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Use filtered_null_mask in CountGroupsAccumulator and PrimitiveGroupsAccumulator #11825

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Use filtered_null_mask in CountGroupsAccumulator and PrimitiveGroupsAccumulator #11825

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b9128eb
Use `filtered_null_mask` in prim_op and count
alamb Aug 5, 2024
4114656
Merge remote-tracking branch 'apache/main' into alamb/refactor_filtering
alamb Sep 5, 2024
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73 changes: 28 additions & 45 deletions datafusion/functions-aggregate-common/src/aggregate/groups_accumulator/prim_op.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -15,17 +15,13 @@
// specific language governing permissions and limitations
// under the License.

use std::sync::Arc;

use arrow::array::{ArrayRef, AsArray, BooleanArray, PrimitiveArray};
use arrow::buffer::NullBuffer;
use arrow::compute;
use arrow::datatypes::ArrowPrimitiveType;
use crate::aggregate::groups_accumulator::accumulate::NullState;
use crate::aggregate::groups_accumulator::nulls::{filtered_null_mask, set_nulls};
use arrow::array::{ArrayRef, ArrowPrimitiveType, AsArray, BooleanArray, PrimitiveArray};
use arrow::datatypes::DataType;
use datafusion_common::{internal_datafusion_err, DataFusionError, Result};
use datafusion_common::Result;
use datafusion_expr_common::groups_accumulator::{EmitTo, GroupsAccumulator};

use super::accumulate::NullState;
use std::sync::Arc;

/// An accumulator that implements a single operation over
/// [`ArrowPrimitiveType`] where the accumulated state is the same as
Expand Down Expand Up @@ -147,44 +143,31 @@ where
values: &[ArrayRef],
opt_filter: Option<&BooleanArray>,
) -> Result<Vec<ArrayRef>> {
let values = values[0].as_primitive::<T>().clone();

// Initializing state with starting values
let initial_state =
PrimitiveArray::<T>::from_value(self.starting_value, values.len());

// Recalculating values in case there is filter
let values = match opt_filter {
None => values,
Some(filter) => {
let (filter_values, filter_nulls) = filter.clone().into_parts();
// Calculating filter mask as a result of bitand of filter, and converting it to null buffer
let filter_bool = match filter_nulls {
Some(filter_nulls) => filter_nulls.inner() & &filter_values,
None => filter_values,
};
let filter_nulls = NullBuffer::from(filter_bool);

// Rebuilding input values with a new nulls mask, which is equal to
// the union of original nulls and filter mask
let (dt, values_buf, original_nulls) = values.into_parts();
let nulls_buf =
NullBuffer::union(original_nulls.as_ref(), Some(&filter_nulls));
PrimitiveArray::<T>::new(values_buf, nulls_buf).with_data_type(dt)
let values = values[0].as_primitive::<T>();

// Figure out which values will be non null in the output
let nulls = filtered_null_mask(opt_filter, values);

// Initializing state with starting value
let mut state = vec![self.starting_value; values.len()];

// update state with any non-filtered input
if nulls.is_some() {
// mask out any filtered / null input values
let values = set_nulls(values.clone(), nulls.clone());
for (state, value) in state.iter_mut().zip(values.iter()) {
if let Some(value) = value {
(self.prim_fn)(state, value);
}
}
} else {
// no nulls in input, so iterate over all values
let all_values = values.values().iter();
for (state, value) in state.iter_mut().zip(all_values) {
(self.prim_fn)(state, *value)
}
};

let state_values = compute::binary_mut(initial_state, &values, |mut x, y| {
(self.prim_fn)(&mut x, y);
x
});
let state_values = state_values
.map_err(|_| {
internal_datafusion_err!(
"initial_values underlying buffer must not be shared"
)
})?
.map_err(DataFusionError::from)?
let state_values = PrimitiveArray::<T>::new(state.into(), nulls)
.with_data_type(self.data_type.clone());

Ok(vec![Arc::new(state_values)])
Expand Down
74 changes: 22 additions & 52 deletions datafusion/functions-aggregate/src/count.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,10 @@
// under the License.

