datafusion-functions-nested 55.0.0

Nested Type Function packages for the DataFusion query engine
Documentation
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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 array_resize function.

use crate::utils::make_scalar_function;
use arrow::array::{
    Array, ArrayRef, Capacities, GenericListArray, Int64Array, MutableArrayData,
    NullBufferBuilder, OffsetSizeTrait, new_null_array,
};
use arrow::buffer::OffsetBuffer;
use arrow::datatypes::DataType;
use arrow::datatypes::{ArrowNativeType, Field};
use arrow::datatypes::{
    DataType::{LargeList, List},
    FieldRef,
};
use datafusion_common::cast::{as_int64_array, as_large_list_array, as_list_array};
use datafusion_common::utils::ListCoercion;
use datafusion_common::{Result, ScalarValue, exec_err, internal_datafusion_err};
use datafusion_expr::{
    ArrayFunctionArgument, ArrayFunctionSignature, ColumnarValue, Documentation,
    ScalarFunctionArgs, ScalarUDFImpl, Signature, TypeSignature, Volatility,
};
use datafusion_macros::user_doc;
use std::sync::Arc;

make_udf_expr_and_func!(
    ArrayResize,
    array_resize,
    array size value,
    "returns an array with the specified size filled with the given value.",
    array_resize_udf
);

#[user_doc(
    doc_section(label = "Array Functions"),
    description = "Resizes the list to contain size elements.",
    syntax_example = "array_resize(array, size[, value])",
    sql_example = r#"```sql
> select array_resize([1, 2, 3], 5, 0);
+-------------------------------------+
| array_resize(List([1,2,3],5,0))     |
+-------------------------------------+
| [1, 2, 3, 0, 0]                     |
+-------------------------------------+
```"#,
    argument(
        name = "array",
        description = "Array expression. Can be a constant, column, or function, and any combination of array operators."
    ),
    argument(name = "size", description = "New size of given array."),
    argument(
        name = "value",
        description = "If expanding the array, defines the values to fill in. Defaults to null."
    )
)]
#[derive(Debug, PartialEq, Eq, Hash)]
pub struct ArrayResize {
    signature: Signature,
    aliases: Vec<String>,
}

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

impl ArrayResize {
    pub fn new() -> Self {
        Self {
            signature: Signature::one_of(
                vec![
                    TypeSignature::ArraySignature(ArrayFunctionSignature::Array {
                        arguments: vec![
                            ArrayFunctionArgument::Array,
                            ArrayFunctionArgument::Index,
                        ],
                        array_coercion: Some(ListCoercion::FixedSizedListToList),
                    }),
                    TypeSignature::ArraySignature(ArrayFunctionSignature::Array {
                        arguments: vec![
                            ArrayFunctionArgument::Array,
                            ArrayFunctionArgument::Index,
                            ArrayFunctionArgument::Element,
                        ],
                        array_coercion: Some(ListCoercion::FixedSizedListToList),
                    }),
                ],
                Volatility::Immutable,
            ),
            aliases: vec!["list_resize".to_string()],
        }
    }
}

impl ScalarUDFImpl for ArrayResize {
    fn name(&self) -> &str {
        "array_resize"
    }

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

    fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
        match &arg_types[0] {
            List(field) => Ok(List(Arc::clone(field))),
            LargeList(field) => Ok(LargeList(Arc::clone(field))),
            DataType::Null => {
                Ok(List(Arc::new(Field::new_list_field(DataType::Int64, true))))
            }
            _ => exec_err!(
                "Not reachable, data_type should be List, LargeList or FixedSizeList"
            ),
        }
    }

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

    fn aliases(&self) -> &[String] {
        &self.aliases
    }

    fn documentation(&self) -> Option<&Documentation> {
        self.doc()
    }
}

fn array_resize_inner(arg: &[ArrayRef]) -> Result<ArrayRef> {
    if arg.len() < 2 || arg.len() > 3 {
        return exec_err!("array_resize needs two or three arguments");
    }

    let array = &arg[0];

    // Checks if entire array is null
    if array.logical_null_count() == array.len() {
        let return_type = match array.data_type() {
            List(field) => List(Arc::clone(field)),
            LargeList(field) => LargeList(Arc::clone(field)),
            _ => {
                return exec_err!(
                    "array_resize does not support type '{:?}'.",
                    array.data_type()
                );
            }
        };
        return Ok(new_null_array(&return_type, array.len()));
    }

    let new_len = as_int64_array(&arg[1])?;
    let new_element = if arg.len() == 3 {
        Some(Arc::clone(&arg[2]))
    } else {
        None
    };

    match &arg[0].data_type() {
        List(field) => {
            let array = as_list_array(&arg[0])?;
            general_list_resize::<i32>(array, new_len, field, new_element)
        }
        LargeList(field) => {
            let array = as_large_list_array(&arg[0])?;
            general_list_resize::<i64>(array, new_len, field, new_element)
        }
        array_type => exec_err!("array_resize does not support type '{array_type}'."),
    }
}

/// array_resize keep the original array and append the default element to the end
fn general_list_resize<O: OffsetSizeTrait + TryInto<i64>>(
    array: &GenericListArray<O>,
    count_array: &Int64Array,
    field: &FieldRef,
    default_element: Option<ArrayRef>,
) -> Result<ArrayRef> {
    let data_type = array.value_type();

    let values = array.values();
    let original_data = values.to_data();

    // Track the largest per-row growth so the uniform-fill fast path can
    // materialize one reusable fill buffer of the required size.
