SubhamSinghal commented on code in PR #22459: URL: https://github.com/apache/datafusion/pull/22459#discussion_r3292436537
########## datafusion/functions-nested/src/array_add.rs: ########## @@ -0,0 +1,274 @@ +// 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_add function. + +use crate::utils::make_scalar_function; +use arrow::array::{ + Array, ArrayRef, Float64Array, GenericListArray, NullBufferBuilder, + OffsetBufferBuilder, OffsetSizeTrait, +}; +use arrow::buffer::NullBuffer; +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, exec_err, not_impl_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!( + ArrayAdd, + array_add, + array1 array2, + "returns the element-wise sum of two numeric arrays.", + array_add_udf +); + +#[user_doc( + doc_section(label = "Array Functions"), + description = "Returns the element-wise sum of two numeric arrays of equal length, computed as `array1[i] + array2[i]` per position. NULL is propagated per element: if either input element at position `i` is NULL, the corresponding output element is NULL (positions are preserved). Returns NULL if either entire input array is NULL. Errors if the per-row lengths differ. Returns an empty array if both inputs are empty.", + syntax_example = "array_add(array1, array2)", + sql_example = r#"```sql +> select array_add([1.0, 2.0, 3.0], [10.0, 20.0, 30.0]); ++---------------------------------------------------------+ +| array_add(List([1.0,2.0,3.0]),List([10.0,20.0,30.0])) | ++---------------------------------------------------------+ +| [11.0, 22.0, 33.0] | ++---------------------------------------------------------+ +```"#, + argument( + name = "array1", + description = "Array expression. Can be a constant, column, or function, and any combination of array operators." + ), + argument( + name = "array2", + description = "Array expression. Can be a constant, column, or function, and any combination of array operators." + ) +)] +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct ArrayAdd { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for ArrayAdd { + fn default() -> Self { + Self::new() + } +} + +impl ArrayAdd { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec!["list_add".to_string()], + } + } +} + +impl ScalarUDFImpl for ArrayAdd { + fn name(&self) -> &str { + "array_add" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> { + // After `coerce_types`, both args share the same List/LargeList<Float64> shape. + Ok(arg_types[0].clone()) + } + + fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> { + let [_, _] = take_function_args(self.name(), arg_types)?; + let coercion = Some(&ListCoercion::FixedSizedListToList); + + for arg_type in arg_types { + if !matches!(arg_type, Null | List(_) | LargeList(_) | FixedSizeList(..)) { + return plan_err!("{} does not support type {arg_type}", self.name()); + } + // Only flat lists of numeric leaves are supported. Peel exactly + // one layer so that `List<List<_>>` is rejected as non-numeric + // rather than passing through and failing opaquely in the kernel. + let element_type = match arg_type { + List(field) | LargeList(field) | FixedSizeList(field, _) => { + field.data_type() + } + other => other, + }; + if matches!( + element_type, + DataType::Decimal128(_, _) | DataType::Decimal256(_, _) + ) { + return not_impl_err!( + "{} does not yet support decimal element types ({element_type}); \ + cast to DOUBLE explicitly to opt into lossy float arithmetic", + self.name() + ); + } + if !matches!(element_type, Null) && !element_type.is_numeric() { + return plan_err!( + "{} requires numeric array elements, got list of {element_type}", + self.name() + ); + } + } + + // If either side is `LargeList`, widen both to `LargeList` so the runtime + // dispatch sees a homogeneous pair. + let any_large_list = arg_types.iter().any(|t| matches!(t, LargeList(_))); + + let coerced = arg_types + .iter() + .map(|arg_type| { + if matches!(arg_type, Null) { + let field = Arc::new(Field::new_list_field(DataType::Float64, true)); + return if any_large_list { + LargeList(field) + } else { + List(field) + }; + } + let coerced = coerced_type_with_base_type_only( + arg_type, + &DataType::Float64, + coercion, + ); + match coerced { + List(field) if any_large_list => LargeList(field), + other => other, + } + }) + .collect(); + + Ok(coerced) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + make_scalar_function(array_add_inner)(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn documentation(&self) -> Option<&Documentation> { + self.doc() + } +} + +fn array_add_inner(args: &[ArrayRef]) -> Result<ArrayRef> { + let [array1, array2] = take_function_args("array_add", args)?; + match (array1.data_type(), array2.data_type()) { + (List(_), List(_)) => general_array_add::<i32>(args), + (LargeList(_), LargeList(_)) => general_array_add::<i64>(args), + (arg_type1, arg_type2) => exec_err!( + "array_add received unexpected types after coercion: {arg_type1} and {arg_type2}" + ), + } +} + +fn general_array_add<O: OffsetSizeTrait>(arrays: &[ArrayRef]) -> Result<ArrayRef> { + let lhs = as_generic_list_array::<O>(&arrays[0])?; + let rhs = as_generic_list_array::<O>(&arrays[1])?; + + if lhs.len() != rhs.len() { + return exec_err!( + "array_add row counts differ ({} vs {})", + lhs.len(), + rhs.len() + ); + } + + let lhs_values = as_float64_array(lhs.values())?; + let rhs_values = as_float64_array(rhs.values())?; + let lhs_offsets = lhs.value_offsets(); + let rhs_offsets = rhs.value_offsets(); + + let mut out_values: Vec<f64> = Vec::with_capacity(lhs_values.len()); + let mut out_inner_nulls = NullBufferBuilder::new(lhs_values.len()); + let mut out_offsets = OffsetBufferBuilder::<O>::new(lhs.len()); + let mut out_row_nulls = NullBufferBuilder::new(lhs.len()); Review Comment: Addressed -- This is an automated message from the Apache Git Service. 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