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// 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 `make_array` function.
use std::{any::Any, sync::Arc};
use arrow::array::{ArrayData, Capacities, MutableArrayData};
use arrow_array::{
new_null_array, Array, ArrayRef, GenericListArray, NullArray, OffsetSizeTrait,
};
use arrow_buffer::OffsetBuffer;
use arrow_schema::DataType::{LargeList, List, Null};
use arrow_schema::{DataType, Field};
use datafusion_common::internal_err;
use datafusion_common::{plan_err, utils::array_into_list_array_nullable, Result};
use datafusion_expr::type_coercion::binary::comparison_coercion;
use datafusion_expr::TypeSignature;
use datafusion_expr::{ColumnarValue, ScalarUDFImpl, Signature, Volatility};
use crate::utils::make_scalar_function;
make_udf_expr_and_func!(
MakeArray,
make_array,
"Returns an Arrow array using the specified input expressions.",
make_array_udf
);
#[derive(Debug)]
pub struct MakeArray {
signature: Signature,
aliases: Vec<String>,
}
impl Default for MakeArray {
fn default() -> Self {
Self::new()
}
}
impl MakeArray {
pub fn new() -> Self {
Self {
signature: Signature::one_of(
vec![TypeSignature::UserDefined, TypeSignature::Any(0)],
Volatility::Immutable,
),
aliases: vec![String::from("make_list")],
}
}
}
impl ScalarUDFImpl for MakeArray {
fn as_any(&self) -> &dyn Any {
self
}
fn name(&self) -> &str {
"make_array"
}
fn signature(&self) -> &Signature {
&self.signature
}
fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
match arg_types.len() {
0 => Ok(empty_array_type()),
_ => {
let mut expr_type = DataType::Null;
for arg_type in arg_types {
if !arg_type.equals_datatype(&DataType::Null) {
expr_type = arg_type.clone();
break;
}
}
if expr_type.is_null() {
expr_type = DataType::Int64;
}
Ok(List(Arc::new(Field::new("item", expr_type, true))))
}
}
}
fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue> {
make_scalar_function(make_array_inner)(args)
}
fn invoke_no_args(&self, _number_rows: usize) -> Result<ColumnarValue> {
make_scalar_function(make_array_inner)(&[])
}
fn aliases(&self) -> &[String] {
&self.aliases
}
fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> {
let new_type = arg_types.iter().skip(1).try_fold(
arg_types.first().unwrap().clone(),
|acc, x| {
// The coerced types found by `comparison_coercion` are not guaranteed to be
// coercible for the arguments. `comparison_coercion` returns more loose
// types that can be coerced to both `acc` and `x` for comparison purpose.
// See `maybe_data_types` for the actual coercion.
let coerced_type = comparison_coercion(&acc, x);
if let Some(coerced_type) = coerced_type {
Ok(coerced_type)
} else {
internal_err!("Coercion from {acc:?} to {x:?} failed.")
}
},
)?;
Ok(vec![new_type; arg_types.len()])
}
}
// Empty array is a special case that is useful for many other array functions
pub(super) fn empty_array_type() -> DataType {
DataType::List(Arc::new(Field::new("item", DataType::Int64, true)))
}
/// `make_array_inner` is the implementation of the `make_array` function.
/// Constructs an array using the input `data` as `ArrayRef`.
/// Returns a reference-counted `Array` instance result.
pub(crate) fn make_array_inner(arrays: &[ArrayRef]) -> Result<ArrayRef> {
let mut data_type = Null;
for arg in arrays {
let arg_data_type = arg.data_type();
if !arg_data_type.equals_datatype(&Null) {
data_type = arg_data_type.clone();
break;
}
}
match data_type {
// Either an empty array or all nulls:
Null => {
let length = arrays.iter().map(|a| a.len()).sum();
// By default Int64
let array = new_null_array(&DataType::Int64, length);
Ok(Arc::new(array_into_list_array_nullable(array)))
}
LargeList(..) => array_array::<i64>(arrays, data_type),
_ => array_array::<i32>(arrays, data_type),
}
}
/// Convert one or more [`ArrayRef`] of the same type into a
/// `ListArray` or 'LargeListArray' depending on the offset size.
