Jefffrey commented on code in PR #22466: URL: https://github.com/apache/datafusion/pull/22466#discussion_r3293660317
########## datafusion/functions-nested/src/array_scale.rs: ########## @@ -0,0 +1,208 @@ +// 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. + +//! [`ScalarUDFImpl`] definitions for array_scale function. + +use crate::utils::make_scalar_function; +use arrow::array::{ + Array, ArrayRef, Float64Array, GenericListArray, NullBufferBuilder, + OffsetBufferBuilder, OffsetSizeTrait, +}; +use arrow::datatypes::{ + DataType, + DataType::{FixedSizeList, LargeList, List, Null}, + Field, +}; +use datafusion_common::cast::{as_float64_array, as_generic_list_array}; +use datafusion_common::utils::{ListCoercion, coerced_type_with_base_type_only}; +use datafusion_common::{Result, internal_err, plan_err, utils::take_function_args}; +use datafusion_expr::{ + ColumnarValue, Documentation, ScalarFunctionArgs, ScalarUDFImpl, Signature, + Volatility, +}; +use datafusion_macros::user_doc; +use std::sync::Arc; + +make_udf_expr_and_func!( + ArrayScale, + array_scale, + array scalar, + "scales each element of a numeric array by a scalar.", + array_scale_udf +); + +#[user_doc( + doc_section(label = "Array Functions"), + description = "Returns a new array with each element of the input array multiplied by a scalar value, computed as `array[i] * scalar`. Returns NULL if the input row is NULL or the scalar is NULL. If a NULL element appears in the input array at position `i`, the result element at position `i` is NULL. Returns an empty array for an empty input array.", + syntax_example = "array_scale(array, scalar)", + sql_example = r#"```sql +> select array_scale([1.0, 2.0, 3.0], 2.0); ++----------------------------------+ +| array_scale(List([1.0,2.0,3.0]),Float64(2.0)) | ++----------------------------------+ +| [2.0, 4.0, 6.0] | ++----------------------------------+ +```"#, + argument( + name = "array", + description = "Array expression. Can be a constant, column, or function, and any combination of array operators." + ), + argument( + name = "scalar", + description = "Numeric scalar to multiply each element by. Can be a constant or column expression." + ) +)] +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct ArrayScale { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for ArrayScale { + fn default() -> Self { + Self::new() + } +} + +impl ArrayScale { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec!["list_scale".to_string()], + } + } +} + +impl ScalarUDFImpl for ArrayScale { + fn name(&self) -> &str { + "array_scale" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> { + // After `coerce_types`, `arg_types[0]` is one of List(Float64) or LargeList(Float64). + Ok(arg_types[0].clone()) + } + + fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> { + let [array_type, scalar_type] = take_function_args(self.name(), arg_types)?; + let coercion = Some(&ListCoercion::FixedSizedListToList); + + if !matches!( + array_type, + Null | List(_) | LargeList(_) | FixedSizeList(..) + ) { + return plan_err!( + "{} first argument must be a list type, got {array_type}", + self.name() + ); + } + + if !scalar_type.is_numeric() && !matches!(scalar_type, Null) { + return plan_err!( + "{} second argument must be numeric, got {scalar_type}", + self.name() + ); + } + + let coerced_array = if matches!(array_type, Null) { + List(Arc::new(Field::new_list_field(DataType::Float64, true))) + } else { + coerced_type_with_base_type_only(array_type, &DataType::Float64, coercion) + }; + + Ok(vec![coerced_array, DataType::Float64]) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + make_scalar_function(array_scale_inner)(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn documentation(&self) -> Option<&Documentation> { + self.doc() + } +} + +fn array_scale_inner(args: &[ArrayRef]) -> Result<ArrayRef> { + let [array, _scalar] = take_function_args("array_scale", args)?; + match array.data_type() { + List(_) => general_array_scale::<i32>(args), + LargeList(_) => general_array_scale::<i64>(args), + arg_type => internal_err!( + "array_scale received unexpected type after coercion: {arg_type}" + ), + } +} + +fn general_array_scale<O: OffsetSizeTrait>(arrays: &[ArrayRef]) -> Result<ArrayRef> { + let list_array = as_generic_list_array::<O>(&arrays[0])?; + let scalar_array = as_float64_array(&arrays[1])?; + + let values = as_float64_array(list_array.values())?; + let offsets = list_array.value_offsets(); + + let mut value_builder = Float64Array::builder(values.len()); + let mut new_offsets = OffsetBufferBuilder::<O>::new(list_array.len()); + let mut row_nulls = NullBufferBuilder::new(list_array.len()); Review Comment: We can use the new `row_nulls` for the null check inside the loop now instead of still querying list + scalar separately e.g. ```rust row_nulls.is_some_and(|nb| nb.is_null(i)) ``` -- This is an automated message from the Apache Git Service. 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