use std::any::Any;
use std::hash::{Hash, Hasher};
use std::sync::Arc;
use crate::physical_expr::down_cast_any_ref;
use crate::PhysicalExpr;
use arrow::{
datatypes::{DataType, Schema},
record_batch::RecordBatch,
};
use datafusion_common::{internal_err, Result};
use datafusion_expr::ColumnarValue;
#[derive(Debug, Hash, PartialEq, Eq, Clone)]
pub struct UnKnownColumn {
name: String,
}
impl UnKnownColumn {
pub fn new(name: &str) -> Self {
Self {
name: name.to_owned(),
}
}
pub fn name(&self) -> &str {
&self.name
}
}
impl std::fmt::Display for UnKnownColumn {
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
write!(f, "{}", self.name)
}
}
impl PhysicalExpr for UnKnownColumn {
fn as_any(&self) -> &dyn std::any::Any {
self
}
fn data_type(&self, _input_schema: &Schema) -> Result<DataType> {
Ok(DataType::Null)
}
fn nullable(&self, _input_schema: &Schema) -> Result<bool> {
Ok(true)
}
fn evaluate(&self, _batch: &RecordBatch) -> Result<ColumnarValue> {
internal_err!("UnKnownColumn::evaluate() should not be called")
}
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 UnKnownColumn {
fn eq(&self, other: &dyn Any) -> bool {
down_cast_any_ref(other)
.downcast_ref::<Self>()
.map(|x| self == x)
.unwrap_or(false)
}
}
#[cfg(test)]
mod test {
use crate::expressions::Column;
use crate::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(())
}
}