datafusion_comet_spark_expr/string_funcs/
prediction.rs#![allow(deprecated)]
use arrow::{
compute::{
contains_dyn, contains_utf8_scalar_dyn, ends_with_dyn, ends_with_utf8_scalar_dyn, like_dyn,
like_utf8_scalar_dyn, starts_with_dyn, starts_with_utf8_scalar_dyn,
},
record_batch::RecordBatch,
};
use arrow_schema::{DataType, Schema};
use datafusion::logical_expr::ColumnarValue;
use datafusion_common::{DataFusionError, ScalarValue::Utf8};
use datafusion_physical_expr::PhysicalExpr;
use std::{
any::Any,
fmt::{Display, Formatter},
hash::Hash,
sync::Arc,
};
macro_rules! make_predicate_function {
($name: ident, $kernel: ident, $str_scalar_kernel: ident) => {
#[derive(Debug, Eq)]
pub struct $name {
left: Arc<dyn PhysicalExpr>,
right: Arc<dyn PhysicalExpr>,
}
impl $name {
pub fn new(left: Arc<dyn PhysicalExpr>, right: Arc<dyn PhysicalExpr>) -> Self {
Self { left, right }
}
}
impl Display for $name {
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
write!(f, "$name [left: {}, right: {}]", self.left, self.right)
}
}
impl Hash for $name {
fn hash<H: std::hash::Hasher>(&self, state: &mut H) {
self.left.hash(state);
self.right.hash(state);
}
}
impl PartialEq for $name {
fn eq(&self, other: &Self) -> bool {
self.left.eq(&other.left) && self.right.eq(&other.right)
}
}
impl PhysicalExpr for $name {
fn as_any(&self) -> &dyn Any {
self
}
fn data_type(&self, _: &Schema) -> datafusion_common::Result<DataType> {
Ok(DataType::Boolean)
}
fn nullable(&self, _: &Schema) -> datafusion_common::Result<bool> {
Ok(true)
}
fn evaluate(&self, batch: &RecordBatch) -> datafusion_common::Result<ColumnarValue> {
let left_arg = self.left.evaluate(batch)?;
let right_arg = self.right.evaluate(batch)?;
let array = match (left_arg, right_arg) {
(ColumnarValue::Array(array), ColumnarValue::Scalar(Utf8(Some(string)))) => {
$str_scalar_kernel(&array, string.as_str())
}
(ColumnarValue::Array(_), ColumnarValue::Scalar(other)) => {
return Err(DataFusionError::Execution(format!(
"Should be String but got: {:?}",
other
)))
}
(ColumnarValue::Array(array1), ColumnarValue::Array(array2)) => {
$kernel(&array1, &array2)
}
_ => {
return Err(DataFusionError::Execution(
"Predicate on two literals should be folded at Spark".to_string(),
))
}
}?;
Ok(ColumnarValue::Array(Arc::new(array)))
}
fn children(&self) -> Vec<&Arc<dyn PhysicalExpr>> {
vec![&self.left, &self.right]
}
fn with_new_children(
self: Arc<Self>,
children: Vec<Arc<dyn PhysicalExpr>>,
) -> datafusion_common::Result<Arc<dyn PhysicalExpr>> {
Ok(Arc::new($name::new(
children[0].clone(),
children[1].clone(),
)))
}
}
};
}
make_predicate_function!(Like, like_dyn, like_utf8_scalar_dyn);
make_predicate_function!(StartsWith, starts_with_dyn, starts_with_utf8_scalar_dyn);
make_predicate_function!(EndsWith, ends_with_dyn, ends_with_utf8_scalar_dyn);
make_predicate_function!(Contains, contains_dyn, contains_utf8_scalar_dyn);