datafusion_physical_expr/expressions/column.rs
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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
// "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.
//! Physical column reference: [`Column`]
use std::any::Any;
use std::hash::{Hash, Hasher};
use std::sync::Arc;
use arrow::{
datatypes::{DataType, Schema},
record_batch::RecordBatch,
};
use arrow_schema::SchemaRef;
use datafusion_common::tree_node::{Transformed, TreeNode};
use datafusion_common::{internal_err, plan_err, Result};
use datafusion_expr::ColumnarValue;
use crate::physical_expr::{down_cast_any_ref, PhysicalExpr};
/// Represents the column at a given index in a RecordBatch
///
/// This is a physical expression that represents a column at a given index in an
/// arrow [`Schema`] / [`RecordBatch`].
///
/// Unlike the [logical `Expr::Column`], this expression is always resolved by schema index,
/// even though it does have a name. This is because the physical plan is always
/// resolved to a specific schema and there is no concept of "relation"
///
/// # Example:
/// If the schema is `a`, `b`, `c` the `Column` for `b` would be represented by
/// index 1, since `b` is the second colum in the schema.
///
/// ```
/// # use datafusion_physical_expr::expressions::Column;
/// # use arrow::datatypes::{DataType, Field, Schema};
/// // Schema with columns a, b, c
/// let schema = Schema::new(vec![
/// Field::new("a", DataType::Int32, false),
/// Field::new("b", DataType::Int32, false),
/// Field::new("c", DataType::Int32, false),
/// ]);
///
/// // reference to column b is index 1
/// let column_b = Column::new_with_schema("b", &schema).unwrap();
/// assert_eq!(column_b.index(), 1);
///
/// // reference to column c is index 2
/// let column_c = Column::new_with_schema("c", &schema).unwrap();
/// assert_eq!(column_c.index(), 2);
/// ```
/// [logical `Expr::Column`]: https://docs.rs/datafusion/latest/datafusion/logical_expr/enum.Expr.html#variant.Column
#[derive(Debug, Hash, PartialEq, Eq, Clone)]
pub struct Column {
/// The name of the column (used for debugging and display purposes)
name: String,
/// The index of the column in its schema
index: usize,
}
impl Column {
/// Create a new column expression which references the
/// column with the given index in the schema.
pub fn new(name: &str, index: usize) -> Self {
Self {
name: name.to_owned(),
index,
}
}
/// Create a new column expression which references the
/// column with the given name in the schema
pub fn new_with_schema(name: &str, schema: &Schema) -> Result<Self> {
Ok(Column::new(name, schema.index_of(name)?))
}
/// Get the column's name
pub fn name(&self) -> &str {
&self.name
}
/// Get the column's schema index
pub fn index(&self) -> usize {
self.index
}
}
impl std::fmt::Display for Column {
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
write!(f, "{}@{}", self.name, self.index)
}
}
impl PhysicalExpr for Column {
/// Return a reference to Any that can be used for downcasting
fn as_any(&self) -> &dyn Any {
self
}
/// Get the data type of this expression, given the schema of the input
fn data_type(&self, input_schema: &Schema) -> Result<DataType> {
self.bounds_check(input_schema)?;
Ok(input_schema.field(self.index).data_type().clone())
}
/// Decide whether this expression is nullable, given the schema of the input
fn nullable(&self, input_schema: &Schema) -> Result<bool> {
self.bounds_check(input_schema)?;
Ok(input_schema.field(self.index).is_nullable())
}
/// Evaluate the expression
fn evaluate(&self, batch: &RecordBatch) -> Result<ColumnarValue> {
self.bounds_check(batch.schema().as_ref())?;
Ok(ColumnarValue::Array(Arc::clone(batch.column(self.index))))
}
fn children(&self) -> Vec<&Arc<dyn PhysicalExpr>> {
vec![]
}
fn with_new_children(
self: Arc<Self>,
_children: Vec<Arc<dyn PhysicalExpr>>,
) -> Result<Arc<dyn PhysicalExpr>> {
Ok(self)
}
fn dyn_hash(&self, state: &mut dyn Hasher) {
let mut s = state;
self.hash(&mut s);
}
}
impl PartialEq<dyn Any> for Column {
fn eq(&self, other: &dyn Any) -> bool {
down_cast_any_ref(other)
.downcast_ref::<Self>()
.map(|x| self == x)
.unwrap_or(false)
}
}
impl Column {
fn bounds_check(&self, input_schema: &Schema) -> Result<()> {
if self.index < input_schema.fields.len() {
Ok(())
} else {
internal_err!(
"PhysicalExpr Column references column '{}' at index {} (zero-based) but input schema only has {} columns: {:?}",
self.name,
self.index,
input_schema.fields.len(),
input_schema.fields().iter().map(|f| f.name()).collect::<Vec<_>>()
)
}
}
}
/// Create a column expression
pub fn col(name: &str, schema: &Schema) -> Result<Arc<dyn PhysicalExpr>> {
Ok(Arc::new(Column::new_with_schema(name, schema)?))
