comphead commented on code in PR #22605: URL: https://github.com/apache/datafusion/pull/22605#discussion_r3326281585
########## datafusion/spark/src/function/math/pow.rs: ########## @@ -0,0 +1,152 @@ +// 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. + +//! Spark-compatible `pow` / `power` function. +//! +//! Unlike the default DataFusion (PostgreSQL) implementation, Spark returns +//! `Infinity` for `pow(0, <negative>)` rather than raising an error. + +use std::sync::Arc; + +use arrow::array::{Array, ArrayRef, Float64Array}; +use arrow::datatypes::DataType; + +use datafusion_common::utils::take_function_args; +use datafusion_common::{Result, ScalarValue}; +use datafusion_expr::{ + ColumnarValue, Documentation, ScalarFunctionArgs, ScalarUDFImpl, Signature, +}; +use datafusion_functions::math::power::PowerFunc; + +/// Spark-compatible implementation of `pow` / `power`. +/// +/// Behavioural difference from the DataFusion default: +/// - `pow(0, <negative>)` → `Infinity` (IEEE 754 / Spark semantics) +/// The default raises `"zero raised to a negative power is undefined"` to +/// match PostgreSQL. +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct SparkPow { + inner: PowerFunc, + aliases: Vec<String>, +} + +impl Default for SparkPow { + fn default() -> Self { + Self::new() + } +} + +impl SparkPow { + pub fn new() -> Self { + Self { + inner: PowerFunc::new(), + // SparkPow is named "pow"; expose "power" as an alias so that + // both names resolve to Spark semantics when this crate is active. + aliases: vec!["power".to_string()], + } + } +} + +impl ScalarUDFImpl for SparkPow { + fn name(&self) -> &str { + "pow" + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn signature(&self) -> &Signature { + self.inner.signature() + } + + fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> { + self.inner.return_type(arg_types) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + // Only Float64 × Float64 needs the Spark override. + // Decimal / integer / mixed-type paths are delegated to the standard + // PowerFunc which already handles them correctly (decimal can't + // represent Infinity anyway). + match args.args.as_slice() { + [base, exponent] + if matches!(base.data_type(), DataType::Float64) + && matches!(exponent.data_type(), DataType::Float64) => {} + _ => return self.inner.invoke_with_args(args), + } + + let num_rows = args.number_rows; + + // ── Scalar × Scalar fast path ──────────────────────────────────────── + // Pattern-match on the slice to avoid any ownership issues. + if let [ + ColumnarValue::Scalar(ScalarValue::Float64(b)), + ColumnarValue::Scalar(ScalarValue::Float64(e)), + ] = args.args.as_slice() + { + // b and e are &Option<f64>; Option<f64> is Copy. + let result = (*b).zip(*e).map(|(b, e)| { + if b == 0.0 && e < 0.0 { + f64::INFINITY + } else { + b.powf(e) + } + }); + return Ok(ColumnarValue::Scalar(ScalarValue::Float64(result))); + } + + // ── Array path ─────────────────────────────────────────────────────── + let [base, exponent] = take_function_args(self.name(), &args.args)?; + + let base_arr: ArrayRef = base.to_array(num_rows)?; + let exp_arr: ArrayRef = exponent.to_array(num_rows)?; + + let base_f64 = base_arr + .as_any() + .downcast_ref::<Float64Array>() + .expect("base must be Float64Array"); + let exp_f64 = exp_arr + .as_any() + .downcast_ref::<Float64Array>() + .expect("exponent must be Float64Array"); + + // Spark: 0^negative = +Infinity (covers both 0.0 and -0.0) + // IEEE 754: 0.0^-1.0 = +Infinity, -0.0^-1.0 = -Infinity + // Thus we need an explicit guard for b == 0.0 to ensure +Infinity. + let result: Float64Array = base_f64 + .iter() + .zip(exp_f64.iter()) + .map(|(b, e)| match (b, e) { Review Comment: same -- 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: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
