Jefffrey commented on code in PR #20928: URL: https://github.com/apache/datafusion/pull/20928#discussion_r3378158154
########## datafusion/spark/src/function/string/concat_ws.rs: ########## @@ -0,0 +1,289 @@ +// 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. + +//! Spark-compatible `concat_ws`: joins strings (and array elements) with a separator. +//! +//! Null scalar args and null array elements are skipped; a null separator yields a +//! null row. Non-string args are coerced to STRING; list args (`List`, `LargeList`, +//! `ListView`, `LargeListView`, `FixedSizeList`) expand their elements. +//! +//! Differences with DataFusion core `concat_ws`: +//! - Accepts list arguments and expands their elements +//! - Always returns Utf8 (Spark's `STRING` type) +//! - Coerces non-string scalars (numbers, booleans, dates, ...) to Utf8 + +use std::sync::Arc; + +use arrow::array::{ + Array, ArrayRef, AsArray, GenericListArray, LargeStringArray, OffsetSizeTrait, + StringArray, StringBuilder, StringViewArray, +}; +use arrow::datatypes::DataType; +use datafusion_common::{Result, ScalarValue}; +use datafusion_expr::{ + ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility, +}; + +use crate::function::error_utils::{ + invalid_arg_count_exec_err, unsupported_data_type_exec_err, +}; + +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct SparkConcatWs { + signature: Signature, +} + +impl Default for SparkConcatWs { + fn default() -> Self { + Self::new() + } +} + +impl SparkConcatWs { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + } + } +} + +impl ScalarUDFImpl for SparkConcatWs { + fn name(&self) -> &str { + "concat_ws" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { + Ok(DataType::Utf8) + } + + fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> { + if arg_types.is_empty() { + return Err(invalid_arg_count_exec_err("concat_ws", (1, i32::MAX), 0)); + } + Ok(arg_types + .iter() + .enumerate() + .map(|(i, dt)| match dt { + DataType::Utf8 | DataType::LargeUtf8 | DataType::Utf8View => dt.clone(), + // Non-separator list args expand their elements at runtime; + // normalize list variants so the kernel only sees List/LargeList. + DataType::List(f) + | DataType::ListView(f) + | DataType::FixedSizeList(f, _) + if i > 0 => + { + DataType::List(Arc::clone(f)) + } + DataType::LargeList(f) | DataType::LargeListView(f) if i > 0 => { + DataType::LargeList(Arc::clone(f)) + } + // Spark casts everything else (numbers, booleans, dates, + // binary, null...) to STRING. + _ => DataType::Utf8, + }) + .collect()) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + // Only separator provided → empty string (or NULL if separator is null). + // Arg-count validation happens in coerce_types at planning time. + if args.args.len() == 1 { + return only_separator(&args.args[0]); + } + + spark_concat_ws(&args.args, args.number_rows) + } +} + +fn only_separator(sep: &ColumnarValue) -> Result<ColumnarValue> { + match sep { + ColumnarValue::Scalar(s) if s.is_null() => { + Ok(ColumnarValue::Scalar(ScalarValue::Utf8(None))) + } + ColumnarValue::Scalar(_) => Ok(ColumnarValue::Scalar(ScalarValue::Utf8(Some( + String::new(), + )))), + ColumnarValue::Array(arr) => { + let mut builder = StringBuilder::with_capacity(arr.len(), 0); + for row_idx in 0..arr.len() { + if arr.is_null(row_idx) { + builder.append_null(); + } else { + builder.append_value(""); + } + } + Ok(ColumnarValue::Array(Arc::new(builder.finish()) as ArrayRef)) + } + } +} + +fn spark_concat_ws(args: &[ColumnarValue], num_rows: usize) -> Result<ColumnarValue> { + let arrays = ColumnarValue::values_to_arrays(args)?; + + // Untyped-NULL separator → every row is NULL. Returning a scalar is enough; + // the framework broadcasts it to `num_rows` nulls when needed. + if *arrays[0].data_type() == DataType::Null { Review Comment: i dont think this is possible, since in `coerce_types` any `DataType::Null` is cast to `DataType::Utf8` ########## datafusion/spark/src/function/string/concat_ws.rs: ########## @@ -0,0 +1,289 @@ +// 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. + +//! Spark-compatible `concat_ws`: joins strings (and array elements) with a separator. +//! +//! Null scalar args and null array elements are skipped; a null separator yields a +//! null row. Non-string args are coerced to STRING; list args (`List`, `LargeList`, +//! `ListView`, `LargeListView`, `FixedSizeList`) expand their elements. +//! +//! Differences with DataFusion core `concat_ws`: +//! - Accepts list arguments and expands their elements +//! - Always returns Utf8 (Spark's `STRING` type) +//! - Coerces non-string scalars (numbers, booleans, dates, ...) to Utf8 + +use std::sync::Arc; + +use arrow::array::{ + Array, ArrayRef, AsArray, GenericListArray, LargeStringArray, OffsetSizeTrait, + StringArray, StringBuilder, StringViewArray, +}; +use arrow::datatypes::DataType; +use datafusion_common::{Result, ScalarValue}; +use datafusion_expr::{ + ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility, +}; + +use crate::function::error_utils::{ + invalid_arg_count_exec_err, unsupported_data_type_exec_err, +}; + +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct SparkConcatWs { + signature: Signature, +} + +impl Default for SparkConcatWs { + fn default() -> Self { + Self::new() + } +} + +impl SparkConcatWs { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + } + } +} + +impl ScalarUDFImpl for SparkConcatWs { + fn name(&self) -> &str { + "concat_ws" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { + Ok(DataType::Utf8) + } + + fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> { + if arg_types.is_empty() { + return Err(invalid_arg_count_exec_err("concat_ws", (1, i32::MAX), 0)); + } + Ok(arg_types + .iter() + .enumerate() + .map(|(i, dt)| match dt { + DataType::Utf8 | DataType::LargeUtf8 | DataType::Utf8View => dt.clone(), + // Non-separator list args expand their elements at runtime; + // normalize list variants so the kernel only sees List/LargeList. + DataType::List(f) + | DataType::ListView(f) + | DataType::FixedSizeList(f, _) + if i > 0 => + { + DataType::List(Arc::clone(f)) + } + DataType::LargeList(f) | DataType::LargeListView(f) if i > 0 => { + DataType::LargeList(Arc::clone(f)) + } + // Spark casts everything else (numbers, booleans, dates, + // binary, null...) to STRING. + _ => DataType::Utf8, + }) + .collect()) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + // Only separator provided → empty string (or NULL if separator is null). + // Arg-count validation happens in coerce_types at planning time. + if args.args.len() == 1 { + return only_separator(&args.args[0]); + } + + spark_concat_ws(&args.args, args.number_rows) + } +} + +fn only_separator(sep: &ColumnarValue) -> Result<ColumnarValue> { + match sep { + ColumnarValue::Scalar(s) if s.is_null() => { + Ok(ColumnarValue::Scalar(ScalarValue::Utf8(None))) + } + ColumnarValue::Scalar(_) => Ok(ColumnarValue::Scalar(ScalarValue::Utf8(Some( + String::new(), + )))), + ColumnarValue::Array(arr) => { + let mut builder = StringBuilder::with_capacity(arr.len(), 0); + for row_idx in 0..arr.len() { + if arr.is_null(row_idx) { + builder.append_null(); + } else { + builder.append_value(""); + } + } + Ok(ColumnarValue::Array(Arc::new(builder.finish()) as ArrayRef)) + } + } +} + +fn spark_concat_ws(args: &[ColumnarValue], num_rows: usize) -> Result<ColumnarValue> { + let arrays = ColumnarValue::values_to_arrays(args)?; + + // Untyped-NULL separator → every row is NULL. Returning a scalar is enough; + // the framework broadcasts it to `num_rows` nulls when needed. + if *arrays[0].data_type() == DataType::Null { + return Ok(ColumnarValue::Scalar(ScalarValue::Utf8(None))); + } + + let sep_view = StringView::try_new(&arrays[0])?; + let arg_views: Vec<ArgView> = arrays[1..] + .iter() + .map(ArgView::try_new) + .collect::<Result<_>>()?; + + let mut builder = StringBuilder::with_capacity(num_rows, num_rows * 16); + let mut buf = String::new(); Review Comment: instead of having a separate `buf`, we could try writing directly into `builder`, e.g. ```rust builder.write_str("a").unwrap(); // not fallible, can check the arrow code to confirm this builder.write_str("b").unwrap(); builder.append_value(""); // to finish it (add offset + validity) ``` ########## datafusion/spark/src/function/string/concat_ws.rs: ########## @@ -0,0 +1,289 @@ +// 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. + +//! Spark-compatible `concat_ws`: joins strings (and array elements) with a separator. +//! +//! Null scalar args and null array elements are skipped; a null separator yields a +//! null row. Non-string args are coerced to STRING; list args (`List`, `LargeList`, +//! `ListView`, `LargeListView`, `FixedSizeList`) expand their elements. +//! +//! Differences with DataFusion core `concat_ws`: +//! - Accepts list arguments and expands their elements +//! - Always returns Utf8 (Spark's `STRING` type) +//! - Coerces non-string scalars (numbers, booleans, dates, ...) to Utf8 + +use std::sync::Arc; + +use arrow::array::{ + Array, ArrayRef, AsArray, GenericListArray, LargeStringArray, OffsetSizeTrait, + StringArray, StringBuilder, StringViewArray, +}; +use arrow::datatypes::DataType; +use datafusion_common::{Result, ScalarValue}; +use datafusion_expr::{ + ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility, +}; + +use crate::function::error_utils::{ + invalid_arg_count_exec_err, unsupported_data_type_exec_err, +}; + +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct SparkConcatWs { + signature: Signature, +} + +impl Default for SparkConcatWs { + fn default() -> Self { + Self::new() + } +} + +impl SparkConcatWs { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + } + } +} + +impl ScalarUDFImpl for SparkConcatWs { + fn name(&self) -> &str { + "concat_ws" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { + Ok(DataType::Utf8) + } + + fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> { + if arg_types.is_empty() { + return Err(invalid_arg_count_exec_err("concat_ws", (1, i32::MAX), 0)); + } + Ok(arg_types + .iter() + .enumerate() + .map(|(i, dt)| match dt { + DataType::Utf8 | DataType::LargeUtf8 | DataType::Utf8View => dt.clone(), + // Non-separator list args expand their elements at runtime; + // normalize list variants so the kernel only sees List/LargeList. + DataType::List(f) + | DataType::ListView(f) + | DataType::FixedSizeList(f, _) + if i > 0 => + { + DataType::List(Arc::clone(f)) + } + DataType::LargeList(f) | DataType::LargeListView(f) if i > 0 => { + DataType::LargeList(Arc::clone(f)) + } + // Spark casts everything else (numbers, booleans, dates, + // binary, null...) to STRING. + _ => DataType::Utf8, + }) + .collect()) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + // Only separator provided → empty string (or NULL if separator is null). + // Arg-count validation happens in coerce_types at planning time. + if args.args.len() == 1 { + return only_separator(&args.args[0]); + } + + spark_concat_ws(&args.args, args.number_rows) + } +} + +fn only_separator(sep: &ColumnarValue) -> Result<ColumnarValue> { + match sep { + ColumnarValue::Scalar(s) if s.is_null() => { + Ok(ColumnarValue::Scalar(ScalarValue::Utf8(None))) + } + ColumnarValue::Scalar(_) => Ok(ColumnarValue::Scalar(ScalarValue::Utf8(Some( + String::new(), + )))), + ColumnarValue::Array(arr) => { + let mut builder = StringBuilder::with_capacity(arr.len(), 0); + for row_idx in 0..arr.len() { + if arr.is_null(row_idx) { + builder.append_null(); + } else { + builder.append_value(""); + } + } + Ok(ColumnarValue::Array(Arc::new(builder.finish()) as ArrayRef)) + } + } +} + +fn spark_concat_ws(args: &[ColumnarValue], num_rows: usize) -> Result<ColumnarValue> { + let arrays = ColumnarValue::values_to_arrays(args)?; + + // Untyped-NULL separator → every row is NULL. Returning a scalar is enough; + // the framework broadcasts it to `num_rows` nulls when needed. + if *arrays[0].data_type() == DataType::Null { + return Ok(ColumnarValue::Scalar(ScalarValue::Utf8(None))); + } + + let sep_view = StringView::try_new(&arrays[0])?; + let arg_views: Vec<ArgView> = arrays[1..] + .iter() + .map(ArgView::try_new) + .collect::<Result<_>>()?; + + let mut builder = StringBuilder::with_capacity(num_rows, num_rows * 16); + let mut buf = String::new(); + + for row_idx in 0..num_rows { + if sep_view.is_null(row_idx) { + builder.append_null(); + continue; + } + + let separator = sep_view.value(row_idx); + buf.clear(); + let mut first = true; + + for view in &arg_views { + view.write_row(row_idx, separator, &mut buf, &mut first)?; + } + + builder.append_value(&buf); + } + + Ok(ColumnarValue::Array(Arc::new(builder.finish()) as ArrayRef)) +} + +/// Typed view over a string array that downcasts once and exposes +/// per-row access without further dispatch. +enum StringView<'a> { + Utf8(&'a StringArray), + LargeUtf8(&'a LargeStringArray), + Utf8View(&'a StringViewArray), +} + +impl<'a> StringView<'a> { + fn try_new(arr: &'a ArrayRef) -> Result<Self> { + match arr.data_type() { + DataType::Utf8 => Ok(Self::Utf8(arr.as_string::<i32>())), + DataType::LargeUtf8 => Ok(Self::LargeUtf8(arr.as_string::<i64>())), + DataType::Utf8View => Ok(Self::Utf8View(arr.as_string_view())), + other => Err(unsupported_data_type_exec_err("concat_ws", "STRING", other)), + } + } + + fn value(&self, idx: usize) -> &str { + match self { + Self::Utf8(a) => a.value(idx), + Self::LargeUtf8(a) => a.value(idx), + Self::Utf8View(a) => a.value(idx), + } + } + + fn is_null(&self, idx: usize) -> bool { + match self { + Self::Utf8(a) => a.is_null(idx), + Self::LargeUtf8(a) => a.is_null(idx), + Self::Utf8View(a) => a.is_null(idx), + } + } +} + +/// Per-argument view: a string array, a list of strings, or an all-null +/// argument. The downcast happens once at construction time. +enum ArgView<'a> { + Null, + Str(StringView<'a>), + List(&'a GenericListArray<i32>), + LargeList(&'a GenericListArray<i64>), +} + +impl<'a> ArgView<'a> { + fn try_new(arr: &'a ArrayRef) -> Result<Self> { + match arr.data_type() { + DataType::Null => Ok(Self::Null), Review Comment: same here ########## datafusion/spark/src/function/string/concat_ws.rs: ########## @@ -0,0 +1,289 @@ +// 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. + +//! Spark-compatible `concat_ws`: joins