1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
use std::{any::Any, sync::Arc};
use crate::physical_expr::down_cast_any_ref;
use crate::PhysicalExpr;
use arrow::compute;
use arrow::{
datatypes::{DataType, Schema},
record_batch::RecordBatch,
};
use datafusion_common::Result;
use datafusion_common::ScalarValue;
use datafusion_expr::ColumnarValue;
#[derive(Debug)]
pub struct IsNotNullExpr {
arg: Arc<dyn PhysicalExpr>,
}
impl IsNotNullExpr {
pub fn new(arg: Arc<dyn PhysicalExpr>) -> Self {
Self { arg }
}
pub fn arg(&self) -> &Arc<dyn PhysicalExpr> {
&self.arg
}
}
impl std::fmt::Display for IsNotNullExpr {
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
write!(f, "{} IS NOT NULL", self.arg)
}
}
impl PhysicalExpr for IsNotNullExpr {
fn as_any(&self) -> &dyn Any {
self
}
fn data_type(&self, _input_schema: &Schema) -> Result<DataType> {
Ok(DataType::Boolean)
}
fn nullable(&self, _input_schema: &Schema) -> Result<bool> {
Ok(false)
}
fn evaluate(&self, batch: &RecordBatch) -> Result<ColumnarValue> {
let arg = self.arg.evaluate(batch)?;
match arg {
ColumnarValue::Array(array) => Ok(ColumnarValue::Array(Arc::new(
compute::is_not_null(array.as_ref())?,
))),
ColumnarValue::Scalar(scalar) => Ok(ColumnarValue::Scalar(
ScalarValue::Boolean(Some(!scalar.is_null())),
)),
}
}
fn children(&self) -> Vec<Arc<dyn PhysicalExpr>> {
vec![self.arg.clone()]
}
fn with_new_children(
self: Arc<Self>,
children: Vec<Arc<dyn PhysicalExpr>>,
) -> Result<Arc<dyn PhysicalExpr>> {
Ok(Arc::new(IsNotNullExpr::new(children[0].clone())))
}
}
impl PartialEq<dyn Any> for IsNotNullExpr {
fn eq(&self, other: &dyn Any) -> bool {
down_cast_any_ref(other)
.downcast_ref::<Self>()
.map(|x| self.arg.eq(&x.arg))
.unwrap_or(false)
}
}
pub fn is_not_null(arg: Arc<dyn PhysicalExpr>) -> Result<Arc<dyn PhysicalExpr>> {
Ok(Arc::new(IsNotNullExpr::new(arg)))
}
#[cfg(test)]
mod tests {
use super::*;
use crate::expressions::col;
use arrow::{
array::{BooleanArray, StringArray},
datatypes::*,
record_batch::RecordBatch,
};
use datafusion_common::cast::as_boolean_array;
use std::sync::Arc;
#[test]
fn is_not_null_op() -> Result<()> {
let schema = Schema::new(vec![Field::new("a", DataType::Utf8, true)]);
let a = StringArray::from(vec![Some("foo"), None]);
let expr = is_not_null(col("a", &schema)?).unwrap();
let batch = RecordBatch::try_new(Arc::new(schema), vec![Arc::new(a)])?;
let result = expr.evaluate(&batch)?.into_array(batch.num_rows());
let result =
as_boolean_array(&result).expect("failed to downcast to BooleanArray");
let expected = &BooleanArray::from(vec![true, false]);
assert_eq!(expected, result);
Ok(())
}
}