    let mut max_extra: usize = 0;
    let mut output_values_len: usize = 0;
    for (row_index, offset_window) in array.offsets().windows(2).enumerate() {
        if array.is_null(row_index) || count_array.is_null(row_index) {
            continue;
        }
        let target_count = count_array.value(row_index).to_usize().ok_or_else(|| {
            internal_datafusion_err!("array_resize: failed to convert size to usize")
        })?;
        output_values_len =
            output_values_len.checked_add(target_count).ok_or_else(|| {
                internal_datafusion_err!("array_resize: output size overflow")
            })?;
        let current_len = (offset_window[1] - offset_window[0]).to_usize().unwrap();
        if target_count > current_len {
            max_extra = max_extra.max(target_count - current_len);
        }
    }

    if output_values_len > max_resize_values(&data_type)
        || O::from_usize(output_values_len).is_none()
    {
        return exec_err!(
            "array_resize: resulting array of {output_values_len} elements exceeds the maximum array size"
        );
    }

    // The fast path is valid when at least one row grows and every row would
    // use the same fill value.
    let use_bulk_fill = max_extra > 0
        && match &default_element {
            None => true,
            Some(fill_array) => {
                let len = fill_array.len();
                let null_count = fill_array.logical_null_count();

                len <= 1
                    || null_count == len
                    || (null_count == 0 && {
                        let first = fill_array.slice(0, 1);
                        (1..len)
                            .all(|i| fill_array.slice(i, 1).as_ref() == first.as_ref())
                    })
            }
        };

    if use_bulk_fill {
        // Fast path: materialize one reusable fill buffer for all grown rows.
        let fill_scalar = match &default_element {
            None => ScalarValue::try_from(&data_type)?,
            Some(fill_array) if fill_array.logical_null_count() == fill_array.len() => {
                ScalarValue::try_from(&data_type)?
            }
            Some(fill_array) => ScalarValue::try_from_array(fill_array.as_ref(), 0)?,
        };
        let fill_values = fill_scalar.to_array_of_size(max_extra)?;
        let default_value_data = fill_values.to_data();
        build_resized_list(
            array,
            count_array,
            field,
            &original_data,
            &default_value_data,
            output_values_len,
            |mutable, _, extra_count| Ok(mutable.try_extend(1, 0, extra_count)?),
        )
    } else {
        // Slow path: rows may need different fill values, so append from the
        // corresponding slot in the input fill array for each grown element.
        let fill_values = match default_element {
            Some(fill_values) => fill_values,
            None => {
                let null_scalar = ScalarValue::try_from(&data_type)?;
                null_scalar.to_array_of_size(original_data.len())?
            }
        };
        let default_value_data = fill_values.to_data();
        build_resized_list(
            array,
            count_array,
            field,
            &original_data,
            &default_value_data,
            output_values_len,
            |mutable, row_index, extra_count| {
                for _ in 0..extra_count {
                    mutable.try_extend(1, row_index, row_index + 1)?;
                }
                Ok(())
            },
        )
    }
}

fn build_resized_list<O, F>(
    array: &GenericListArray<O>,
    count_array: &Int64Array,
    field: &FieldRef,
    original_data: &arrow::array::ArrayData,
    default_value_data: &arrow::array::ArrayData,
    output_values_len: usize,
    mut append_fill_values: F,
) -> Result<ArrayRef>
where
    O: OffsetSizeTrait + TryInto<i64>,
    F: FnMut(&mut MutableArrayData, usize, usize) -> Result<()>,
{
    let capacity = Capacities::Array(output_values_len);
    let mut offsets = vec![O::usize_as(0)];
    let mut mutable = MutableArrayData::with_capacities(
        vec![original_data, default_value_data],
        false,
        capacity,
    );
    let mut null_builder = NullBufferBuilder::new(array.len());

    for (row_index, offset_window) in array.offsets().windows(2).enumerate() {
        if array.is_null(row_index) || count_array.is_null(row_index) {
            null_builder.append_null();
            offsets.push(offsets[row_index]);
            continue;
        }
        null_builder.append_non_null();

        let count = count_array.value(row_index).to_usize().ok_or_else(|| {
            internal_datafusion_err!("array_resize: failed to convert size to usize")
        })?;
        let count = O::usize_as(count);
        let start = offset_window[0];
        if start + count > offset_window[1] {
            let extra_count = (start + count - offset_window[1]).to_usize().unwrap();
            let end = offset_window[1];
            mutable.try_extend(0, start.to_usize().unwrap(), end.to_usize().unwrap())?;
            append_fill_values(&mut mutable, row_index, extra_count)?;
        } else {
            let end = start + count;
            mutable.try_extend(0, start.to_usize().unwrap(), end.to_usize().unwrap())?;
        };
        offsets.push(offsets[row_index] + count);
    }

    let data = mutable.freeze();

    Ok(Arc::new(GenericListArray::<O>::try_new(
        Arc::clone(field),
        OffsetBuffer::<O>::new(offsets.into()),
        arrow::array::make_array(data),
        null_builder.finish(),
    )?))