use ahash::RandomState;
use datafusion_functions_aggregate_common::aggregate::count_distinct::BytesViewDistinctCountAccumulator;
use datafusion_functions_aggregate_common::aggregate::count_distinct::{
BytesDistinctCountAccumulator, BytesViewDistinctCountAccumulator,
FloatDistinctCountAccumulator, PrimitiveDistinctCountAccumulator,
};
use std::collections::HashSet;
use std::ops::BitAnd;
use std::{fmt::Debug, sync::Arc};
Expand Down Expand Up @@ -47,11 +50,8 @@ use datafusion_expr::{
EmitTo, GroupsAccumulator, Signature, Volatility,
};
use datafusion_expr::{Expr, ReversedUDAF, TypeSignature};
use datafusion_functions_aggregate_common::aggregate::count_distinct::{
BytesDistinctCountAccumulator, FloatDistinctCountAccumulator,
PrimitiveDistinctCountAccumulator,
};
use datafusion_functions_aggregate_common::aggregate::groups_accumulator::accumulate::accumulate_indices;
use datafusion_functions_aggregate_common::aggregate::groups_accumulator::nulls::filtered_null_mask;
use datafusion_physical_expr_common::binary_map::OutputType;

make_udaf_expr_and_func!(
Expand Down Expand Up @@ -450,59 +450,29 @@ impl GroupsAccumulator for CountGroupsAccumulator {
/// Converts an input batch directly to a state batch
///
/// The state of `COUNT` is always a single Int64Array:
/// * `1` (for non-null, non filtered values)
/// * `0` (for null values)
/// * `1` (for non null, non filtered values)
/// * `0` (for filtered or null values)
fn convert_to_state(
&self,
values: &[ArrayRef],
opt_filter: Option<&BooleanArray>,
) -> Result<Vec<ArrayRef>> {
let values = &values[0];

let state_array = match (values.logical_nulls(), opt_filter) {
(None, None) => {
// In case there is no nulls in input and no filter, returning array of 1
Arc::new(Int64Array::from_value(1, values.len()))
}
(Some(nulls), None) => {
// If there are any nulls in input values -- casting `nulls` (true for values, false for nulls)
// of input array to Int64
let nulls = BooleanArray::new(nulls.into_inner(), None);
compute::cast(&nulls, &DataType::Int64)?
}
(None, Some(filter)) => {
// If there is only filter
// - applying filter null mask to filter values by bitand filter values and nulls buffers
// (using buffers guarantees absence of nulls in result)
// - casting result of bitand to Int64 array
let (filter_values, filter_nulls) = filter.clone().into_parts();

let state_buf = match filter_nulls {
Some(filter_nulls) => &filter_values & filter_nulls.inner(),
None => filter_values,
};

let boolean_state = BooleanArray::new(state_buf, None);
compute::cast(&boolean_state, &DataType::Int64)?
}
(Some(nulls), Some(filter)) => {
// For both input nulls and filter
// - applying filter null mask to filter values by bitand filter values and nulls buffers
// (using buffers guarantees absence of nulls in result)
// - applying values null mask to filter buffer by another bitand on filter result and
// nulls from input values
// - casting result to Int64 array
let (filter_values, filter_nulls) = filter.clone().into_parts();

let filter_buf = match filter_nulls {
Some(filter_nulls) => &filter_values & filter_nulls.inner(),
None => filter_values,
};
let state_buf = &filter_buf & nulls.inner();

let boolean_state = BooleanArray::new(state_buf, None);
compute::cast(&boolean_state, &DataType::Int64)?
}
let nulls = filtered_null_mask(opt_filter, values);

let state_array: ArrayRef = if let Some(nulls) = nulls {
// nulls (false) in the filtered mask means we should output 0
// counts for those values.
//
// cast kernel does the following conversion:

// * `true` -> `1`
// * `false` -> `0`
let nulls = BooleanArray::new(nulls.into_inner(), None);
compute::cast(&nulls, &DataType::Int64)?
} else {
// all input values contribute a 1
Arc::new(Int64Array::from_value(1, values.len()))
};

Ok(vec![state_array])
Expand Down