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datafusion_functions/math/
trunc.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 std::ops::{Div, Mul};
19use std::sync::Arc;
20
21use crate::utils::{calculate_binary_decimal_math_cast, make_scalar_function};
22
23use arrow::array::{ArrayRef, AsArray, PrimitiveArray};
24use arrow::datatypes::DataType::{
25    Decimal32, Decimal64, Decimal128, Decimal256, Float32, Float64,
26};
27use arrow::datatypes::{
28    ArrowPrimitiveType, DataType, Decimal32Type, Decimal64Type, Decimal128Type,
29    Decimal256Type, DecimalType, Float32Type, Float64Type, Int64Type,
30};
31use datafusion_common::ScalarValue::Int64;
32use datafusion_common::types::{
33    NativeType, logical_float32, logical_float64, logical_int64,
34};
35use datafusion_common::{Result, ScalarValue, exec_err, plan_err};
36use datafusion_expr::sort_properties::{ExprProperties, SortProperties};
37use datafusion_expr::{
38    ColumnarValue, Documentation, ScalarFunctionArgs, ScalarUDFImpl, Signature,
39    Volatility,
40};
41use datafusion_expr_common::signature::{Coercion, TypeSignature, TypeSignatureClass};
42use datafusion_macros::user_doc;
43use num_traits::{Float, NumCast, One, Zero, pow};
44
45#[user_doc(
46    doc_section(label = "Math Functions"),
47    description = "Truncates a number to a whole number or truncated to the specified decimal places.",
48    syntax_example = "trunc(numeric_expression[, decimal_places])",
49    standard_argument(name = "numeric_expression", prefix = "Numeric"),
50    argument(
51        name = "decimal_places",
52        description = r#"Optional. The number of decimal places to
53  truncate to. Defaults to 0 (truncate to a whole number). If
54  `decimal_places` is a positive integer, truncates digits to the
55  right of the decimal point. If `decimal_places` is a negative
56  integer, replaces digits to the left of the decimal point with `0`."#
57    ),
58    sql_example = r#"
59  ```sql
60  > SELECT trunc(42.738);
61  +----------------+
62  | trunc(42.738)  |
63  +----------------+
64  | 42             |
65  +----------------+
66  ```"#
67)]
68#[derive(Debug, PartialEq, Eq, Hash)]
69pub struct TruncFunc {
70    signature: Signature,
71}
72
73impl Default for TruncFunc {
74    fn default() -> Self {
75        TruncFunc::new()
76    }
77}
78
79impl TruncFunc {
80    pub fn new() -> Self {
81        let decimal = Coercion::new_exact(TypeSignatureClass::Decimal);
82        let decimal_places = Coercion::new_implicit(
83            TypeSignatureClass::Native(logical_int64()),
84            vec![TypeSignatureClass::Integer],
85            NativeType::Int64,
86        );
87        let float32 = Coercion::new_exact(TypeSignatureClass::Native(logical_float32()));
88        let float64 = Coercion::new_implicit(
89            TypeSignatureClass::Native(logical_float64()),
90            vec![TypeSignatureClass::Numeric],
91            NativeType::Float64,
92        );
93        Self {
94            // math expressions expect 1 argument of type f64 or f32
95            // priority is given to f64 because e.g. `sqrt(1i32)` is in IR (real numbers) and thus we
96            // return the best approximation for it (in f64).