}

/// Largest element count whose eager value buffer stays within `isize::MAX`
/// bytes, so `array_resize` rejects oversized results instead of panicking.
/// Only primitive and `FixedSizeBinary` leaves are byte-exact.
fn max_resize_values(value_type: &DataType) -> usize {
    let element_width = match value_type {
        DataType::FixedSizeBinary(size) if *size > 0 => *size as usize,
        _ => value_type.primitive_width().unwrap_or(size_of::<u128>()),
    };

    (isize::MAX as usize) / element_width.max(1)
}

#[cfg(test)]
mod tests {
    use super::array_resize_inner;
    use arrow::array::{
        ArrayRef, AsArray, FixedSizeBinaryArray, Int64Array, LargeListArray, ListArray,
    };
    use arrow::buffer::{NullBuffer, OffsetBuffer, ScalarBuffer};
    use arrow::datatypes::{DataType, Field, Int32Type, Int64Type};
    use datafusion_common::Result;
    use std::sync::Arc;

    #[test]
    fn test_array_resize_null_size_returns_null() -> Result<()> {
        let array: ArrayRef =
            Arc::new(ListArray::from_iter_primitive::<Int32Type, _, _>(vec![
                Some(vec![Some(1), Some(2), Some(3)]),
                Some(vec![Some(4), Some(5)]),
            ]));
        let size: ArrayRef = Arc::new(Int64Array::new(
            ScalarBuffer::from(vec![2, 1]),
            Some(NullBuffer::from(vec![true, false])),
        ));

        let result = array_resize_inner(&[array, size])?;
        let expected = ListArray::from_iter_primitive::<Int32Type, _, _>(vec![
            Some(vec![Some(1), Some(2)]),
            None,
        ]);

        assert_eq!(result.as_list::<i32>(), &expected);

        Ok(())
    }

    #[test]
    fn test_array_resize_large_size_errors_without_panicking() {
        let array: ArrayRef =
            Arc::new(ListArray::from_iter_primitive::<Int64Type, _, _>(vec![
                Some(vec![Some(1)]),
            ]));
        let size: ArrayRef = Arc::new(Int64Array::from(vec![i64::MAX]));
        let fill: ArrayRef = Arc::new(Int64Array::from(vec![0]));

        let err = array_resize_inner(&[array, size, fill]).unwrap_err();
        assert!(
            err.to_string().contains("exceeds the maximum array size"),
            "unexpected error: {err}"
        );
    }

    #[test]
    fn test_array_resize_fixed_size_binary_large_size_errors_without_panicking() {
        let values =
            FixedSizeBinaryArray::try_from_iter(vec![vec![0u8; 32]].into_iter()).unwrap();
        let elem_field =
            Arc::new(Field::new_list_field(DataType::FixedSizeBinary(32), true));
        let offsets = OffsetBuffer::<i64>::new(vec![0i64, 1].into());
        let array: ArrayRef = Arc::new(LargeListArray::new(
            elem_field,
            offsets,
            Arc::new(values) as ArrayRef,
            None,
        ));
        // Passes the width-16 bound (isize::MAX / 16) but overflows at width 32.
        let size: ArrayRef = Arc::new(Int64Array::from(vec![400_000_000_000_000_000i64]));

        let err = array_resize_inner(&[array, size]).unwrap_err();
        assert!(
            err.to_string().contains("exceeds the maximum array size"),
            "unexpected error: {err}"
        );
    }

    #[test]
    fn test_array_resize_accumulates_values_across_rows() {
        // Each row's target (6e17) is individually under the width-8 cap
        // (isize::MAX / 8), but their sum (1.2e18) exceeds it, so the guard
        // must reject based on the accumulated total rather than per row.
        let values = Int64Array::from(vec![1, 2]);
        let offsets = OffsetBuffer::<i64>::new(vec![0i64, 1, 2].into());
        let elem_field = Arc::new(Field::new_list_field(DataType::Int64, true));
        let array: ArrayRef = Arc::new(LargeListArray::new(
            elem_field,
            offsets,
            Arc::new(values) as ArrayRef,
            None,
        ));
        let size: ArrayRef = Arc::new(Int64Array::from(vec![
            600_000_000_000_000_000i64,
            600_000_000_000_000_000i64,
        ]));

        let err = array_resize_inner(&[array, size]).unwrap_err();
        assert!(
            err.to_string().contains("1200000000000000000"),
            "expected accumulated total in error: {err}"
        );
        assert!(
            err.to_string().contains("exceeds the maximum array size"),
            "unexpected error: {err}"
        );
    }
}