alamb commented on code in PR #16125: URL: https://github.com/apache/datafusion/pull/16125#discussion_r2173714597
########## datafusion/spark/src/function/math/factorial.rs: ########## @@ -0,0 +1,196 @@ +// 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 std::any::Any; +use std::sync::Arc; + +use arrow::array::{Array, Int64Array}; +use arrow::datatypes::DataType; +use arrow::datatypes::DataType::{Int32, Int64}; +use datafusion_common::cast::as_int32_array; +use datafusion_common::{exec_err, DataFusionError, Result, ScalarValue}; +use datafusion_expr::Signature; +use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Volatility}; + +/// <https://spark.apache.org/docs/latest/api/sql/index.html#factorial> +#[derive(Debug)] +pub struct SparkFactorial { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for SparkFactorial { + fn default() -> Self { + Self::new() + } +} + +impl SparkFactorial { + pub fn new() -> Self { + Self { + signature: Signature::exact(vec![Int32], Volatility::Immutable), + aliases: vec![], + } + } +} + +impl ScalarUDFImpl for SparkFactorial { + fn as_any(&self) -> &dyn Any { + self + } + + fn name(&self) -> &str { + "factorial" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { + Ok(Int64) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + spark_factorial(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } +} + +const FACTORIALS: [i64; 21] = [ + 1, + 1, + 2, + 6, + 24, + 120, + 720, + 5040, + 40320, + 362880, + 3628800, + 39916800, + 479001600, + 6227020800, + 87178291200, + 1307674368000, + 20922789888000, + 355687428096000, + 6402373705728000, + 121645100408832000, + 2432902008176640000, +]; + +pub fn spark_factorial(args: &[ColumnarValue]) -> Result<ColumnarValue, DataFusionError> { + if args.len() != 1 { + return Err(DataFusionError::Internal( + "`factorial` expects exactly one argument".to_string(), + )); + } + + match &args[0] { + ColumnarValue::Scalar(ScalarValue::Int32(value)) => { + let result = compute_factorial(*value); + Ok(ColumnarValue::Scalar(ScalarValue::Int64(result))) + } + ColumnarValue::Scalar(other) => { + exec_err!("`factorial` got an unexpected scalar type: {:?}", other) + } + ColumnarValue::Array(array) => match array.data_type() { + Int32 => { + let array = as_int32_array(array)?; + + let result: Int64Array = array.iter().map(compute_factorial).collect(); + + Ok(ColumnarValue::Array(Arc::new(result))) + } + other => { + exec_err!("`factorial` got an unexpected argument type: {:?}", other) + } + }, + } +} + +#[inline] +fn compute_factorial(num: Option<i32>) -> Option<i64> { + num.filter(|&v| (0..=20).contains(&v)) + .map(|v| FACTORIALS[v as usize]) +} + +#[cfg(test)] +mod test { Review Comment: For future readers, unless there is some case we can't test with .slt, testing the functionality using .slt is preferred to rust unit tests as they are faster to run and easier to review -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: github-unsubscr...@datafusion.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: github-unsubscr...@datafusion.apache.org For additional commands, e-mail: github-h...@datafusion.apache.org
