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Add library guide for table provider and catalog providers (#7287)
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* docs: add user guide

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* Update docs/source/library-user-guide/catalogs.md

Co-authored-by: Andrew Lamb <[email protected]>

* Update docs/source/library-user-guide/catalogs.md

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tshauck and alamb committed Aug 16, 2023
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2 changes: 1 addition & 1 deletion datafusion-examples/examples/catalog.rs
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Expand Up @@ -58,7 +58,7 @@ async fn main() -> Result<()> {
// context will by default have MemoryCatalogList
ctx.register_catalog_list(catlist.clone());

// intitialize our catalog and schemas
// initialize our catalog and schemas
let catalog = DirCatalog::new();
let parquet_schema = DirSchema::create(
&state,
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17 changes: 17 additions & 0 deletions docs/source/index.rst
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Expand Up @@ -63,6 +63,23 @@ The `developer’s guide`_ contains information on how to contribute.
user-guide/configs
user-guide/faq

.. _toc.library-user-guide:

.. toctree::
:maxdepth: 1
:caption: Library User Guide

library-user-guide/index
library-user-guide/using-the-sql-api
library-user-guide/working-with-exprs
library-user-guide/using-the-dataframe-api
library-user-guide/building-logical-plans
library-user-guide/catalogs
library-user-guide/adding-udfs
library-user-guide/custom-table-providers
library-user-guide/extending-operators
library-user-guide/execution-plans

.. _toc.contributor-guide:

.. toctree::
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22 changes: 22 additions & 0 deletions docs/source/library-user-guide/adding-udfs.md
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<!---
Licensed to the Apache Software Foundation (ASF) under one
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with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
-->

# Adding User Defined Functions: Scalar/Window/Aggregate

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22 changes: 22 additions & 0 deletions docs/source/library-user-guide/building-logical-plans.md
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<!---
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
distributed with this work for additional information
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"License"); you may not use this file except in compliance
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Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
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# Building Logical Plans

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179 changes: 179 additions & 0 deletions docs/source/library-user-guide/catalogs.md
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<!---
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
distributed with this work for additional information
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
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KIND, either express or implied. See the License for the
specific language governing permissions and limitations
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-->

# Catalogs, Schemas, and Tables

This section describes how to create and manage catalogs, schemas, and tables in DataFusion. For those wanting to dive into the code quickly please see the [example](../../../datafusion-examples/examples/catalog.rs).

## General Concepts

Catalogs, schemas, and tables are organized in a hierarchy. A catalog contains schemas, and a schema contains tables.

DataFusion comes with a basic in memory catalog functionality in the [`catalog` module]. You can use these in memory implementations as is, or extend DataFusion with your own catalog implementations, for example based on local files or files on remote object storage.

[`catalog` module]: https://docs.rs/datafusion/latest/datafusion/catalog/index.html

Similarly to other concepts in DataFusion, you'll implement various traits to create your own catalogs, schemas, and tables. The following sections describe the traits you'll need to implement.

The `CatalogProvider` trait has methods to set a schema to a name, get a schema by name, and list all schemas. The `SchemaProvider`, which can be registered with a `CatalogProvider`, has methods to set a table to a name, get a table by name, list all tables, deregister a table, and check for a table's existence. The `TableProvider` trait has methods to scan underlying data and use it in DataFusion. The `TableProvider` trait is covered in more detail [here](./custom-table-providers.md).

In the following example, we'll implement an in memory catalog, starting with the `SchemaProvider` trait as we need one to register with the `CatalogProvider`.

## Implementing `MemorySchemaProvider`

The `MemorySchemaProvider` is a simple implementation of the `SchemaProvider` trait. It stores state (i.e. tables) in a `DashMap`, which then underlies the `SchemaProvider` trait.

```rust
pub struct MemorySchemaProvider {
tables: DashMap<String, Arc<dyn TableProvider>>,
}
```

`tables` is the key-value pair described above. The underlying state could also be another data structure or other storage mechanism such as a file or transactional database.

