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269 changes: 269 additions & 0 deletions datafusion/spark/src/function/string/concat.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,269 @@
// 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 arrow::array::Array;
use arrow::buffer::NullBuffer;
use arrow::datatypes::DataType;
use datafusion_common::{Result, ScalarValue};
use datafusion_expr::{
ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, TypeSignature,
Volatility,
};
use datafusion_functions::string::concat::ConcatFunc;
use std::any::Any;
use std::sync::Arc;

/// Spark-compatible `concat` expression
/// <https://spark.apache.org/docs/latest/api/sql/index.html#concat>
///
/// Concatenates multiple input strings into a single string.
/// Returns NULL if any input is NULL.
///
/// Differences with DataFusion concat:
/// - Support 0 arguments
/// - Return NULL if any input is NULL
#[derive(Debug, PartialEq, Eq, Hash)]
pub struct SparkConcat {
signature: Signature,
}

impl Default for SparkConcat {
fn default() -> Self {
Self::new()
}
}

impl SparkConcat {
pub fn new() -> Self {
Self {
signature: Signature::one_of(
vec![TypeSignature::UserDefined, TypeSignature::Nullary],
Volatility::Immutable,
),
}
}
}

impl ScalarUDFImpl for SparkConcat {
fn as_any(&self) -> &dyn Any {
self
}

fn name(&self) -> &str {
"concat"
}

fn signature(&self) -> &Signature {
&self.signature
}

fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
Ok(DataType::Utf8)
}

fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> {
spark_concat(args)
}

fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> {
// Accept any string types, including zero arguments
Ok(arg_types.to_vec())
}
}

/// Represents the null state for Spark concat
enum NullMaskResolution {
/// Return NULL as the result (e.g., scalar inputs with at least one NULL)
ReturnNull,
/// No null mask needed (e.g., all scalar inputs are non-NULL)
NoMask,
/// Null mask to apply for arrays
Apply(NullBuffer),
}

/// Concatenates strings, returning NULL if any input is NULL
/// This is a Spark-specific wrapper around DataFusion's concat that returns NULL
/// if any argument is NULL (Spark behavior), whereas DataFusion's concat ignores NULLs.
fn spark_concat(args: ScalarFunctionArgs) -> Result<ColumnarValue> {
let ScalarFunctionArgs {
args: arg_values,
arg_fields,
number_rows,
return_field,
config_options,
} = args;

// Handle zero-argument case: return empty string
if arg_values.is_empty() {
return Ok(ColumnarValue::Scalar(ScalarValue::Utf8(
Some(String::new()),
)));
}

// Step 1: Check for NULL mask in incoming args
let null_mask = compute_null_mask(&arg_values, number_rows)?;

// If all scalars and any is NULL, return NULL immediately
if matches!(null_mask, NullMaskResolution::ReturnNull) {
return Ok(ColumnarValue::Scalar(ScalarValue::Utf8(None)));
}

// Step 2: Delegate to DataFusion's concat
let concat_func = ConcatFunc::new();
let func_args = ScalarFunctionArgs {
args: arg_values,
arg_fields,
number_rows,
return_field,
config_options,
};
let result = concat_func.invoke_with_args(func_args)?;

// Step 3: Apply NULL mask to result
apply_null_mask(result, null_mask)
}

/// Compute NULL mask for the arguments using NullBuffer::union
fn compute_null_mask(
args: &[ColumnarValue],
number_rows: usize,
) -> Result<NullMaskResolution> {
// Check if all arguments are scalars
let all_scalars = args
.iter()
.all(|arg| matches!(arg, ColumnarValue::Scalar(_)));

if all_scalars {
// For scalars, check if any is NULL
for arg in args {
if let ColumnarValue::Scalar(scalar) = arg {
if scalar.is_null() {
return Ok(NullMaskResolution::ReturnNull);
}
}
}
// No NULLs in scalars
Ok(NullMaskResolution::NoMask)
} else {
// For arrays, compute NULL mask for each row using NullBuffer::union
let array_len = args
.iter()
.find_map(|arg| match arg {
ColumnarValue::Array(array) => Some(array.len()),
_ => None,
})
.unwrap_or(number_rows);

// Convert all scalars to arrays for uniform processing
let arrays: Result<Vec<_>> = args
.iter()
.map(|arg| match arg {
ColumnarValue::Array(array) => Ok(Arc::clone(array)),
ColumnarValue::Scalar(scalar) => scalar.to_array_of_size(array_len),
})
.collect();
let arrays = arrays?;

// Use NullBuffer::union to combine all null buffers
let combined_nulls = arrays
.iter()
.map(|arr| arr.nulls())
.fold(None, |acc, nulls| NullBuffer::union(acc.as_ref(), nulls));

match combined_nulls {
Some(nulls) => Ok(NullMaskResolution::Apply(nulls)),
None => Ok(NullMaskResolution::NoMask),
}
}
}