97            // We accept f32 because in this case it is clear that the best approximation
98            // Decimal arguments are accepted to handle large values properly
99            signature: Signature::one_of(
100                vec![
101                    TypeSignature::Coercible(vec![
102                        decimal.clone(),
103                        decimal_places.clone(),
104                    ]),
105                    TypeSignature::Coercible(vec![decimal]),
106                    TypeSignature::Coercible(vec![
107                        float32.clone(),
108                        decimal_places.clone(),
109                    ]),
110                    TypeSignature::Coercible(vec![float32]),
111                    TypeSignature::Coercible(vec![float64.clone(), decimal_places]),
112                    TypeSignature::Coercible(vec![float64]),
113                ],
114                Volatility::Immutable,
115            ),
116        }
117    }
118}
119
120impl ScalarUDFImpl for TruncFunc {
121    fn name(&self) -> &str {
122        "trunc"
123    }
124
125    fn is_strict(&self) -> bool {
126        true
127    }
128
129    fn signature(&self) -> &Signature {
130        &self.signature
131    }
132
133    fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
134        match &arg_types[0] {
135            Float32 => Ok(Float32),
136            Float64 => Ok(Float64),
137            dt if dt.is_decimal() => Ok(dt.clone()),
138            DataType::Null => Ok(Float64),
139            _ => plan_err!(
140                "Unsupported data type {:?} for function {}",
141                arg_types[0],
142                self.name()
143            ),
144        }
145    }
146
147    fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> {
148        // Extract precision from second argument (default 0)
149        let precision = match args.args.get(1) {
150            Some(ColumnarValue::Scalar(Int64(Some(p)))) => Some(*p),
151            Some(ColumnarValue::Scalar(Int64(None))) => None, // null precision
152            Some(ColumnarValue::Array(_)) => {
153                // Precision is an array - use array path
154                return make_scalar_function(trunc, vec![])(&args.args);
155            }
156            None => Some(0), // default precision
157            Some(cv) => {
158                return exec_err!(
159                    "trunc function requires precision to be Int64, got {:?}",
160                    cv.data_type()
161                );
162            }
163        };
164
165        // Whether an explicit precision argument was supplied. The array fast
166        // paths below must only apply to the two-argument form: single-argument
167        // `trunc(x)` uses a different zero handling (mapping `-0.0` to `0.0`)
168        // that must be preserved.
169        let has_precision_arg = args.args.len() == 2;
170
171        // Scalar fast path using tuple matching for (value, precision)
172        match (&args.args[0], precision) {
173            // Null cases
174            (ColumnarValue::Scalar(sv), _) if sv.is_null() => {
175                ColumnarValue::Scalar(ScalarValue::Null).cast_to(args.return_type(), None)
176            }
177            (_, None) => {
178                ColumnarValue::Scalar(ScalarValue::Null).cast_to(args.return_type(), None)
179            }
180            // Scalar cases
181            (ColumnarValue::Scalar(ScalarValue::Float64(Some(v))), Some(p)) => Ok(
182                ColumnarValue::Scalar(ScalarValue::Float64(Some(if p == 0 {
183                    v.trunc()
184                } else {
185                    compute_truncate64(*v, p)
186                }))),
187            ),
188            (ColumnarValue::Scalar(ScalarValue::Float32(Some(v))), Some(p)) => Ok(
189                ColumnarValue::Scalar(ScalarValue::Float32(Some(if p == 0 {
190                    v.trunc()
191                } else {
192                    compute_truncate32(*v, p)
193                }))),
194            ),
195            (
196                ColumnarValue::Scalar(ScalarValue::Decimal32(
197                    Some(v),
198                    lprecision,
199                    lscale,
200                )),
201                Some(p),
202            ) => Ok(ColumnarValue::Scalar(ScalarValue::Decimal32(
203                Some(compute_truncate_decimal::<Decimal32Type>(*v, *lscale, p)),
204                *lprecision,
205                *lscale,
206            ))),
207            (
208                ColumnarValue::Scalar(ScalarValue::Decimal64(
209                    Some(v),
210                    lprecision,
211                    lscale,
212                )),
213                Some(p),
214            ) => Ok(ColumnarValue::Scalar(ScalarValue::Decimal64(
215                Some(compute_truncate_decimal::<Decimal64Type>(*v, *lscale, p)),
216                *lprecision,
217                *lscale,
218            ))),
219            (
220                ColumnarValue::Scalar(ScalarValue::Decimal128(
221                    Some(v),
222                    lprecision,
223                    lscale,
224                )),
225                Some(p),
226            ) => Ok(ColumnarValue::Scalar(ScalarValue::Decimal128(
227                Some(compute_truncate_decimal::<Decimal128Type>(*v, *lscale, p)),
228                *lprecision,
229                *lscale,
230            ))),
231            (
232                ColumnarValue::Scalar(ScalarValue::Decimal256(
233                    Some(v),
234                    lprecision,
235                    lscale,
236                )),
237                Some(p),
238            ) => Ok(ColumnarValue::Scalar(ScalarValue::Decimal256(
239                Some(compute_truncate_decimal::<Decimal256Type>(*v, *lscale, p)),
240                *lprecision,
241                *lscale,
242            ))),
243
244            // Array value with a constant (scalar) precision: hoist the power
245            // of ten out of the per-element loop instead of broadcasting the
246            // scalar into a full precision array and recomputing `10^p` for
247            // every element (see `truncate_float_array`).