Then we implement the `SchemaProvider` trait for `MemorySchemaProvider`.

```rust
#[async_trait]
impl SchemaProvider for MemorySchemaProvider {
fn as_any(&self) -> &dyn Any {
self
}

fn table_names(&self) -> Vec<String> {
self.tables
.iter()
.map(|table| table.key().clone())
.collect()
}

async fn table(&self, name: &str) -> Option<Arc<dyn TableProvider>> {
self.tables.get(name).map(|table| table.value().clone())
}

fn register_table(
&self,
name: String,
table: Arc<dyn TableProvider>,
) -> Result<Option<Arc<dyn TableProvider>>> {
if self.table_exist(name.as_str()) {
return Err(DataFusionError::Execution(format!(
"The table {name} already exists"
)));
}
Ok(self.tables.insert(name, table))
}

fn deregister_table(&self, name: &str) -> Result<Option<Arc<dyn TableProvider>>> {
Ok(self.tables.remove(name).map(|(_, table)| table))
}

fn table_exist(&self, name: &str) -> bool {
self.tables.contains_key(name)
}
}
```

Without getting into a `CatalogProvider` implementation, we can create a `MemorySchemaProvider` and register `TableProvider`s with it.

```rust
let schema_provider = Arc::new(MemorySchemaProvider::new());
let table_provider = _; // create a table provider

schema_provider.register_table("table_name".to_string(), table_provider);

let table = schema_provider.table("table_name").unwrap();
```

### Asynchronous `SchemaProvider`

It's often useful to fetch metadata about which tables are in a schema, from a remote source. For example, a schema provider could fetch metadata from a remote database. To support this, the `SchemaProvider` trait has an asynchronous `table` method.

The trait is roughly the same except for the `table` method, and the addition of the `#[async_trait]` attribute.

```rust
#[async_trait]
impl SchemaProvider for Schema {
async fn table(&self, name: &str) -> Option<Arc<dyn TableProvider>> {
// fetch metadata from remote source
}
}
```

### Implementing `MemoryCatalogProvider`

As mentioned, the `CatalogProvider` can manage the schemas in a catalog, and the `MemoryCatalogProvider` is a simple implementation of the `CatalogProvider` trait. It stores schemas in a `DashMap`.

```rust
pub struct MemoryCatalogList {
/// Collection of catalogs containing schemas and ultimately TableProviders
pub catalogs: DashMap<String, Arc<dyn CatalogProvider>>,
}
```

With that the `CatalogProvider` trait can be implemented.

```rust
impl CatalogProvider for MemoryCatalogProvider {
fn as_any(&self) -> &dyn Any {
self
}

fn schema_names(&self) -> Vec<String> {
self.schemas.iter().map(|s| s.key().clone()).collect()
}

fn schema(&self, name: &str) -> Option<Arc<dyn SchemaProvider>> {
self.schemas.get(name).map(|s| s.value().clone())
}

fn register_schema(
&self,
name: &str,
schema: Arc<dyn SchemaProvider>,
) -> Result<Option<Arc<dyn SchemaProvider>>> {
Ok(self.schemas.insert(name.into(), schema))
}

fn deregister_schema(
&self,
name: &str,
cascade: bool,
) -> Result<Option<Arc<dyn SchemaProvider>>> {
/// `cascade` is not used here, but can be used to control whether
/// to delete all tables in the schema or not.
if let Some(schema) = self.schema(name) {
let (_, removed) = self.schemas.remove(name).unwrap();
Ok(Some(removed))
} else {
Ok(None)
}
}
}
```

Again, this is fairly straightforward, as there's an underlying data structure to store the state, via key-value pairs.

## Recap

To recap, you need to:

1. Implement the `TableProvider` trait to create a table provider, or use an existing one.
2. Implement the `SchemaProvider` trait to create a schema provider, or use an existing one.
3. Implement the `CatalogProvider` trait to create a catalog provider, or use an existing one.
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