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
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160

// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements.  See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership.  The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied.  See the License for the
// specific language governing permissions and limitations
// under the License.

//! [`ScalarUDFImpl`] definitions for array_except function.

use crate::utils::{check_datatypes, make_scalar_function};
use arrow::row::{RowConverter, SortField};
use arrow_array::cast::AsArray;
use arrow_array::{Array, ArrayRef, GenericListArray, OffsetSizeTrait};
use arrow_buffer::OffsetBuffer;
use arrow_schema::{DataType, FieldRef};
use datafusion_common::{exec_err, internal_err, Result};
use datafusion_expr::{ColumnarValue, ScalarUDFImpl, Signature, Volatility};
use std::any::Any;
use std::collections::HashSet;
use std::sync::Arc;

make_udf_expr_and_func!(
    ArrayExcept,
    array_except,
    first_array second_array,
    "returns an array of the elements that appear in the first array but not in the second.",
    array_except_udf
);

#[derive(Debug)]
pub(super) struct ArrayExcept {
    signature: Signature,
    aliases: Vec<String>,
}

impl ArrayExcept {
    pub fn new() -> Self {
        Self {
            signature: Signature::any(2, Volatility::Immutable),
            aliases: vec!["list_except".to_string()],
        }
    }
}

impl ScalarUDFImpl for ArrayExcept {
    fn as_any(&self) -> &dyn Any {
        self
    }
    fn name(&self) -> &str {
        "array_except"
    }

    fn signature(&self) -> &Signature {
        &self.signature
    }

    fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
        match (&arg_types[0].clone(), &arg_types[1].clone()) {
            (DataType::Null, _) | (_, DataType::Null) => Ok(arg_types[0].clone()),
            (dt, _) => Ok(dt.clone()),
        }
    }

    fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue> {
        make_scalar_function(array_except_inner)(args)
    }

    fn aliases(&self) -> &[String] {
        &self.aliases
    }
}

/// Array_except SQL function
pub fn array_except_inner(args: &[ArrayRef]) -> Result<ArrayRef> {
    if args.len() != 2 {
        return exec_err!("array_except needs two arguments");
    }

    let array1 = &args[0];
    let array2 = &args[1];

    match (array1.data_type(), array2.data_type()) {
        (DataType::Null, _) | (_, DataType::Null) => Ok(array1.to_owned()),
        (DataType::List(field), DataType::List(_)) => {
            check_datatypes("array_except", &[array1, array2])?;
            let list1 = array1.as_list::<i32>();
            let list2 = array2.as_list::<i32>();
            let result = general_except::<i32>(list1, list2, field)?;
            Ok(Arc::new(result))
        }
        (DataType::LargeList(field), DataType::LargeList(_)) => {
            check_datatypes("array_except", &[array1, array2])?;
            let list1 = array1.as_list::<i64>();
            let list2 = array2.as_list::<i64>();
            let result = general_except::<i64>(list1, list2, field)?;
            Ok(Arc::new(result))
        }
        (dt1, dt2) => {
            internal_err!("array_except got unexpected types: {dt1:?} and {dt2:?}")
        }
    }
}

fn general_except<OffsetSize: OffsetSizeTrait>(
    l: &GenericListArray<OffsetSize>,
    r: &GenericListArray<OffsetSize>,
    field: &FieldRef,
) -> Result<GenericListArray<OffsetSize>> {
    let converter = RowConverter::new(vec![SortField::new(l.value_type())])?;

    let l_values = l.values().to_owned();
    let r_values = r.values().to_owned();
    let l_values = converter.convert_columns(&[l_values])?;
    let r_values = converter.convert_columns(&[r_values])?;

    let mut offsets = Vec::<OffsetSize>::with_capacity(l.len() + 1);
    offsets.push(OffsetSize::usize_as(0));

    let mut rows = Vec::with_capacity(l_values.num_rows());
    let mut dedup = HashSet::new();

    for (l_w, r_w) in l.offsets().windows(2).zip(r.offsets().windows(2)) {
        let l_slice = l_w[0].as_usize()..l_w[1].as_usize();
        let r_slice = r_w[0].as_usize()..r_w[1].as_usize();
        for i in r_slice {
            let right_row = r_values.row(i);
            dedup.insert(right_row);
        }
        for i in l_slice {
            let left_row = l_values.row(i);
            if dedup.insert(left_row) {
                rows.push(left_row);
            }
        }

        offsets.push(OffsetSize::usize_as(rows.len()));
        dedup.clear();
    }

    if let Some(values) = converter.convert_rows(rows)?.first() {
        Ok(GenericListArray::<OffsetSize>::new(
            field.to_owned(),
            OffsetBuffer::new(offsets.into()),
            values.to_owned(),
            l.nulls().cloned(),
        ))
    } else {
        internal_err!("array_except failed to convert rows")
    }
}