strings (and array elements) with a separator. +//! +//! Null scalar args and null array elements are skipped; a null separator yields a +//! null row. Non-string args are coerced to STRING; list args (`List`, `LargeList`, +//! `ListView`, `LargeListView`, `FixedSizeList`) expand their elements. +//! +//! Differences with DataFusion core `concat_ws`: +//! - Accepts list arguments and expands their elements +//! - Always returns Utf8 (Spark's `STRING` type) +//! - Coerces non-string scalars (numbers, booleans, dates, ...) to Utf8 + +use std::sync::Arc; + +use arrow::array::{ + Array, ArrayRef, AsArray, GenericListArray, LargeStringArray, OffsetSizeTrait, + StringArray, StringBuilder, StringViewArray, +}; +use arrow::datatypes::DataType; +use datafusion_common::{Result, ScalarValue}; +use datafusion_expr::{ + ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility, +}; + +use crate::function::error_utils::{ + invalid_arg_count_exec_err, unsupported_data_type_exec_err, +}; + +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct SparkConcatWs { + signature: Signature, +} + +impl Default for SparkConcatWs { + fn default() -> Self { + Self::new() + } +} + +impl SparkConcatWs { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + } + } +} + +impl ScalarUDFImpl for SparkConcatWs { + fn name(&self) -> &str { + "concat_ws" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { + Ok(DataType::Utf8) + } + + fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> { + if arg_types.is_empty() { + return Err(invalid_arg_count_exec_err("concat_ws", (1, i32::MAX), 0)); + } + Ok(arg_types + .iter() + .enumerate() + .map(|(i, dt)| match dt { + DataType::Utf8 | DataType::LargeUtf8 | DataType::Utf8View => dt.clone(), + // Non-separator list args expand their elements at runtime; + // normalize list variants so the kernel only sees List/LargeList. + DataType::List(f) + | DataType::ListView(f) + | DataType::FixedSizeList(f, _) + if i > 0 => + { + DataType::List(Arc::clone(f)) + } + DataType::LargeList(f) | DataType::LargeListView(f) if i > 0 => { + DataType::LargeList(Arc::clone(f)) + } + // Spark casts everything else (numbers, booleans, dates, + // binary, null...) to STRING. + _ => DataType::Utf8, + }) + .collect()) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + // Only separator provided → empty string (or NULL if separator is null). + // Arg-count validation happens in coerce_types at planning time. + if args.args.len() == 1 { + return only_separator(&args.args[0]); + } + + spark_concat_ws(&args.args, args.number_rows) + } +} + +fn only_separator(sep: &ColumnarValue) -> Result<ColumnarValue> { + match sep { + ColumnarValue::Scalar(s) if s.is_null() => { + Ok(ColumnarValue::Scalar(ScalarValue::Utf8(None))) + } + ColumnarValue::Scalar(_) => Ok(ColumnarValue::Scalar(ScalarValue::Utf8(Some( + String::new(), + )))), + ColumnarValue::Array(arr) => { + let mut builder = StringBuilder::with_capacity(arr.len(), 0); + for row_idx in 0..arr.len() { + if arr.is_null(row_idx) { + builder.append_null(); + } else { + builder.append_value(""); + } + } + Ok(ColumnarValue::Array(Arc::new(builder.finish()) as ArrayRef)) + } + } +} + +fn spark_concat_ws(args: &[ColumnarValue], num_rows: usize) -> Result<ColumnarValue> { + let arrays = ColumnarValue::values_to_arrays(args)?; + + // Untyped-NULL separator → every row is NULL. Returning a scalar is enough; + // the framework broadcasts it to `num_rows` nulls when needed. + if *arrays[0].data_type() == DataType::Null { + return Ok(ColumnarValue::Scalar(ScalarValue::Utf8(None))); + } + + let