datafusion 4.0.0

DataFusion is an in-memory query engine that uses Apache Arrow as the memory model
Documentation
// 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
// "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.

//! An empty plan that is usefull for testing and generating plans without mapping them to actual data.

use std::any::Any;
use std::sync::Arc;

use arrow::datatypes::*;

use crate::datasource::datasource::Statistics;
use crate::datasource::TableProvider;
use crate::error::Result;
use crate::logical_plan::Expr;
use crate::physical_plan::{empty::EmptyExec, ExecutionPlan};

/// A table with a schema but no data.
pub struct EmptyTable {
    schema: SchemaRef,
}

impl EmptyTable {
    /// Initialize a new `EmptyTable` from a schema.
    pub fn new(schema: SchemaRef) -> Self {
        Self { schema }
    }
}

impl TableProvider for EmptyTable {
    fn as_any(&self) -> &dyn Any {
        self
    }

    fn schema(&self) -> SchemaRef {
        self.schema.clone()
    }

    fn scan(
        &self,
        projection: &Option<Vec<usize>>,
        _batch_size: usize,
        _filters: &[Expr],
        _limit: Option<usize>,
    ) -> Result<Arc<dyn ExecutionPlan>> {
        // even though there is no data, projections apply
        let projection = match projection.clone() {
            Some(p) => p,
            None => (0..self.schema.fields().len()).collect(),
        };
        let projected_schema = Schema::new(
            projection
                .iter()
                .map(|i| self.schema.field(*i).clone())
                .collect(),
        );
        Ok(Arc::new(EmptyExec::new(false, Arc::new(projected_schema))))
    }

    fn statistics(&self) -> Statistics {
        Statistics {
            num_rows: Some(0),
            total_byte_size: Some(0),
            column_statistics: None,
        }
    }
}