248            (ColumnarValue::Array(arr), Some(p))
249                if has_precision_arg && arr.data_type() == &Float64 =>
250            {
251                Ok(ColumnarValue::Array(truncate_float_array::<Float64Type>(
252                    arr, p,
253                )))
254            }
255            (ColumnarValue::Array(arr), Some(p))
256                if has_precision_arg && arr.data_type() == &Float32 =>
257            {
258                Ok(ColumnarValue::Array(truncate_float_array::<Float32Type>(
259                    arr, p,
260                )))
261            }
262
263            // Array path for everything else
264            _ => make_scalar_function(trunc, vec![])(&args.args),
265        }
266    }
267
268    fn output_ordering(&self, input: &[ExprProperties]) -> Result<SortProperties> {
269        // trunc preserves the order of the first argument
270        let value = &input[0];
271        let precision = input.get(1);
272
273        if precision
274            .map(|r| r.sort_properties.eq(&SortProperties::Singleton))
275            .unwrap_or(true)
276        {
277            Ok(value.sort_properties)
278        } else {
279            Ok(SortProperties::Unordered)
280        }
281    }
282
283    fn documentation(&self) -> Option<&Documentation> {
284        self.doc()
285    }
286}
287
288/// Truncate(numeric, decimalPrecision) and trunc(numeric) SQL function
289fn trunc(args: &[ArrayRef]) -> Result<ArrayRef> {
290    if args.len() != 1 && args.len() != 2 {
291        return exec_err!(
292            "truncate function requires one or two arguments, got {}",
293            args.len()
294        );
295    }
296
297    // If only one arg then invoke toolchain trunc(num) and precision = 0 by default
298    // or then invoke the compute_truncate method to process precision
299    let num = &args[0];
300    let precision = if args.len() == 1 {
301        ColumnarValue::Scalar(Int64(Some(0)))
302    } else {
303        ColumnarValue::Array(Arc::clone(&args[1]))
304    };
305
306    match num.data_type() {
307        Float64 => match precision {
308            ColumnarValue::Scalar(Int64(Some(0))) => {
309                Ok(Arc::new(
310                    args[0]
311                        .as_primitive::<Float64Type>()
312                        .unary::<_, Float64Type>(|x: f64| {
313                            if x == 0_f64 { 0_f64 } else { x.trunc() }
314                        }),
315                ) as ArrayRef)
316            }
317            ColumnarValue::Array(precision) => {
318                let num_array = num.as_primitive::<Float64Type>();
319                let precision_array = precision.as_primitive::<Int64Type>();
320                let result: PrimitiveArray<Float64Type> =
321                    arrow::compute::binary(num_array, precision_array, |x, y| {
322                        compute_truncate64(x, y)
323                    })?;
324
325                Ok(Arc::new(result) as ArrayRef)
326            }
327            _ => exec_err!("trunc function requires a scalar or array for precision"),
328        },
329        Float32 => match precision {
330            ColumnarValue::Scalar(Int64(Some(0))) => {
331                Ok(Arc::new(
332                    args[0]
333                        .as_primitive::<Float32Type>()
334                        .unary::<_, Float32Type>(|x: f32| {
335                            if x == 0_f32 { 0_f32 } else { x.trunc() }
336                        }),
337                ) as ArrayRef)
338            }
339            ColumnarValue::Array(precision) => {
340                let num_array = num.as_primitive::<Float32Type>();
341                let precision_array = precision.as_primitive::<Int64Type>();
342                let result: PrimitiveArray<Float32Type> =
343                    arrow::compute::binary(num_array, precision_array, |x, y| {
344                        compute_truncate32(x, y)
345                    })?;
346
347                Ok(Arc::new(result) as ArrayRef)
348            }
349            _ => exec_err!("trunc function requires a scalar or array for precision"),
350        },
351        Decimal32(lprecision, lscale) => Ok(calculate_binary_decimal_math_cast::<
352            Decimal32Type,
353            Int64Type,
354            Decimal32Type,
355            _,
356        >(
357            num.as_ref(),
358            &precision,
359            |v, y| Ok(compute_truncate_decimal::<Decimal32Type>(v, *lscale, y)),
360            *lprecision,
361            *lscale,
362            &DataType::Int64,
363        )? as ArrayRef),
364        Decimal64(lprecision, lscale) => Ok(calculate_binary_decimal_math_cast::<
365            Decimal64Type,
366            Int64Type,
367            Decimal64Type,
368            _,
369        >(
370            num.as_ref(),
371            &precision,
372            |v, y| Ok(compute_truncate_decimal::<Decimal64Type>(v, *lscale, y)),
373            *lprecision,
374            *lscale,
375            &DataType::Int64,
376        )? as ArrayRef),
377        Decimal128(lprecision, lscale) => Ok(calculate_binary_decimal_math_cast::<
378            Decimal128Type,
379            Int64Type,
380            Decimal128Type,
381            _,
382        >(
383            num.as_ref(),
384            &precision,
385            |v, y| Ok(compute_truncate_decimal::<Decimal128Type>(v, *lscale, y)),
386            *lprecision,
387            *lscale,
388            &DataType::Int64,
389        )? as ArrayRef),
390        Decimal256(lprecision, lscale) => Ok(calculate_binary_decimal_math_cast::<
391            Decimal256Type,
392            Int64Type,
393            Decimal256Type,
394            _,
395        >(
396            num.as_ref(),
397            &precision,
398            |v, y| Ok(compute_truncate_decimal::<Decimal256Type>(v, *lscale, y)),
399            *lprecision,
400            *lscale,
401            &DataType::Int64,
402        )? as ArrayRef),
403        other => exec_err!("Unsupported data type {other:?} for function trunc"),
404    }
405}
406
407/// Truncates `x` using a pre-computed `factor` of `10^precision`. Taking the
408/// factor as an argument lets callers hoist `10^precision` out of a per-element
409/// loop when the precision is constant.
