SubhamSinghal commented on code in PR #22703: URL: https://github.com/apache/datafusion/pull/22703#discussion_r3342075386
########## datafusion/functions-nested/src/array_product.rs: ########## @@ -0,0 +1,185 @@ +// 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_product 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!( + ArrayProduct, + array_product, + array, + "returns the product of the elements of a numeric array.", + array_product_udf +); + +#[user_doc( + doc_section(label = "Array Functions"), + description = "Returns the product of the elements in the input numeric array. \ + NULL elements inside the array are skipped (matching SQL aggregate \ + convention). Returns NULL if the whole input is NULL or if every \ + element is NULL. Returns 1.0 for an empty array (multiplicative \ + identity). The result is always returned as `Float64`.", + syntax_example = "array_product(array)", + sql_example = r#"```sql +> select array_product([1.0, 2.0, 3.0]); ++------------------------------------+ +| array_product(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 ArrayProduct { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for ArrayProduct { + fn default() -> Self { + Self::new() + } +} + +impl ArrayProduct { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec!["list_product".to_string()], + } + } +} + +impl ScalarUDFImpl for ArrayProduct { + fn name(&self) -> &str { + "array_product" + } + + 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_product_inner)(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn documentation(&self) -> Option<&Documentation> { + self.doc() + } +} + +fn array_product_inner(args: &[ArrayRef]) -> Result<ArrayRef> { + let [array] = take_function_args("array_product", args)?; + match array.data_type() { + List(_) => general_array_product::<i32>(args), + LargeList(_) => general_array_product::<i64>(args), + arg_type => internal_err!( + "array_product received unexpected type after coercion: {arg_type}" + ), + } +} + +fn general_array_product<O: OffsetSizeTrait>(arrays: &[ArrayRef]) -> Result<ArrayRef> { + let list_array = as_generic_list_array::<O>(&arrays[0])?; + 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 list -> multiplicative identity. Distinguished here from + // all-NULL elements (which yield NULL): we have no data either way, + // but `[]` is structurally a known-empty product, while `[NULL,NULL]` + // means every value was unknown. + if len == 0 { + builder.append_value(1.0); + continue; + } Review Comment: fixed. matched behaviour with duckDB. -- 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]