sep_view = StringView::try_new(&arrays[0])?; + let arg_views: Vec<ArgView> = arrays[1..] + .iter() + .map(ArgView::try_new) + .collect::<Result<_>>()?; + + let mut builder = StringBuilder::with_capacity(num_rows, num_rows * 16); + let mut buf = String::new(); + + for row_idx in 0..num_rows { + if sep_view.is_null(row_idx) { + builder.append_null(); + continue; + } + + let separator = sep_view.value(row_idx); + buf.clear(); + let mut first = true; + + for view in &arg_views { + view.write_row(row_idx, separator, &mut buf, &mut first)?; + } + + builder.append_value(&buf); + } + + Ok(ColumnarValue::Array(Arc::new(builder.finish()) as ArrayRef)) +} + +/// Typed view over a string array that downcasts once and exposes +/// per-row access without further dispatch. +enum StringView<'a> { + Utf8(&'a StringArray), + LargeUtf8(&'a LargeStringArray), + Utf8View(&'a StringViewArray), +} + +impl<'a> StringView<'a> { + fn try_new(arr: &'a ArrayRef) -> Result<Self> { + match arr.data_type() { + DataType::Utf8 => Ok(Self::Utf8(arr.as_string::<i32>())), + DataType::LargeUtf8 => Ok(Self::LargeUtf8(arr.as_string::<i64>())), + DataType::Utf8View => Ok(Self::Utf8View(arr.as_string_view())), + other => Err(unsupported_data_type_exec_err("concat_ws", "STRING", other)), + } + } + + fn value(&self, idx: usize) -> &str { + match self { + Self::Utf8(a) => a.value(idx), + Self::LargeUtf8(a) => a.value(idx), + Self::Utf8View(a) => a.value(idx), + } + } + + fn is_null(&self, idx: usize) -> bool { + match self { + Self::Utf8(a) => a.is_null(idx), + Self::LargeUtf8(a) => a.is_null(idx), + Self::Utf8View(a) => a.is_null(idx), + } + } +} + +/// Per-argument view: a string array, a list of strings, or an all-null +/// argument. The downcast happens once at construction time. +enum ArgView<'a> { + Null, + Str(StringView<'a>), + List(&'a GenericListArray<i32>), + LargeList(&'a GenericListArray<i64>), +} + +impl<'a> ArgView<'a> { + fn try_new(arr: &'a ArrayRef) -> Result<Self> { + match arr.data_type() { + DataType::Null => Ok(Self::Null), + DataType::Utf8 | DataType::LargeUtf8 | DataType::Utf8View => { + Ok(Self::Str(StringView::try_new(arr)?)) + } + DataType::List(_) => Ok(Self::List(arr.as_list::<i32>())), + DataType::LargeList(_) => Ok(Self::LargeList(arr.as_list::<i64>())), + other => Err(unsupported_data_type_exec_err( + "concat_ws", + "STRING or ARRAY<STRING>", + other, + )), + } + } + + fn write_row( + &self, + row_idx: usize, + sep: &str, + buf: &mut String, + first: &mut bool, + ) -> Result<()> { + match self { + Self::Null => {} + Self::Str(view) => { + if !view.is_null(row_idx) { + push_part(buf, view.value(row_idx), sep, first); + } + } + Self::List(list) => write_list_row(*list, row_idx, sep, buf, first)?, + Self::LargeList(list) => write_list_row(*list, row_idx, sep, buf, first)?, + } + Ok(()) + } +} + +fn write_list_row<O: OffsetSizeTrait>( + list: &GenericListArray<O>, + row_idx: usize, + sep: &str, + buf: &mut String, + first: &mut bool, +) -> Result<()> { + if list.is_null(row_idx) { + return Ok(()); + } + let values = list.value(row_idx); + // An empty array (e.g. `array()`) or an all-null-typed array contributes + // nothing — Spark renders it as the empty string, not an error. + if values.is_empty() || *values.data_type() == DataType::Null { + return Ok(()); + } + let view = StringView::try_new(&values)?; Review Comment: are we guaranteed that child types of lists are strings? i dont see this guarantee anywhere -- This is an automated message from the Apache Git Service. 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