Copilot commented on code in PR #16780: URL: https://github.com/apache/datafusion/pull/16780#discussion_r2206549032
########## datafusion/spark/src/function/datetime/next_day.rs: ########## @@ -0,0 +1,255 @@ +// 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. + +use std::any::Any; +use std::sync::Arc; + +use arrow::array::{new_null_array, ArrayRef, AsArray, Date32Array, StringArrayType}; +use arrow::datatypes::{DataType, Date32Type}; +use chrono::{Datelike, Duration, Weekday}; +use datafusion_common::types::NativeType; +use datafusion_common::{exec_err, plan_err, Result, ScalarValue}; +use datafusion_expr::{ + ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility, +}; + +/// <https://spark.apache.org/docs/latest/api/sql/index.html#next_day> +#[derive(Debug)] +pub struct SparkNextDay { + signature: Signature, +} + +impl Default for SparkNextDay { + fn default() -> Self { + Self::new() + } +} + +impl SparkNextDay { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + } + } +} + +impl ScalarUDFImpl for SparkNextDay { + fn as_any(&self) -> &dyn Any { + self + } + + fn name(&self) -> &str { + "next_day" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { + Ok(DataType::Date32) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + let ScalarFunctionArgs { args, .. } = args; + let [date, day_of_week] = args.as_slice() else { + return exec_err!( + "Spark `next_day` function requires 2 arguments, got {}", + args.len() + ); + }; + + match (date, day_of_week) { + (ColumnarValue::Scalar(date), ColumnarValue::Scalar(day_of_week)) => { + match (date, day_of_week) { + (ScalarValue::Date32(days), ScalarValue::Utf8(day_of_week) | ScalarValue::LargeUtf8(day_of_week) | ScalarValue::Utf8View(day_of_week)) => { + if let Some(days) = days { + if let Some(day_of_week) = day_of_week { + Ok(ColumnarValue::Scalar(ScalarValue::Date32( + spark_next_day(*days, day_of_week.as_str()), + ))) + } else { + // TODO: if spark.sql.ansi.enabled is false, + // returns NULL instead of an error for a malformed dayOfWeek. + Ok(ColumnarValue::Scalar(ScalarValue::Date32(None))) + } + } else { + Ok(ColumnarValue::Scalar(ScalarValue::Date32(None))) + } + } + _ => exec_err!("Spark `next_day` function: first arg must be date, second arg must be string. Got {args:?}"), + } + } + (ColumnarValue::Array(date_array), ColumnarValue::Scalar(day_of_week)) => { + match (date_array.data_type(), day_of_week) { + (DataType::Date32, ScalarValue::Utf8(day_of_week) | ScalarValue::LargeUtf8(day_of_week) | ScalarValue::Utf8View(day_of_week)) => { + if let Some(day_of_week) = day_of_week { + let result: Date32Array = date_array + .as_primitive::<Date32Type>() + .unary_opt(|days| spark_next_day(days, day_of_week.as_str())) + .with_data_type(DataType::Date32); + Ok(ColumnarValue::Array(Arc::new(result) as ArrayRef)) + } else { + // TODO: if spark.sql.ansi.enabled is false, + // returns NULL instead of an error for a malformed dayOfWeek. + Ok(ColumnarValue::Array(Arc::new(new_null_array(&DataType::Date32, date_array.len())))) + } + } + _ => exec_err!("Spark `next_day` function: first arg must be date, second arg must be string. Got {args:?}"), + } + } + ( + ColumnarValue::Array(date_array), + ColumnarValue::Array(day_of_week_array), + ) => { + let result = match (date_array.data_type(), day_of_week_array.data_type()) + { + ( + DataType::Date32, + DataType::Utf8 | DataType::LargeUtf8 | DataType::Utf8View, + ) => { + let date_array: &Date32Array = + date_array.as_primitive::<Date32Type>(); + match day_of_week_array.data_type() { + DataType::Utf8 => { + let day_of_week_array = + day_of_week_array.as_string::<i32>(); + process_next_day_arrays(date_array, day_of_week_array) + } + DataType::LargeUtf8 => { + let day_of_week_array = + day_of_week_array.as_string::<i64>(); + process_next_day_arrays(date_array, day_of_week_array) + } + DataType::Utf8View => { + let day_of_week_array = + day_of_week_array.as_string_view(); + process_next_day_arrays(date_array, day_of_week_array) + } + other => { + exec_err!("Spark `next_day` function: second arg must be string. Got {other:?}") + } + } + } + (left, right) => { + exec_err!( + "Spark `next_day` function: first arg must be date, second arg must be string. Got {left:?}, {right:?}" + ) + } + }?; + Ok(ColumnarValue::Array(result)) + } + _ => exec_err!("Unsupported args {args:?} for Spark function `next_day`"), + } + } + + fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> { + if arg_types.len() != 2 { + return exec_err!( + "Spark `next_day` function requires 2 arguments, got {}", + arg_types.len() + ); + } + + let current_native_type: NativeType = (&arg_types[0]).into(); + if matches!(current_native_type, NativeType::Date) + || matches!(current_native_type, NativeType::String) + || matches!(current_native_type, NativeType::Null) + { + if matches!(&arg_types[1], DataType::Utf8) + || matches!(&arg_types[1], DataType::LargeUtf8) + || matches!(&arg_types[1], DataType::Utf8View) + { + Ok(vec![DataType::Date32, arg_types[1].clone()]) + } else { + plan_err!( + "The second argument of the Spark `next_day` function must be a string, but got {}", + &arg_types[1] + ) + } + } else { + plan_err!( + "The first argument of the Spark `next_day` function can only be a date or string, but got {}", &arg_types[0] + ) + } + } +} + +fn process_next_day_arrays<'a, S>( + date_array: &Date32Array, + day_of_week_array: &'a S, +) -> Result<ArrayRef> +where + &'a S: StringArrayType<'a>, +{ + let result = date_array + .iter() + .zip(day_of_week_array.iter()) + .map(|(days, day_of_week)| { + if let Some(days) = days { + if let Some(day_of_week) = day_of_week { + spark_next_day(days, day_of_week) + } else { + // TODO: if spark.sql.ansi.enabled is false, + // returns NULL instead of an error for a malformed dayOfWeek. + None + } + } else { + None + } + }) + .collect::<Date32Array>(); + Ok(Arc::new(result) as ArrayRef) +} + +fn spark_next_day(days: i32, day_of_week: &str) -> Option<i32> { + let date = Date32Type::to_naive_date(days); + Review Comment: [nitpick] The `spark_next_day` function recomputes `trim().to_uppercase()` and parses the weekday for each element in an array. You could pre-normalize and parse the target `Weekday` once outside loops for better performance on large arrays. ```suggestion fn spark_next_day_with_weekday(days: i32, day_of_week: Weekday) -> Option<i32> { let date = Date32Type::to_naive_date(days); Some(Date32Type::from_naive_date( date + Duration::days( (7 - date.weekday().days_since(day_of_week)) as i64, ), )) } fn normalize_and_parse_weekday(day_of_week: &str) -> Option<Weekday> { ``` -- 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: github-unsubscr...@datafusion.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: github-unsubscr...@datafusion.apache.org For additional commands, e-mail: github-h...@datafusion.apache.org
