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fix: Return NULL for empty BIT_XOR sliding windows #26095

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fix: Return NULL for empty BIT_XOR sliding windows #26095

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253 changes: 210 additions & 43 deletions datafusion/functions-aggregate/src/bit_and_or_xor.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -64,15 +64,17 @@ macro_rules! group_accumulator_helper {
};
}

/// `accumulator_helper` is a macro accepting (ArrowPrimitiveType, BitwiseOperationType, bool)
/// Create an accumulator for the integer type and bitwise operation.
macro_rules! accumulator_helper {
($t:ty, $opr:expr, $is_distinct: expr) => {
($t:ty, $opr:expr, $is_distinct:expr, $is_sliding:expr) => {
match $opr {
BitwiseOperationType::And => Ok(Box::<BitAndAccumulator<$t>>::default()),
BitwiseOperationType::Or => Ok(Box::<BitOrAccumulator<$t>>::default()),
BitwiseOperationType::Xor => {
if $is_distinct {
Ok(Box::<DistinctBitXorAccumulator<$t>>::default())
} else if $is_sliding {
Ok(Box::<SlidingBitXorAccumulator<$t>>::default())
} else {
Ok(Box::<BitXorAccumulator<$t>>::default())
}
Expand All @@ -87,17 +89,33 @@ macro_rules! accumulator_helper {
/// `opr` is [BitwiseOperationType]
/// `is_distinct` is boolean value indicating whether the operation is distinct or not.
macro_rules! downcast_bitwise_accumulator {
($args:ident, $opr:expr, $is_distinct: expr) => {
($args:ident, $opr:expr, $is_distinct:expr, $is_sliding:expr) => {
match $args.return_field.data_type() {
DataType::Null => Ok(Box::new(NoopAccumulator::default())),
DataType::Int8 => accumulator_helper!(Int8Type, $opr, $is_distinct),
DataType::Int16 => accumulator_helper!(Int16Type, $opr, $is_distinct),
DataType::Int32 => accumulator_helper!(Int32Type, $opr, $is_distinct),
DataType::Int64 => accumulator_helper!(Int64Type, $opr, $is_distinct),
DataType::UInt8 => accumulator_helper!(UInt8Type, $opr, $is_distinct),
DataType::UInt16 => accumulator_helper!(UInt16Type, $opr, $is_distinct),
DataType::UInt32 => accumulator_helper!(UInt32Type, $opr, $is_distinct),
DataType::UInt64 => accumulator_helper!(UInt64Type, $opr, $is_distinct),
DataType::Int8 => {
accumulator_helper!(Int8Type, $opr, $is_distinct, $is_sliding)
}
DataType::Int16 => {
accumulator_helper!(Int16Type, $opr, $is_distinct, $is_sliding)
}
DataType::Int32 => {
accumulator_helper!(Int32Type, $opr, $is_distinct, $is_sliding)
}
DataType::Int64 => {
accumulator_helper!(Int64Type, $opr, $is_distinct, $is_sliding)
}
DataType::UInt8 => {
accumulator_helper!(UInt8Type, $opr, $is_distinct, $is_sliding)
}
DataType::UInt16 => {
accumulator_helper!(UInt16Type, $opr, $is_distinct, $is_sliding)
}
DataType::UInt32 => {
accumulator_helper!(UInt32Type, $opr, $is_distinct, $is_sliding)
}
DataType::UInt64 => {
accumulator_helper!(UInt64Type, $opr, $is_distinct, $is_sliding)
}
_ => {
not_impl_err!(
"{} not supported for {}: {}",
Expand Down Expand Up @@ -253,7 +271,24 @@ impl AggregateUDFImpl for BitwiseOperation {
}

fn accumulator(&self, acc_args: AccumulatorArgs) -> Result<Box<dyn Accumulator>> {
downcast_bitwise_accumulator!(acc_args, self.operation, acc_args.is_distinct)
downcast_bitwise_accumulator!(
acc_args,
self.operation,
acc_args.is_distinct,
false
)
}

fn create_sliding_accumulator(
&self,
acc_args: AccumulatorArgs,
) -> Result<Box<dyn Accumulator>> {
downcast_bitwise_accumulator!(
acc_args,
self.operation,
acc_args.is_distinct,
true
)
}

fn state_fields(&self, args: StateFieldsArgs) -> Result<Vec<FieldRef>> {
Expand Down Expand Up @@ -460,29 +495,99 @@ where
Ok(())
}

fn evaluate(&mut self) -> Result<ScalarValue> {
ScalarValue::new_primitive::<T>(self.value, &T::DATA_TYPE)
}

fn size(&self) -> usize {
size_of_val(self)
}

fn state(&mut self) -> Result<Vec<ScalarValue>> {
Ok(vec![self.evaluate()?])
}

fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
self.update_batch(states)
}
}

