datafusion-physical-expr 35.0.0

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// to you under the Apache License, Version 2.0 (the
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// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
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// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// specific language governing permissions and limitations
// under the License.

//! Literal expressions for physical operations

use std::any::Any;
use std::hash::{Hash, Hasher};
use std::sync::Arc;

use crate::physical_expr::down_cast_any_ref;
use crate::sort_properties::SortProperties;
use crate::PhysicalExpr;

use arrow::{
    datatypes::{DataType, Schema},
    record_batch::RecordBatch,
};
use datafusion_common::{Result, ScalarValue};
use datafusion_expr::{ColumnarValue, Expr};

/// Represents a literal value
#[derive(Debug, PartialEq, Eq, Hash)]
pub struct Literal {
    value: ScalarValue,
}

impl Literal {
    /// Create a literal value expression
    pub fn new(value: ScalarValue) -> Self {
        Self { value }
    }

    /// Get the scalar value
    pub fn value(&self) -> &ScalarValue {
        &self.value
    }
}

impl std::fmt::Display for Literal {
    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
        write!(f, "{}", self.value)
    }
}

impl PhysicalExpr for Literal {
    /// Return a reference to Any that can be used for downcasting
    fn as_any(&self) -> &dyn Any {
        self
    }

    fn data_type(&self, _input_schema: &Schema) -> Result<DataType> {
        Ok(self.value.data_type())
    }

    fn nullable(&self, _input_schema: &Schema) -> Result<bool> {
        Ok(self.value.is_null())
    }

    fn evaluate(&self, _batch: &RecordBatch) -> Result<ColumnarValue> {
        Ok(ColumnarValue::Scalar(self.value.clone()))
    }

    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);
    }

    fn get_ordering(&self, _children: &[SortProperties]) -> SortProperties {
        SortProperties::Singleton
    }
}

impl PartialEq<dyn Any> for Literal {
    fn eq(&self, other: &dyn Any) -> bool {
        down_cast_any_ref(other)
            .downcast_ref::<Self>()
            .map(|x| self == x)
            .unwrap_or(false)
    }
}

/// Create a literal expression
pub fn lit<T: datafusion_expr::Literal>(value: T) -> Arc<dyn PhysicalExpr> {
    match value.lit() {
        Expr::Literal(v) => Arc::new(Literal::new(v)),
        _ => unreachable!(),
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use arrow::array::Int32Array;
    use arrow::datatypes::*;
    use datafusion_common::cast::as_int32_array;
    use datafusion_common::Result;

    #[test]
    fn literal_i32() -> Result<()> {
        // create an arbitrary record bacth
        let schema = Schema::new(vec![Field::new("a", DataType::Int32, true)]);
        let a = Int32Array::from(vec![Some(1), None, Some(3), Some(4), Some(5)]);
        let batch = RecordBatch::try_new(Arc::new(schema), vec![Arc::new(a)])?;

        // create and evaluate a literal expression
        let literal_expr = lit(42i32);
        assert_eq!("42", format!("{literal_expr}"));

        let literal_array = literal_expr
            .evaluate(&batch)?
            .into_array(batch.num_rows())
            .expect("Failed to convert to array");
        let literal_array = as_int32_array(&literal_array)?;

        // note that the contents of the literal array are unrelated to the batch contents except for the length of the array
        assert_eq!(literal_array.len(), 5); // 5 rows in the batch
        for i in 0..literal_array.len() {
            assert_eq!(literal_array.value(i), 42);
        }

        Ok(())
    }
}