///
/// # Example (non nested)
///
/// Calling `array(col1, col2)` where col1 and col2 are non nested
/// would return a single new `ListArray`, where each row was a list
/// of 2 elements:
///
/// ```text
/// ┌─────────┐ ┌─────────┐ ┌──────────────┐
/// │ ┌─────┐ │ │ ┌─────┐ │ │ ┌──────────┐ │
/// │ │ A │ │ │ │ X │ │ │ │ [A, X] │ │
/// │ ├─────┤ │ │ ├─────┤ │ │ ├──────────┤ │
/// │ │NULL │ │ │ │ Y │ │──────────▶│ │[NULL, Y] │ │
/// │ ├─────┤ │ │ ├─────┤ │ │ ├──────────┤ │
/// │ │ C │ │ │ │ Z │ │ │ │ [C, Z] │ │
/// │ └─────┘ │ │ └─────┘ │ │ └──────────┘ │
/// └─────────┘ └─────────┘ └──────────────┘
/// col1 col2 output
/// ```
///
/// # Example (nested)
///
/// Calling `array(col1, col2)` where col1 and col2 are lists
/// would return a single new `ListArray`, where each row was a list
/// of the corresponding elements of col1 and col2.
///
/// ``` text
/// ┌──────────────┐ ┌──────────────┐ ┌─────────────────────────────┐
/// │ ┌──────────┐ │ │ ┌──────────┐ │ │ ┌────────────────────────┐ │
/// │ │ [A, X] │ │ │ │ [] │ │ │ │ [[A, X], []] │ │
/// │ ├──────────┤ │ │ ├──────────┤ │ │ ├────────────────────────┤ │
/// │ │[NULL, Y] │ │ │ │[Q, R, S] │ │───────▶│ │ [[NULL, Y], [Q, R, S]] │ │
/// │ ├──────────┤ │ │ ├──────────┤ │ │ ├────────────────────────│ │
/// │ │ [C, Z] │ │ │ │ NULL │ │ │ │ [[C, Z], NULL] │ │
/// │ └──────────┘ │ │ └──────────┘ │ │ └────────────────────────┘ │
/// └──────────────┘ └──────────────┘ └─────────────────────────────┘
/// col1 col2 output
/// ```
fn array_array<O: OffsetSizeTrait>(
args: &[ArrayRef],
data_type: DataType,
) -> Result<ArrayRef> {
// do not accept 0 arguments.
if args.is_empty() {
return plan_err!("Array requires at least one argument");
}
let mut data = vec![];
let mut total_len = 0;
for arg in args {
let arg_data = if arg.as_any().is::<NullArray>() {
ArrayData::new_empty(&data_type)
} else {
arg.to_data()
};
total_len += arg_data.len();
data.push(arg_data);
}
let mut offsets: Vec<O> = Vec::with_capacity(total_len);
offsets.push(O::usize_as(0));
let capacity = Capacities::Array(total_len);
let data_ref = data.iter().collect::<Vec<_>>();
let mut mutable = MutableArrayData::with_capacities(data_ref, true, capacity);
let num_rows = args[0].len();
for row_idx in 0..num_rows {
for (arr_idx, arg) in args.iter().enumerate() {
if !arg.as_any().is::<NullArray>()
&& !arg.is_null(row_idx)
&& arg.is_valid(row_idx)
{
mutable.extend(arr_idx, row_idx, row_idx + 1);
} else {
mutable.extend_nulls(1);
}
}
offsets.push(O::usize_as(mutable.len()));
}
let data = mutable.freeze();
Ok(Arc::new(GenericListArray::<O>::try_new(
Arc::new(Field::new("item", data_type, true)),
OffsetBuffer::new(offsets.into()),
arrow_array::make_array(data),
None,
)?))
}