use crate::sql::db_connection_pool::dbconnection::{get_schema, Error as DbError};
use crate::sql::sql_provider_datafusion::{get_stream, to_execution_error};
use arrow::datatypes::SchemaRef;
use async_trait::async_trait;
use datafusion::physical_expr::PhysicalExpr;
use datafusion::sql::sqlparser::ast::{self, VisitMut};
use datafusion::sql::unparser::dialect::Dialect;
use datafusion_federation::sql::{
AstAnalyzer, RemoteTableRef, SQLExecutor, SQLFederationProvider, SQLTableSource,
};
use datafusion_federation::{FederatedTableProviderAdaptor, FederatedTableSource};
use futures::TryStreamExt;
use snafu::ResultExt;
use std::sync::Arc;
use super::mysql_window::MySQLWindowVisitor;
use super::sql_table::MySQLTable;
use datafusion::{
datasource::TableProvider,
error::{DataFusionError, Result as DataFusionResult},
execution::SendableRecordBatchStream,
physical_plan::stream::RecordBatchStreamAdapter,
sql::TableReference,
};
impl MySQLTable {
fn create_federated_table_source(
self: Arc<Self>,
) -> DataFusionResult<Arc<dyn FederatedTableSource>> {
let table_reference = self.base_table.table_reference.clone();
let schema = Arc::clone(&Arc::clone(&self).base_table.schema());
let fed_provider = Arc::new(SQLFederationProvider::new(self));
Ok(Arc::new(SQLTableSource::new_with_schema(
fed_provider,
RemoteTableRef::from(table_reference),
schema,
)))
}
pub fn create_federated_table_provider(
self: Arc<Self>,
) -> DataFusionResult<FederatedTableProviderAdaptor> {
let table_source = Self::create_federated_table_source(Arc::clone(&self))?;
Ok(FederatedTableProviderAdaptor::new_with_provider(
table_source,
self,
))
}
}
#[allow(clippy::unnecessary_wraps)]
fn mysql_ast_analyzer(ast: ast::Statement) -> Result<ast::Statement, DataFusionError> {
match ast {
ast::Statement::Query(query) => {
let mut new_query = query.clone();
let mut window_visitor = MySQLWindowVisitor::default();
let _ = new_query.visit(&mut window_visitor);
Ok(ast::Statement::Query(new_query))
}
_ => Ok(ast),
}
}
#[async_trait]
impl SQLExecutor for MySQLTable {
fn name(&self) -> &str {
self.base_table.name()
}
fn compute_context(&self) -> Option<String> {
self.base_table.compute_context()
}
fn dialect(&self) -> Arc<dyn Dialect> {
self.base_table.dialect()
}
fn ast_analyzer(&self) -> Option<AstAnalyzer> {
Some(Box::new(mysql_ast_analyzer))
}
fn execute(
&self,
query: &str,
schema: SchemaRef,
_filters: &[Arc<dyn PhysicalExpr>],
) -> DataFusionResult<SendableRecordBatchStream> {
let fut = get_stream(
self.base_table.clone_pool(),
query.to_string(),
Arc::clone(&schema),
);
let stream = futures::stream::once(fut).try_flatten();
Ok(Box::pin(RecordBatchStreamAdapter::new(schema, stream)))
}
async fn table_names(&self) -> DataFusionResult<Vec<String>> {
Err(DataFusionError::NotImplemented(
"table inference not implemented".to_string(),
))
}
async fn get_table_schema(&self, table_name: &str) -> DataFusionResult<SchemaRef> {
let conn = self
.base_table
.clone_pool()
.connect()
.await
.map_err(to_execution_error)?;
get_schema(conn, &TableReference::from(table_name))
.await
.boxed()
.map_err(|e| DbError::UnableToGetSchema { source: e })
.map_err(to_execution_error)
}
}