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use crate::PhysicalExpr;
use arrow::datatypes::{DataType, Schema};
use arrow::record_batch::RecordBatch;
use datafusion_common::Result;
use datafusion_common::{DataFusionError, ScalarValue};
use datafusion_expr::{ColumnarValue, Operator};
use std::any::Any;
use std::fmt::{Display, Formatter};
use std::sync::Arc;
#[derive(Debug)]
pub struct DateIntervalExpr {
lhs: Arc<dyn PhysicalExpr>,
op: Operator,
rhs: Arc<dyn PhysicalExpr>,
}
impl DateIntervalExpr {
pub fn try_new(
lhs: Arc<dyn PhysicalExpr>,
op: Operator,
rhs: Arc<dyn PhysicalExpr>,
input_schema: &Schema,
) -> Result<Self> {
match lhs.data_type(input_schema)? {
DataType::Date32 | DataType::Date64 => match rhs.data_type(input_schema)? {
DataType::Interval(_) => match &op {
Operator::Plus | Operator::Minus => Ok(Self { lhs, op, rhs }),
_ => Err(DataFusionError::Execution(format!(
"Invalid operator '{}' for DateIntervalExpr",
op
))),
},
other => Err(DataFusionError::Execution(format!(
"Invalid rhs type '{}' for DateIntervalExpr",
other
))),
},
other => Err(DataFusionError::Execution(format!(
"Invalid lhs type '{}' for DateIntervalExpr",
other
))),
}
}
}
impl Display for DateIntervalExpr {
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
write!(f, "{} {} {}", self.lhs, self.op, self.rhs)
}
}
impl PhysicalExpr for DateIntervalExpr {
fn as_any(&self) -> &dyn Any {
self
}
fn data_type(&self, input_schema: &Schema) -> datafusion_common::Result<DataType> {
self.lhs.data_type(input_schema)
}
fn nullable(&self, input_schema: &Schema) -> datafusion_common::Result<bool> {
self.lhs.nullable(input_schema)
}
fn evaluate(&self, batch: &RecordBatch) -> datafusion_common::Result<ColumnarValue> {
let dates = self.lhs.evaluate(batch)?;
let intervals = self.rhs.evaluate(batch)?;
let interval = match intervals {
ColumnarValue::Scalar(interval) => match interval {
ScalarValue::IntervalDayTime(Some(interval)) => interval as i32,
ScalarValue::IntervalYearMonth(Some(_)) => {
return Err(DataFusionError::Execution(
"DateIntervalExpr does not support IntervalYearMonth".to_string(),
))
}
ScalarValue::IntervalMonthDayNano(Some(_)) => {
return Err(DataFusionError::Execution(
"DateIntervalExpr does not support IntervalMonthDayNano"
.to_string(),
))
}
other => {
return Err(DataFusionError::Execution(format!(
"DateIntervalExpr does not support non-interval type {:?}",
other
)))
}
},
_ => {
return Err(DataFusionError::Execution(
"Columnar execution is not yet supported for DateIntervalExpr"
.to_string(),
))
}
};
match dates {
ColumnarValue::Scalar(scalar) => match scalar {
ScalarValue::Date32(Some(date)) => match &self.op {
Operator::Plus => Ok(ColumnarValue::Scalar(ScalarValue::Date32(
Some(date + interval),
))),
Operator::Minus => Ok(ColumnarValue::Scalar(ScalarValue::Date32(
Some(date - interval),
))),
_ => {
Err(DataFusionError::Execution(
"Invalid operator for DateIntervalExpr".to_string(),
))
}
},
ScalarValue::Date64(Some(date)) => match &self.op {
Operator::Plus => Ok(ColumnarValue::Scalar(ScalarValue::Date64(
Some(date + interval as i64),
))),
Operator::Minus => Ok(ColumnarValue::Scalar(ScalarValue::Date64(
Some(date - interval as i64),
))),
_ => {
Err(DataFusionError::Execution(
"Invalid operator for DateIntervalExpr".to_string(),
))
}
},
_ => {
Err(DataFusionError::Execution(
"Invalid lhs type for DateIntervalExpr".to_string(),
))
}
},
_ => Err(DataFusionError::Execution(
"Columnar execution is not yet supported for DateIntervalExpr"
.to_string(),
)),
}
}
}