/// Tracks non-null cardinality so an empty window returns NULL, while a
/// non-empty window whose values cancel returns zero. Ordinary aggregation
/// retains its single-field state and primitive groups accumulator.
struct SlidingBitXorAccumulator<T: ArrowNumericType> {
value: T::Native,
count: u64,
}

impl<T: ArrowNumericType> std::fmt::Debug for SlidingBitXorAccumulator<T> {
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
write!(f, "SlidingBitXorAccumulator({})", T::DATA_TYPE)
}
}

impl<T: ArrowNumericType> Default for SlidingBitXorAccumulator<T> {
fn default() -> Self {
Self {
value: T::Native::usize_as(0),
count: 0,
}
}
}

impl<T: ArrowNumericType> Accumulator for SlidingBitXorAccumulator<T>
where
T::Native: std::ops::BitXor<Output = T::Native>,
{
fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
let values = values[0].as_primitive::<T>();
self.count += (values.len() - values.null_count()) as u64;
if let Some(value) = arrow::compute::bit_xor(values) {
self.value = self.value ^ value;
}
Ok(())
}

fn retract_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
// XOR is it's own inverse
self.update_batch(values)
let values = values[0].as_primitive::<T>();
self.count -= (values.len() - values.null_count()) as u64;
// XOR is its own inverse; nullness also depends on the remaining count.
if let Some(value) = arrow::compute::bit_xor(values) {
self.value = self.value ^ value;
}
Ok(())
}

fn supports_retract_batch(&self) -> bool {
true
}

fn evaluate(&mut self) -> Result<ScalarValue> {
ScalarValue::new_primitive::<T>(self.value, &T::DATA_TYPE)
ScalarValue::new_primitive::<T>(
(self.count != 0).then_some(self.value),
&T::DATA_TYPE,
)
}

fn size(&self) -> usize {
size_of_val(self)
}

fn state(&mut self) -> Result<Vec<ScalarValue>> {
Ok(vec![self.evaluate()?])
Ok(vec![
self.evaluate()?,
ScalarValue::UInt64(Some(self.count)),
])
}

fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
self.update_batch(states)
if let Some(value) = arrow::compute::bit_xor(states[0].as_primitive::<T>()) {
self.value = self.value ^ value;
}
if let Some(count) = arrow::compute::sum(states[1].as_primitive::<UInt64Type>()) {
self.count += count;
}
Ok(())
}
}

Expand Down Expand Up @@ -572,35 +677,97 @@ mod tests {
use std::sync::Arc;

use arrow::array::{ArrayRef, UInt64Array};
use arrow::datatypes::UInt64Type;
use datafusion_common::ScalarValue;

use crate::bit_and_or_xor::BitXorAccumulator;
use arrow::datatypes::{DataType, Field, Schema, UInt64Type};
use datafusion_common::{Result, ScalarValue};
use datafusion_expr::Accumulator;
use datafusion_expr::function::AccumulatorArgs;

use super::{SlidingBitXorAccumulator, bit_xor_udaf};

fn array(values: &[Option<u64>]) -> ArrayRef {
Arc::new(UInt64Array::from(values.to_vec()))
}

fn accumulator_args(schema: &Schema) -> AccumulatorArgs<'_> {
AccumulatorArgs {
return_field: schema.field(0).clone().into(),
schema,
ignore_nulls: false,
order_bys: &[],
is_reversed: false,
name: "bit_xor(v)",
is_distinct: false,
exprs: &[],
expr_fields: &[],
}
}

#[test]
fn test_bit_xor_accumulator() {
let mut accumulator = BitXorAccumulator::<UInt64Type> { value: None };
let batches: Vec<_> = vec![vec![1, 2], vec![1]]
.into_iter()
.map(|b| Arc::new(b.into_iter().collect::<UInt64Array>()) as ArrayRef)
.collect();

let added = &[Arc::clone(&batches[0])];
let retracted = &[Arc::clone(&batches[1])];

// XOR of 1..3 is 3
accumulator.update_batch(added).unwrap();
assert_eq!(
accumulator.evaluate().unwrap(),
ScalarValue::UInt64(Some(3))
);
fn sliding_bit_xor_retract_last_non_null() -> Result<()> {
let schema = Schema::new(vec![Field::new("v", DataType::UInt64, true)]);
let mut accumulator =
bit_xor_udaf().create_sliding_accumulator(accumulator_args(&schema))?;
accumulator.update_batch(&[array(&[Some(7), None, Some(7), None])])?;
assert_eq!(accumulator.evaluate()?, ScalarValue::UInt64(Some(0)));
accumulator.retract_batch(&[array(&[Some(7), None])])?;
assert_eq!(accumulator.evaluate()?, ScalarValue::UInt64(Some(7)));
accumulator.retract_batch(&[array(&[Some(7)])])?;
assert_eq!(accumulator.evaluate()?, ScalarValue::UInt64(None));

