Jefffrey commented on code in PR #22542: URL: https://github.com/apache/datafusion/pull/22542#discussion_r3308031982
########## datafusion/functions-nested/src/array_sum.rs: ########## @@ -0,0 +1,184 @@ +// 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_sum function. + +use crate::utils::make_scalar_function; +use arrow::array::{Array, ArrayRef, Float64Array, 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!( + ArraySum, + array_sum, + array, + "returns the sum of elements in a numeric array.", + array_sum_udf +); + +#[user_doc( + doc_section(label = "Array Functions"), + description = "Returns the sum of the elements of the input array, computed as `array[0] + array[1] + ...`. NULL elements are skipped (per SQL aggregate convention). Returns NULL if the input row is NULL or every element is NULL. Returns 0.0 for an empty array.", + syntax_example = "array_sum(array)", + sql_example = r#"```sql +> select array_sum([1.0, 2.0, 3.0]); ++----------------------------+ +| array_sum(List([1.0,2.0,3.0])) | ++----------------------------+ +| 6.0 | ++----------------------------+ +```"#, + argument( + name = "array", + description = "Array expression. Can be a constant, column, or function, and any combination of array operators." + ) +)] +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct ArraySum { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for ArraySum { + fn default() -> Self { + Self::new() + } +} + +impl ArraySum { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec!["list_sum".to_string()], + } + } +} + +impl ScalarUDFImpl for ArraySum { + fn name(&self) -> &str { + "array_sum" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { + Ok(DataType::Float64) + } + + fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> { + let [arg_type] = take_function_args(self.name(), arg_types)?; + let coercion = Some(&ListCoercion::FixedSizedListToList); + + if !matches!(arg_type, Null | List(_) | LargeList(_) | FixedSizeList(..)) { + return plan_err!("{} does not support type {arg_type}", self.name()); + } + + let coerced = if matches!(arg_type, Null) { + List(Arc::new(Field::new_list_field(DataType::Float64, true))) + } else { + coerced_type_with_base_type_only(arg_type, &DataType::Float64, coercion) + }; + + Ok(vec![coerced]) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + make_scalar_function(array_sum_inner)(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn documentation(&self) -> Option<&Documentation> { + self.doc() + } +} + +fn array_sum_inner(args: &[ArrayRef]) -> Result<ArrayRef> { + let [array] = take_function_args("array_sum", args)?; + match array.data_type() { + List(_) => general_array_sum::<i32>(array), + LargeList(_) => general_array_sum::<i64>(array), + arg_type => { + internal_err!("array_sum received unexpected type after coercion: {arg_type}") + } + } +} + +fn general_array_sum<O: OffsetSizeTrait>(array: &ArrayRef) -> Result<ArrayRef> { + let list_array = as_generic_list_array::<O>(array)?; + let values = as_float64_array(list_array.values())?; + let offsets = list_array.value_offsets(); + + let mut builder = Float64Array::builder(list_array.len()); + + for row in 0..list_array.len() { + if list_array.is_null(row) { + builder.append_null(); + continue; + } + + let start = offsets[row].as_usize(); + let end = offsets[row + 1].as_usize(); + let len = end - start; + + // Empty array: sum is the additive identity. Matches SQL SUM(<empty>) = 0 + // and DuckDB's list_sum(([]) = 0 conventions. + if len == 0 { + builder.append_value(0.0); + continue; + } + + // `slice` resets the logical offset to 0, so `i` below is 0-based within the slice. + let slice = values.slice(start, len); Review Comment: Can probably get away without need a slice here, just manually iterate over the range `start..end` ########## datafusion/functions-nested/src/array_sum.rs: ########## @@ -0,0 +1,184 @@ +// 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_sum function. + +use crate::utils::make_scalar_function; +use arrow::array::{Array, ArrayRef, Float64Array, 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!( + ArraySum, + array_sum, + array, + "returns the sum of elements in a numeric array.", + array_sum_udf +); + +#[user_doc( + doc_section(label = "Array Functions"), + description = "Returns the sum of the elements of the input array, computed as `array[0] + array[1] + ...`. NULL elements are skipped (per SQL aggregate convention). Returns NULL if the input row is NULL or every element is NULL. Returns 0.0 for an empty array.", + syntax_example = "array_sum(array)", + sql_example = r#"```sql +> select array_sum([1.0, 2.0, 3.0]); ++----------------------------+ +| array_sum(List([1.0,2.0,3.0])) | ++----------------------------+ +| 6.0 | ++----------------------------+ +```"#, + argument( + name = "array", + description = "Array expression. Can be a constant, column, or function, and any combination of array operators." + ) +)] +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct ArraySum { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for ArraySum { + fn default() -> Self { + Self::new() + } +} + +impl ArraySum { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec!["list_sum".to_string()], + } + } +} + +impl ScalarUDFImpl for ArraySum { + fn name(&self) -> &str { + "array_sum" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { + Ok(DataType::Float64) + } + + fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> { + let [arg_type] = take_function_args(self.name(), arg_types)?; + let coercion = Some(&ListCoercion::FixedSizedListToList); + + if !matches!(arg_type, Null | List(_) | LargeList(_) | FixedSizeList(..)) { + return plan_err!("{} does not support type {arg_type}", self.name()); + } + + let coerced = if matches!(arg_type, Null) { + List(Arc::new(Field::new_list_field(DataType::Float64, true))) + } else { + coerced_type_with_base_type_only(arg_type, &DataType::Float64, coercion) + }; + + Ok(vec![coerced]) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + make_scalar_function(array_sum_inner)(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn documentation(&self) -> Option<&Documentation> { + self.doc() + } +} + +fn array_sum_inner(args: &[ArrayRef]) -> Result<ArrayRef> { + let [array] = take_function_args("array_sum", args)?; + match array.data_type() { + List(_) => general_array_sum::<i32>(array), + LargeList(_) => general_array_sum::<i64>(array), + arg_type => { + internal_err!("array_sum received unexpected type after coercion: {arg_type}") + } + } +} + +fn general_array_sum<O: OffsetSizeTrait>(array: &ArrayRef) -> Result<ArrayRef> { + let list_array = as_generic_list_array::<O>(array)?; + let values = as_float64_array(list_array.values())?; + let offsets = list_array.value_offsets(); + + let mut builder = Float64Array::builder(list_array.len()); + + for row in 0..list_array.len() { + if list_array.is_null(row) { + builder.append_null(); + continue; + } + + let start = offsets[row].as_usize(); + let end = offsets[row + 1].as_usize(); + let len = end - start; + + // Empty array: sum is the additive identity. Matches SQL SUM(<empty>) = 0 + // and DuckDB's list_sum(([]) = 0 conventions. + if len == 0 { + builder.append_value(0.0); + continue; + } + + // `slice` resets the logical offset to 0, so `i` below is 0-based within the slice. + let slice = values.slice(start, len); + + // Skip NULL elements per SQL aggregate convention (matches PostgreSQL + // array_sum, DuckDB list_sum, Spark aggregate). A row with every + // element NULL yields NULL — same behavior as SQL SUM over all-NULL. + let mut sum = 0.0_f64; + let mut any_valid = false; + for i in 0..len { + if !slice.is_null(i) { Review Comment: ```suggestion if slice.is_valid(i) { ``` -- 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. 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