410fn truncate_with_factor<F: Float>(x: F, factor: F) -> F {
411    (x * factor).trunc() / factor
412}
413
414/// Truncates every element of a float array to `precision` decimal places,
415/// computing the `10^precision` factor once and reusing it for every element.
416fn truncate_float_array<T>(arr: &ArrayRef, precision: i64) -> ArrayRef
417where
418    T: ArrowPrimitiveType,
419    T::Native: Float,
420{
421    let factor = <T::Native as NumCast>::from(10.0_f64)
422        .unwrap()
423        .powi(precision as i32);
424    Arc::new(
425        arr.as_primitive::<T>()
426            .unary::<_, T>(|x| truncate_with_factor(x, factor)),
427    )
428}
429
430fn compute_truncate32(x: f32, y: i64) -> f32 {
431    truncate_with_factor(x, 10.0_f32.powi(y as i32))
432}
433
434fn compute_truncate64(x: f64, y: i64) -> f64 {
435    truncate_with_factor(x, 10.0_f64.powi(y as i32))
436}
437
438/// Truncates a decimal value to `truncate_precision` fractional digits.
439/// If `truncate_precision` is positive, clear that amount of trailing low-order digits
440/// If `truncate_precision` is negative, it also clears digits before a decimal point
441///
442/// Example:
443///   Truncating number 12.3456 (123456 as i128 with scale=4) to 1 digit produces 12.3.
444///   It makes exp = 4-1 = 3; factor = 10^3 = 1000; result = (123456 / 1000) * 1000 = 123000
445///   It is a decimal 12.3 with scale=4
446///
447///   Truncating number 12.3456 to -1 digit produces 10.0.
448///   It makes exp = 4-(-1) = 5; factor = 10^5 = 100000; result = (123456 / 100000) * 100000 = 100000
449///   It is a decimal 10.0 with scale=4
450fn compute_truncate_decimal<T>(
451    x: T::Native,
452    scale: i8,
453    truncate_precision: i64,
454) -> T::Native
455where
456    T: DecimalType,
457    T::Native: Copy + From<i32> + One + Zero + Div<Output = T::Native> + Mul,
458{
459    // How many trailing digits of decimal to clear
460    let exp = (scale as i64).saturating_sub(truncate_precision);
461    if exp <= 0 {
462        // Keep more digits than actually stored, so nothing to truncate
463        x
464    } else if exp >= T::MAX_PRECISION as i64 {
465        // Drop more digits that can be stored, return 0 without overflowing `pow`
466        T::Native::zero()
467    } else {
468        let base = T::Native::from(10_i32);
469        let exp = exp as usize;
470        let factor = pow::<T::Native>(base, exp);
471        // Result is (x / factor) * factor, so (x/factor) drops extra digits
472        (x / factor) * factor
473    }
474}
475
476#[cfg(test)]
477mod test {
478    use std::sync::Arc;
479
480    use crate::math::trunc::{compute_truncate_decimal, trunc};
481
482    use arrow::array::{ArrayRef, Float32Array, Float64Array, Int64Array};
483    use arrow::datatypes::Decimal128Type;
484    use datafusion_common::cast::{as_float32_array, as_float64_array};
485
486    #[test]
487    fn test_truncate_32() {
488        let args: Vec<ArrayRef> = vec![
489            Arc::new(Float32Array::from(vec![
490                15.0,
491                1_234.267_8,
492                1_233.123_4,
493                3.312_979_2,
494                -21.123_4,
495            ])),
496            Arc::new(Int64Array::from(vec![0, 3, 2, 5, 6])),
497        ];
498
499        let result = trunc(&args).expect("failed to initialize function truncate");
500        let floats =
501            as_float32_array(&result).expect("failed to initialize function truncate");
502
503        assert_eq!(floats.len(), 5);
504        assert_eq!(floats.value(0), 15.0);
505        assert_eq!(floats.value(1), 1_234.267);
506        assert_eq!(floats.value(2), 1_233.12);
