datafusion-spark 53.1.0

DataFusion expressions that emulate Apache Spark's behavior
Documentation 
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

// 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.

use arrow::array::{ArrayRef, AsArray, Int64Array};
use arrow::datatypes::Field;
use arrow::datatypes::{DataType, FieldRef, Int8Type, Int16Type, Int32Type, Int64Type};
use datafusion_common::utils::take_function_args;
use datafusion_common::{Result, internal_err};
use datafusion_expr::{
    ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, TypeSignature,
    Volatility,
};
use datafusion_functions::utils::make_scalar_function;
use std::any::Any;
use std::sync::Arc;

/// Spark-compatible `bitmap_bucket_number` expression
/// <https://spark.apache.org/docs/latest/api/sql/index.html#bitmap_bucket_number>
#[derive(Debug, PartialEq, Eq, Hash)]
pub struct BitmapBucketNumber {
    signature: Signature,
}

impl Default for BitmapBucketNumber {
    fn default() -> Self {
        Self::new()
    }
}

impl BitmapBucketNumber {
    pub fn new() -> Self {
        Self {
            signature: Signature::one_of(
                vec![
                    TypeSignature::Exact(vec![DataType::Int8]),
                    TypeSignature::Exact(vec![DataType::Int16]),
                    TypeSignature::Exact(vec![DataType::Int32]),
                    TypeSignature::Exact(vec![DataType::Int64]),
                ],
                Volatility::Immutable,
            ),
        }
    }
}

impl ScalarUDFImpl for BitmapBucketNumber {
    fn as_any(&self) -> &dyn Any {
        self
    }

    fn name(&self) -> &str {
        "bitmap_bucket_number"
    }

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

    fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
        internal_err!("return_field_from_args should be used instead")
    }

    fn return_field_from_args(
        &self,
        args: datafusion_expr::ReturnFieldArgs,
    ) -> Result<FieldRef> {
        Ok(Arc::new(Field::new(
            self.name(),
            DataType::Int64,
            args.arg_fields[0].is_nullable(),
        )))
    }

    fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> {
        make_scalar_function(bitmap_bucket_number_inner, vec![])(&args.args)
    }
}

pub fn bitmap_bucket_number_inner(arg: &[ArrayRef]) -> Result<ArrayRef> {
    let [array] = take_function_args("bitmap_bucket_number", arg)?;
    match &array.data_type() {
        DataType::Int8 => {
            let result: Int64Array = array
                .as_primitive::<Int8Type>()
                .iter()
                .map(|opt| opt.map(|value| bitmap_bucket_number(value.into())))
                .collect();
            Ok(Arc::new(result))
        }
        DataType::Int16 => {
            let result: Int64Array = array
                .as_primitive::<Int16Type>()
                .iter()
                .map(|opt| opt.map(|value| bitmap_bucket_number(value.into())))
                .collect();
            Ok(Arc::new(result))
        }
        DataType::Int32 => {
            let result: Int64Array = array
                .as_primitive::<Int32Type>()
                .iter()
                .map(|opt| opt.map(|value| bitmap_bucket_number(value.into())))
                .collect();
            Ok(Arc::new(result))
        }
        DataType::Int64 => {
            let result: Int64Array = array
                .as_primitive::<Int64Type>()
                .iter()
                .map(|opt| opt.map(bitmap_bucket_number))
                .collect();
            Ok(Arc::new(result))
        }
        data_type => {
            internal_err!("bitmap_bucket_number does not support {data_type}")
        }
    }
}

const NUM_BYTES: i64 = 4 * 1024;
const NUM_BITS: i64 = NUM_BYTES * 8;

fn bitmap_bucket_number(value: i64) -> i64 {
    if value > 0 {
        1 + (value - 1) / NUM_BITS
    } else {
        value / NUM_BITS
    }
}