// A real zero remains non-null when the empty accumulator is reused.
accumulator.update_batch(&[array(&[Some(0)])])?;
assert_eq!(accumulator.evaluate()?, ScalarValue::UInt64(Some(0)));
accumulator.retract_batch(&[array(&[None, Some(0)])])?;
assert_eq!(accumulator.evaluate()?, ScalarValue::UInt64(None));
Ok(())
}

// Removing [1] ^ 3 = 2
accumulator.retract_batch(retracted).unwrap();
assert_eq!(
accumulator.evaluate().unwrap(),
ScalarValue::UInt64(Some(2))
);
#[test]
fn sliding_bit_xor_merge_preserves_count() -> Result<()> {
let mut states = Vec::new();
for values in [vec![Some(7); 4], vec![Some(9)], vec![None]] {
let mut partial = SlidingBitXorAccumulator::<UInt64Type>::default();
partial.update_batch(&[array(&values)])?;
states.push(partial.state()?);
}
let arrays = (0..2)
.map(|index| {
ScalarValue::iter_to_array(
states.iter().map(|state| state[index].clone()),
)
})
.collect::<Result<Vec<_>>>()?;
let mut accumulator = SlidingBitXorAccumulator::<UInt64Type>::default();
accumulator.merge_batch(&arrays)?;

// The zero-valued partial contributes four input rows.
accumulator.retract_batch(&[array(&[Some(7); 4])])?;
assert_eq!(accumulator.evaluate()?, ScalarValue::UInt64(Some(9)));
accumulator.retract_batch(&[array(&[Some(9)])])?;
assert_eq!(accumulator.evaluate()?, ScalarValue::UInt64(None));
Ok(())
}

#[test]
fn bit_xor_factory_contracts() -> Result<()> {
let schema = Schema::new(vec![Field::new("v", DataType::UInt64, true)]);
let udf = bit_xor_udaf();
let args = accumulator_args(&schema);
let values = array(&[Some(7), Some(7), None]);

let mut ordinary = udf.accumulator(args.clone())?;
assert!(!ordinary.supports_retract_batch());
ordinary.update_batch(&[Arc::clone(&values)])?;
assert_eq!(ordinary.state()?, vec![ScalarValue::UInt64(Some(0))]);

let mut distinct = udf.create_sliding_accumulator(AccumulatorArgs {
is_distinct: true,
..args
})?;
assert!(!distinct.supports_retract_batch());
distinct.update_batch(&[values])?;
assert_eq!(distinct.evaluate()?, ScalarValue::UInt64(Some(7)));
assert_eq!(distinct.state()?.len(), 1);
Ok(())
}
}
66 changes: 66 additions & 0 deletions datafusion/sqllogictest/test_files/bit_xor_sliding_window.slt
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Original file line number Diff line number Diff line change
@@ -0,0 +1,66 @@
# 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.

# A populated frame containing only NULLs must return NULL after its last
# non-null input leaves. Zero remains a valid result for cancelling values.
statement ok
SET datafusion.execution.batch_size = 2;

statement ok
CREATE TABLE bit_xor_window(id INT, v BIGINT) AS VALUES
(1, 7), (2, NULL), (3, NULL), (4, 0), (5, 7), (6, 7);

# Exercise every integer accumulator type across batch boundaries.
query IIIIIIIII
SELECT id,
bit_xor(arrow_cast(v, 'Int8')) OVER w,
bit_xor(arrow_cast(v, 'Int16')) OVER w,
bit_xor(arrow_cast(v, 'Int32')) OVER w,
bit_xor(v) OVER w,
bit_xor(arrow_cast(v, 'UInt8')) OVER w,
bit_xor(arrow_cast(v, 'UInt16')) OVER w,
bit_xor(arrow_cast(v, 'UInt32')) OVER w,
bit_xor(arrow_cast(v, 'UInt64')) OVER w
FROM bit_xor_window
WINDOW w AS (ORDER BY id ROWS BETWEEN CURRENT ROW AND 1 FOLLOWING)
ORDER BY id;
----
1 7 7 7 7 7 7 7 7
2 NULL NULL NULL NULL NULL NULL NULL NULL
3 0 0 0 0 0 0 0 0
4 7 7 7 7 7 7 7 7
5 0 0 0 0 0 0 0 0
6 7 7 7 7 7 7 7 7

# Empty and all-null frames also differ from a one-row frame containing zero.
query II
SELECT id, bit_xor(v) OVER (ORDER BY id ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING)
FROM bit_xor_window
ORDER BY id;
----
1 NULL
2 7
3 NULL
4 NULL
5 0
6 7

statement ok
DROP TABLE bit_xor_window;

statement ok
RESET datafusion.execution.batch_size;
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