507        assert_eq!(floats.value(3), 3.312_97);
508        assert_eq!(floats.value(4), -21.123_4);
509    }
510
511    #[test]
512    fn test_truncate_64() {
513        let args: Vec<ArrayRef> = vec![
514            Arc::new(Float64Array::from(vec![
515                5.0,
516                234.267_812_176,
517                123.123_456_789,
518                123.312_979_313_2,
519                -321.123_1,
520            ])),
521            Arc::new(Int64Array::from(vec![0, 3, 2, 5, 6])),
522        ];
523
524        let result = trunc(&args).expect("failed to initialize function truncate");
525        let floats =
526            as_float64_array(&result).expect("failed to initialize function truncate");
527
528        assert_eq!(floats.len(), 5);
529        assert_eq!(floats.value(0), 5.0);
530        assert_eq!(floats.value(1), 234.267);
531        assert_eq!(floats.value(2), 123.12);
532        assert_eq!(floats.value(3), 123.312_97);
533        assert_eq!(floats.value(4), -321.123_1);
534    }
535
536    #[test]
537    fn test_truncate_64_one_arg() {
538        let args: Vec<ArrayRef> = vec![Arc::new(Float64Array::from(vec![
539            5.0,
540            234.267_812,
541            123.123_45,
542            123.312_979_313_2,
543            -321.123,
544        ]))];
545
546        let result = trunc(&args).expect("failed to initialize function truncate");
547        let floats =
548            as_float64_array(&result).expect("failed to initialize function truncate");
549
550        assert_eq!(floats.len(), 5);
551        assert_eq!(floats.value(0), 5.0);
552        assert_eq!(floats.value(1), 234.0);
553        assert_eq!(floats.value(2), 123.0);
554        assert_eq!(floats.value(3), 123.0);
555        assert_eq!(floats.value(4), -321.0);
556    }
557
558    #[test]
559    fn test_compute_truncate_decimal128() {
560        // number 12.3456 (scale 4) truncated to 3 places = 12.345
561        assert_eq!(
562            compute_truncate_decimal::<Decimal128Type>(123_456, 4, 3),
563            123_450
564        );
565        // number 12.3456 (scale 4) truncated to 1 place = 12.3
566        assert_eq!(
567            compute_truncate_decimal::<Decimal128Type>(123_456, 4, 1),
568            123_000
569        );
570
571        // requesting more places = no change
572        assert_eq!(
573            compute_truncate_decimal::<Decimal128Type>(123_456, 4, 10),
574            123_456
575        );
576
577        // truncating to 0 places = whole number 12
578        assert_eq!(
579            compute_truncate_decimal::<Decimal128Type>(123_456, 4, 0),
580            120_000
581        );
582
583        // number 12.3456 (scale 2) truncated to -1 places = 10
584        assert_eq!(
585            compute_truncate_decimal::<Decimal128Type>(123_456, 4, -1),
586            100_000
587        );
588
589        // number 12.3456 (scale 2) truncated to -3 places = 0
590        assert_eq!(
591            compute_truncate_decimal::<Decimal128Type>(123_456, 4, -3),
592            0
593        );
594
595        // number 1234.56 (scale 2) truncated to -3 places = 1000
596        assert_eq!(
597            compute_truncate_decimal::<Decimal128Type>(123_456, 2, -3),
598            100_000
599        );
600
601        // out of scale
602        assert_eq!(
603            compute_truncate_decimal::<Decimal128Type>(123_456, 4, -900),
604            0
605        );
606
607        // truncation rounds towards zero: -12.3456 = -12.345
608        assert_eq!(
609            compute_truncate_decimal::<Decimal128Type>(-123_456, 4, 3),
610            -123_450
611        );
612    }
613}