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
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
// 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.

//! Aggregate function module contains all built-in aggregate functions definitions

use crate::{type_coercion::aggregates::*, Signature, TypeSignature, Volatility};
use arrow::datatypes::{DataType, Field};
use datafusion_common::{DataFusionError, Result};
use std::sync::Arc;
use std::{fmt, str::FromStr};

/// Enum of all built-in aggregate functions
#[derive(Debug, Clone, PartialEq, Eq, PartialOrd, Hash)]
pub enum AggregateFunction {
    /// count
    Count,
    /// sum
    Sum,
    /// min
    Min,
    /// max
    Max,
    /// avg
    Avg,
    /// median
    Median,
    /// Approximate aggregate function
    ApproxDistinct,
    /// array_agg
    ArrayAgg,
    /// Variance (Sample)
    Variance,
    /// Variance (Population)
    VariancePop,
    /// Standard Deviation (Sample)
    Stddev,
    /// Standard Deviation (Population)
    StddevPop,
    /// Covariance (Sample)
    Covariance,
    /// Covariance (Population)
    CovariancePop,
    /// Correlation
    Correlation,
    /// Approximate continuous percentile function
    ApproxPercentileCont,
    /// Approximate continuous percentile function with weight
    ApproxPercentileContWithWeight,
    /// ApproxMedian
    ApproxMedian,
    /// Grouping
    Grouping,
    /// Bit And
    BitAnd,
    /// Bit Or
    BitOr,
    /// Bit Xor
    BitXor,
    /// Bool And
    BoolAnd,
    /// Bool Or
    BoolOr,
}

impl fmt::Display for AggregateFunction {
    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
        // uppercase of the debug.
        write!(f, "{}", format!("{self:?}").to_uppercase())
    }
}

impl FromStr for AggregateFunction {
    type Err = DataFusionError;
    fn from_str(name: &str) -> Result<AggregateFunction> {
        Ok(match name {
            // general
            "avg" => AggregateFunction::Avg,
            "bit_and" => AggregateFunction::BitAnd,
            "bit_or" => AggregateFunction::BitOr,
            "bit_xor" => AggregateFunction::BitXor,
            "bool_and" => AggregateFunction::BoolAnd,
            "bool_or" => AggregateFunction::BoolOr,
            "count" => AggregateFunction::Count,
            "max" => AggregateFunction::Max,
            "mean" => AggregateFunction::Avg,
            "median" => AggregateFunction::Median,
            "min" => AggregateFunction::Min,
            "sum" => AggregateFunction::Sum,
            "array_agg" => AggregateFunction::ArrayAgg,
            // statistical
            "corr" => AggregateFunction::Correlation,
            "covar" => AggregateFunction::Covariance,
            "covar_pop" => AggregateFunction::CovariancePop,
            "covar_samp" => AggregateFunction::Covariance,
            "stddev" => AggregateFunction::Stddev,
            "stddev_pop" => AggregateFunction::StddevPop,
            "stddev_samp" => AggregateFunction::Stddev,
            "var" => AggregateFunction::Variance,
            "var_pop" => AggregateFunction::VariancePop,
            "var_samp" => AggregateFunction::Variance,
            // approximate
            "approx_distinct" => AggregateFunction::ApproxDistinct,
            "approx_median" => AggregateFunction::ApproxMedian,
            "approx_percentile_cont" => AggregateFunction::ApproxPercentileCont,
            "approx_percentile_cont_with_weight" => {
                AggregateFunction::ApproxPercentileContWithWeight
            }
            // other
            "grouping" => AggregateFunction::Grouping,
            _ => {
                return Err(DataFusionError::Plan(format!(
                    "There is no built-in function named {name}"
                )));
            }
        })
    }
}

/// Returns the datatype of the aggregate function.
/// This is used to get the returned data type for aggregate expr.
pub fn return_type(
    fun: &AggregateFunction,
    input_expr_types: &[DataType],
) -> Result<DataType> {
    // Note that this function *must* return the same type that the respective physical expression returns
    // or the execution panics.

    let coerced_data_types = crate::type_coercion::aggregates::coerce_types(
        fun,
        input_expr_types,
        &signature(fun),
    )?;

