor planning performance.
To implement CatalogProvider and SchemaProvider for remote catalogs,
you need to provide an in memory snapshot of the required metadata. Most
systems typically either already have this information cached locally or can
batch access to the remote catalog to retrieve multiple schemas and tables
in a single network call.
Note that SchemaProvider::table is an async function in order to
simplify implementing simple SchemaProviders. For many table formats it
is easy to list all available tables but there is additional non trivial
access required to read table details (e.g. statistics).
The pattern that DataFusion itself uses to plan SQL queries is to walk over the query to find all table references, performing required remote catalog lookups in parallel, storing the results in a cached snapshot, and then plans the query using that snapshot.
§Example Catalog Implementations
Here are some examples of how to implement custom catalogs:
-
datafusion-cli:DynamicFileCatalogProvidercatalog provider that treats files and directories on a filesystem as tables. -
The
catalog.rs: a simple directory based catalog. -
delta-rs:
UnityCatalogProviderimplementation that can read from Delta Lake tables
Required Methods§
Sourcefn as_any(&self) -> &(dyn Any + 'static)
fn as_any(&self) -> &(dyn Any + 'static)
Returns the catalog provider as Any
so that it can be downcast to a specific implementation.
Sourcefn schema_names(&self) -> Vec<String>
fn schema_names(&self) -> Vec<String>
Retrieves the list of available schema names in this catalog.
Provided Methods§
Sourcefn register_schema(
&self,
name: &str,
schema: Arc<dyn SchemaProvider>,
) -> Result<Option<Arc<dyn SchemaProvider>>, DataFusionError>
fn register_schema( &self, name: &str, schema: Arc<dyn SchemaProvider>, ) -> Result<Option<Arc<dyn SchemaProvider>>, DataFusionError>
Adds a new schema to this catalog.
If a schema of the same name existed before, it is replaced in the catalog and returned.
By default returns a “Not Implemented” error
Sourcefn deregister_schema(
&self,
_name: &str,
_cascade: bool,
) -> Result<Option<Arc<dyn SchemaProvider>>, DataFusionError>
fn deregister_schema( &self, _name: &str, _cascade: bool, ) -> Result<Option<Arc<dyn SchemaProvider>>, DataFusionError>
Removes a schema from this catalog. Implementations of this method should return
errors if the schema exists but cannot be dropped. For example, in DataFusion’s
default in-memory catalog, MemoryCatalogProvider, a non-empty schema
will only be successfully dropped when cascade is true.
This is equivalent to how DROP SCHEMA works in PostgreSQL.
Implementations of this method should return None if schema with name
does not exist.
By default returns a “Not Implemented” error