/// Apply NULL mask to the result using NullBuffer::union
fn apply_null_mask(
result: ColumnarValue,
null_mask: NullMaskResolution,
) -> Result<ColumnarValue> {
match (result, null_mask) {
// Scalar with ReturnNull mask means return NULL
(ColumnarValue::Scalar(_), NullMaskResolution::ReturnNull) => {
Ok(ColumnarValue::Scalar(ScalarValue::Utf8(None)))
}
// Scalar without mask, return as-is
(scalar @ ColumnarValue::Scalar(_), NullMaskResolution::NoMask) => Ok(scalar),
// Array with NULL mask - use NullBuffer::union to combine nulls
(ColumnarValue::Array(array), NullMaskResolution::Apply(null_mask)) => {
// Combine the result's existing nulls with our computed null mask
let combined_nulls = NullBuffer::union(array.nulls(), Some(&null_mask));

// Create new array with combined nulls
let new_array = array
.into_data()
.into_builder()
.nulls(combined_nulls)
.build()?;

Ok(ColumnarValue::Array(Arc::new(arrow::array::make_array(
new_array,
))))
}
// Array without NULL mask, return as-is
(array @ ColumnarValue::Array(_), NullMaskResolution::NoMask) => Ok(array),
// Edge cases that shouldn't happen in practice
(scalar, _) => Ok(scalar),
}
}

#[cfg(test)]
mod tests {
use super::*;
use crate::function::utils::test::test_scalar_function;
use arrow::array::StringArray;
use arrow::datatypes::DataType;
use datafusion_common::Result;

#[test]
fn test_concat_basic() -> Result<()> {
test_scalar_function!(
SparkConcat::new(),
vec![
ColumnarValue::Scalar(ScalarValue::Utf8(Some("Spark".to_string()))),
ColumnarValue::Scalar(ScalarValue::Utf8(Some("SQL".to_string()))),
],
Ok(Some("SparkSQL")),
&str,
DataType::Utf8,
StringArray
);
Ok(())
}

#[test]
fn test_concat_with_null() -> Result<()> {
test_scalar_function!(
SparkConcat::new(),
vec![
ColumnarValue::Scalar(ScalarValue::Utf8(Some("Spark".to_string()))),
ColumnarValue::Scalar(ScalarValue::Utf8(Some("SQL".to_string()))),
ColumnarValue::Scalar(ScalarValue::Utf8(None)),
],
Ok(None),
&str,
DataType::Utf8,
StringArray
);
Ok(())
}
}
9 changes: 8 additions & 1 deletion datafusion/spark/src/function/string/mod.rs
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@

pub mod ascii;
pub mod char;
pub mod concat;
pub mod ilike;
pub mod like;
pub mod luhn_check;
Expand All @@ -27,6 +28,7 @@ use std::sync::Arc;

make_udf_function!(ascii::SparkAscii, ascii);
make_udf_function!(char::CharFunc, char);
make_udf_function!(concat::SparkConcat, concat);
make_udf_function!(ilike::SparkILike, ilike);
make_udf_function!(like::SparkLike, like);
make_udf_function!(luhn_check::SparkLuhnCheck, luhn_check);
Expand All @@ -44,6 +46,11 @@ pub mod expr_fn {
"Returns the ASCII character having the binary equivalent to col. If col is larger than 256 the result is equivalent to char(col % 256).",
arg1
));
export_functions!((
concat,
"Concatenates multiple input strings into a single string. Returns NULL if any input is NULL.",
args
));
export_functions!((
ilike,
"Returns true if str matches pattern (case insensitive).",
Expand All @@ -62,5 +69,5 @@ pub mod expr_fn {
}

pub fn functions() -> Vec<Arc<ScalarUDF>> {
vec![ascii(), char(), ilike(), like(), luhn_check()]
vec![ascii(), char(), concat(), ilike(), like(), luhn_check()]
}
48 changes: 48 additions & 0 deletions datafusion/sqllogictest/test_files/spark/string/concat.slt
Original file line number Diff line number Diff line change
@@ -0,0 +1,48 @@
# 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.

query T
SELECT concat('Spark', 'SQL');
----
SparkSQL

query T
SELECT concat('Spark', 'SQL', NULL);
----
NULL

query T
SELECT concat('', '1', '', '2');
----
12

query T
SELECT concat();
----
(empty)

query T
SELECT concat('');
----
(empty)


query T
SELECT concat(a, b, c) from (select 'a' a, 'b' b, 'c' c union all select null a, 'b', 'c') order by 1 nulls last;
----
abc
NULL
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