    match fun {
        AggregateFunction::Count | AggregateFunction::ApproxDistinct => {
            Ok(DataType::Int64)
        }
        AggregateFunction::Max | AggregateFunction::Min => {
            // For min and max agg function, the returned type is same as input type.
            // The coerced_data_types is same with input_types.
            Ok(coerced_data_types[0].clone())
        }
        AggregateFunction::Sum => sum_return_type(&coerced_data_types[0]),
        AggregateFunction::BitAnd
        | AggregateFunction::BitOr
        | AggregateFunction::BitXor => Ok(coerced_data_types[0].clone()),
        AggregateFunction::BoolAnd | AggregateFunction::BoolOr => Ok(DataType::Boolean),
        AggregateFunction::Variance => variance_return_type(&coerced_data_types[0]),
        AggregateFunction::VariancePop => variance_return_type(&coerced_data_types[0]),
        AggregateFunction::Covariance => covariance_return_type(&coerced_data_types[0]),
        AggregateFunction::CovariancePop => {
            covariance_return_type(&coerced_data_types[0])
        }
        AggregateFunction::Correlation => correlation_return_type(&coerced_data_types[0]),
        AggregateFunction::Stddev => stddev_return_type(&coerced_data_types[0]),
        AggregateFunction::StddevPop => stddev_return_type(&coerced_data_types[0]),
        AggregateFunction::Avg => avg_return_type(&coerced_data_types[0]),
        AggregateFunction::ArrayAgg => Ok(DataType::List(Arc::new(Field::new(
            "item",
            coerced_data_types[0].clone(),
            true,
        )))),
        AggregateFunction::ApproxPercentileCont => Ok(coerced_data_types[0].clone()),
        AggregateFunction::ApproxPercentileContWithWeight => {
            Ok(coerced_data_types[0].clone())
        }
        AggregateFunction::ApproxMedian | AggregateFunction::Median => {
            Ok(coerced_data_types[0].clone())
        }
        AggregateFunction::Grouping => Ok(DataType::Int32),
    }
}

/// Returns the internal sum datatype of the avg aggregate function.
pub fn sum_type_of_avg(input_expr_types: &[DataType]) -> Result<DataType> {
    // Note that this function *must* return the same type that the respective physical expression returns
    // or the execution panics.
    let fun = AggregateFunction::Avg;
    let coerced_data_types = crate::type_coercion::aggregates::coerce_types(
        &fun,
        input_expr_types,
        &signature(&fun),
    )?;
    avg_sum_type(&coerced_data_types[0])
}

/// the signatures supported by the function `fun`.
pub fn signature(fun: &AggregateFunction) -> Signature {
    // note: the physical expression must accept the type returned by this function or the execution panics.
    match fun {
        AggregateFunction::Count => Signature::variadic_any(Volatility::Immutable),
        AggregateFunction::ApproxDistinct
        | AggregateFunction::Grouping
        | AggregateFunction::ArrayAgg => Signature::any(1, Volatility::Immutable),
        AggregateFunction::Min | AggregateFunction::Max => {
            let valid = STRINGS
                .iter()
                .chain(NUMERICS.iter())
                .chain(TIMESTAMPS.iter())
                .chain(DATES.iter())
                .chain(TIMES.iter())
                .cloned()
                .collect::<Vec<_>>();
            Signature::uniform(1, valid, Volatility::Immutable)
        }
        AggregateFunction::BitAnd
        | AggregateFunction::BitOr
        | AggregateFunction::BitXor => {
            Signature::uniform(1, INTEGERS.to_vec(), Volatility::Immutable)
        }
        AggregateFunction::BoolAnd | AggregateFunction::BoolOr => {
            Signature::uniform(1, vec![DataType::Boolean], Volatility::Immutable)
        }
        AggregateFunction::Avg
        | AggregateFunction::Sum
        | AggregateFunction::Variance
        | AggregateFunction::VariancePop
        | AggregateFunction::Stddev
        | AggregateFunction::StddevPop
        | AggregateFunction::Median
        | AggregateFunction::ApproxMedian => {
            Signature::uniform(1, NUMERICS.to_vec(), Volatility::Immutable)
        }
        AggregateFunction::Covariance | AggregateFunction::CovariancePop => {
            Signature::uniform(2, NUMERICS.to_vec(), Volatility::Immutable)
        }
        AggregateFunction::Correlation => {
            Signature::uniform(2, NUMERICS.to_vec(), Volatility::Immutable)
        }
        AggregateFunction::ApproxPercentileCont => {
            // Accept any numeric value paired with a float64 percentile
            let with_tdigest_size = NUMERICS.iter().map(|t| {
                TypeSignature::Exact(vec![t.clone(), DataType::Float64, t.clone()])
            });
            Signature::one_of(
                NUMERICS
                    .iter()
                    .map(|t| TypeSignature::Exact(vec![t.clone(), DataType::Float64]))
                    .chain(with_tdigest_size)
                    .collect(),
                Volatility::Immutable,
            )
        }
        AggregateFunction::ApproxPercentileContWithWeight => Signature::one_of(
            // Accept any numeric value paired with a float64 percentile
            NUMERICS
                .iter()
                .map(|t| {
                    TypeSignature::Exact(vec![t.clone(), t.clone(), DataType::Float64])
                })
                .collect(),
            Volatility::Immutable,
        ),
    }
}