}
/// Rewrites an expression according to new schema; i.e. changes the columns it
/// refers to with the column at corresponding index in the new schema. Returns
/// an error if the given schema has fewer columns than the original schema.
/// Note that the resulting expression may not be valid if data types in the
/// new schema is incompatible with expression nodes.
pub fn with_new_schema(
expr: Arc<dyn PhysicalExpr>,
schema: &SchemaRef,
) -> Result<Arc<dyn PhysicalExpr>> {
Ok(expr
.transform_up(|expr| {
if let Some(col) = expr.as_any().downcast_ref::<Column>() {
let idx = col.index();
let Some(field) = schema.fields().get(idx) else {
return plan_err!(
"New schema has fewer columns than original schema"
);
};
let new_col = Column::new(field.name(), idx);
Ok(Transformed::yes(Arc::new(new_col) as _))
} else {
Ok(Transformed::no(expr))
}
})?
.data)
}
#[cfg(test)]
mod test {
use super::Column;
use crate::physical_expr::PhysicalExpr;
use arrow::array::StringArray;
use arrow::datatypes::{DataType, Field, Schema};
use arrow::record_batch::RecordBatch;
use datafusion_common::Result;
use std::sync::Arc;
#[test]
fn out_of_bounds_data_type() {
let schema = Schema::new(vec![Field::new("foo", DataType::Utf8, true)]);
let col = Column::new("id", 9);
let error = col.data_type(&schema).expect_err("error").strip_backtrace();
assert!("Internal error: PhysicalExpr Column references column 'id' at index 9 (zero-based) \
but input schema only has 1 columns: [\"foo\"].\nThis was likely caused by a bug in \
DataFusion's code and we would welcome that you file an bug report in our issue tracker".starts_with(&error))
}
#[test]
fn out_of_bounds_nullable() {
let schema = Schema::new(vec![Field::new("foo", DataType::Utf8, true)]);
let col = Column::new("id", 9);
let error = col.nullable(&schema).expect_err("error").strip_backtrace();
assert!("Internal error: PhysicalExpr Column references column 'id' at index 9 (zero-based) \
but input schema only has 1 columns: [\"foo\"].\nThis was likely caused by a bug in \
DataFusion's code and we would welcome that you file an bug report in our issue tracker".starts_with(&error))
}
#[test]
fn out_of_bounds_evaluate() -> Result<()> {
let schema = Schema::new(vec![Field::new("foo", DataType::Utf8, true)]);
let data: StringArray = vec!["data"].into();
let batch = RecordBatch::try_new(Arc::new(schema), vec![Arc::new(data)])?;
let col = Column::new("id", 9);
let error = col.evaluate(&batch).expect_err("error").strip_backtrace();
assert!("Internal error: PhysicalExpr Column references column 'id' at index 9 (zero-based) \
but input schema only has 1 columns: [\"foo\"].\nThis was likely caused by a bug in \
DataFusion's code and we would welcome that you file an bug report in our issue tracker".starts_with(&error));
Ok(())
}
}