datafusion_comet_spark_expr/predicate_funcs/
is_nan.rs

1// Licensed to the Apache Software Foundation (ASF) under one
2// or more contributor license agreements.  See the NOTICE file
3// distributed with this work for additional information
4// regarding copyright ownership.  The ASF licenses this file
5// to you under the Apache License, Version 2.0 (the
6// "License"); you may not use this file except in compliance
7// with the License.  You may obtain a copy of the License at
8//
9//   http://www.apache.org/licenses/LICENSE-2.0
10//
11// Unless required by applicable law or agreed to in writing,
12// software distributed under the License is distributed on an
13// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
14// KIND, either express or implied.  See the License for the
15// specific language governing permissions and limitations
16// under the License.
17
18use arrow::array::{Array, BooleanArray};
19use arrow::array::{Float32Array, Float64Array};
20use arrow::datatypes::DataType;
21use datafusion::common::{DataFusionError, ScalarValue};
22use datafusion::physical_plan::ColumnarValue;
23use std::sync::Arc;
24
25/// Spark-compatible `isnan` expression
26pub fn spark_isnan(args: &[ColumnarValue]) -> Result<ColumnarValue, DataFusionError> {
27    fn set_nulls_to_false(is_nan: BooleanArray) -> ColumnarValue {
28        match is_nan.nulls() {
29            Some(nulls) => {
30                let is_not_null = nulls.inner();
31                ColumnarValue::Array(Arc::new(BooleanArray::new(
32                    is_nan.values() & is_not_null,
33                    None,
34                )))
35            }
36            None => ColumnarValue::Array(Arc::new(is_nan)),
37        }
38    }
39    let value = &args[0];
40    match value {
41        ColumnarValue::Array(array) => match array.data_type() {
42            DataType::Float64 => {
43                let array = array.as_any().downcast_ref::<Float64Array>().unwrap();
44                let is_nan = BooleanArray::from_unary(array, |x| x.is_nan());
45                Ok(set_nulls_to_false(is_nan))
46            }
47            DataType::Float32 => {
48                let array = array.as_any().downcast_ref::<Float32Array>().unwrap();
49                let is_nan = BooleanArray::from_unary(array, |x| x.is_nan());
50                Ok(set_nulls_to_false(is_nan))
51            }
52            other => Err(DataFusionError::Internal(format!(
53                "Unsupported data type {other:?} for function isnan",
54            ))),
55        },
56        ColumnarValue::Scalar(a) => match a {
57            ScalarValue::Float64(a) => Ok(ColumnarValue::Scalar(ScalarValue::Boolean(Some(
58                a.map(|x| x.is_nan()).unwrap_or(false),
59            )))),
60            ScalarValue::Float32(a) => Ok(ColumnarValue::Scalar(ScalarValue::Boolean(Some(
61                a.map(|x| x.is_nan()).unwrap_or(false),
62            )))),
63            _ => Err(DataFusionError::Internal(format!(
64                "Unsupported data type {:?} for function isnan",
65                value.data_type(),
66            ))),
67        },
68    }
69}
datafusion_comet_spark_expr/predicate_funcs/is_nan.rs

datafusion_comet_spark_expr/predicate_funcs/
is_nan.rs
