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Add value_from_statisics to AggregateUDFImpl, remove special case for min/max/count aggregate statistics #12296

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merged 5 commits into from
Sep 30, 2024
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Add value_from_statisics to AggregateUDFImpl, remove special case for min/max/count aggregate statistics #12296

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f478344
Removes min/max/count comparison based on name in aggregate statistics
edmondop Sep 2, 2024
751e35a
Abstracting away value from statistics
edmondop Sep 13, 2024
016decf
Removing imports
edmondop Sep 13, 2024
f41dd3e
Introduced StatisticsArgs
edmondop Sep 28, 2024
faf6c45
Fixed docs
edmondop Sep 28, 2024
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22 changes: 21 additions & 1 deletion datafusion/expr/src/udaf.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,8 @@ use std::vec;

use arrow::datatypes::{DataType, Field};

use datafusion_common::{exec_err, not_impl_err, Result, ScalarValue};
use datafusion_common::{exec_err, not_impl_err, Result, ScalarValue, Statistics};
use datafusion_physical_expr_common::physical_expr::PhysicalExpr;

use crate::expr::AggregateFunction;
use crate::function::{
Expand Down Expand Up @@ -262,6 +263,16 @@ impl AggregateUDF {
self.inner.is_descending()
}

pub fn value_from_stats(
&self,
statistics: &Statistics,
data_type: &DataType,
arguments: &[Arc<dyn PhysicalExpr>],
) -> Option<ScalarValue> {
self.inner
.value_from_stats(statistics, &data_type, arguments)
}

/// See [`AggregateUDFImpl::default_value`] for more details.
pub fn default_value(&self, data_type: &DataType) -> Result<ScalarValue> {
self.inner.default_value(data_type)
Expand Down Expand Up @@ -574,6 +585,15 @@ pub trait AggregateUDFImpl: Debug + Send + Sync {
fn is_descending(&self) -> Option<bool> {
None
}
// Return the value of the current UDF from the statistics
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Suggested change
// Return the value of the current UDF from the statistics
/// Return the value of this UDF for the query if it can be determined entirely from
/// statistics and arguments.
///
/// For example, if the minimum value of column `x` is known exactly in the statistics,
/// then `MIN(x)` can be replaced by that value, significantly improving query performance.

fn value_from_stats(
&self,
_statistics: &Statistics,
_data_type: &DataType,
_arguments: &[Arc<dyn PhysicalExpr>],
) -> Option<ScalarValue> {
None
}

/// Returns default value of the function given the input is all `null`.
///
Expand Down
32 changes: 32 additions & 0 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 +16,9 @@
// under the License.

use ahash::RandomState;
use datafusion_common::stats::Precision;
use datafusion_functions_aggregate_common::aggregate::count_distinct::BytesViewDistinctCountAccumulator;
use datafusion_physical_expr::expressions;
use std::collections::HashSet;
use std::ops::BitAnd;
use std::{fmt::Debug, sync::Arc};
Expand Down Expand Up @@ -54,6 +56,7 @@ use datafusion_functions_aggregate_common::aggregate::count_distinct::{
use datafusion_functions_aggregate_common::aggregate::groups_accumulator::accumulate::accumulate_indices;
use datafusion_physical_expr_common::binary_map::OutputType;

use datafusion_common::utils::expr::COUNT_STAR_EXPANSION;
make_udaf_expr_and_func!(
Count,
count,
Expand Down Expand Up @@ -291,6 +294,35 @@ impl AggregateUDFImpl for Count {
fn default_value(&self, _data_type: &DataType) -> Result<ScalarValue> {
Ok(ScalarValue::Int64(Some(0)))
}

fn value_from_stats(
&self,
statistics: &datafusion_common::Statistics,
_data_type: &DataType,
arguments: &[Arc<dyn datafusion_physical_expr::PhysicalExpr>],
) -> Option<ScalarValue> {
if let Precision::Exact(num_rows) = statistics.num_rows {
if arguments.len() == 1 {
// TODO optimize with exprs other than Column
if let Some(col_expr) =
arguments[0].as_any().downcast_ref::<expressions::Column>()
{
let current_val =
&statistics.column_statistics[col_expr.index()].null_count;
if let &Precision::Exact(val) = current_val {
return Some(ScalarValue::Int64(Some((num_rows - val) as i64)));
}
} else if let Some(lit_expr) =
arguments[0].as_any().downcast_ref::<expressions::Literal>()
{
if lit_expr.value() == &COUNT_STAR_EXPANSION {
return Some(ScalarValue::Int64(Some(num_rows as i64)));
}
}
}
}
None
}
}

#[derive(Debug)]
Expand Down
86 changes: 85 additions & 1 deletion datafusion/functions-aggregate/src/min_max.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -49,11 +49,15 @@ use arrow::datatypes::{
UInt8Type,
};
use arrow_schema::IntervalUnit;
use datafusion_common::stats::Precision;
use datafusion_common::{
downcast_value, exec_err, internal_err, DataFusionError, Result,
downcast_value, exec_err, internal_err, ColumnStatistics, DataFusionError, Result,
Statistics,
};
use datafusion_functions_aggregate_common::aggregate::groups_accumulator::prim_op::PrimitiveGroupsAccumulator;
use datafusion_physical_expr::{expressions, PhysicalExpr};
use std::fmt::Debug;
use std::sync::Arc;

use arrow::datatypes::i256;
use arrow::datatypes::{
Expand Down Expand Up @@ -147,6 +151,55 @@ macro_rules! instantiate_min_accumulator {
}};
}

trait FromColumnStatistics {
fn value_from_column_statistics(
&self,
stats: &ColumnStatistics,
) -> Option<ScalarValue>;

fn value_from_statistics(
&self,
statistics: &Statistics,
data_type: &DataType,
arguments: &[Arc<dyn PhysicalExpr>],
) -> Option<ScalarValue> {
if let Precision::Exact(num_rows) = &statistics.num_rows {
match *num_rows {
0 => return ScalarValue::try_from(data_type).ok(),
value if value > 0 => {
let col_stats = &statistics.column_statistics;
if arguments.len() == 1 {
// TODO optimize with exprs other than Column
if let Some(col_expr) =
arguments[0].as_any().downcast_ref::<expressions::Column>()
{
return self.value_from_column_statistics(
&col_stats[col_expr.index()],
);
}
}
}
_ => {}
}
}
None
}
}

impl FromColumnStatistics for Max {
fn value_from_column_statistics(
&self,
col_stats: &ColumnStatistics,
) -> Option<ScalarValue> {
if let Precision::Exact(ref val) = col_stats.max_value {
if !val.is_null() {
return Some(val.clone());
}
}
None
}
}

impl AggregateUDFImpl for Max {
fn as_any(&self) -> &dyn std::any::Any {
self
Expand Down Expand Up @@ -272,6 +325,7 @@ impl AggregateUDFImpl for Max {
fn is_descending(&self) -> Option<bool> {
Some(true)
}

fn order_sensitivity(&self) -> datafusion_expr::utils::AggregateOrderSensitivity {
datafusion_expr::utils::AggregateOrderSensitivity::Insensitive
}
Expand All @@ -282,6 +336,14 @@ impl AggregateUDFImpl for Max {
fn reverse_expr(&self) -> datafusion_expr::ReversedUDAF {
datafusion_expr::ReversedUDAF::Identical
}
fn value_from_stats(
&self,
statistics: &Statistics,
data_type: &DataType,
arguments: &[Arc<dyn PhysicalExpr>],
) -> Option<ScalarValue> {
self.value_from_statistics(statistics, data_type, arguments)
}
}

// Statically-typed version of min/max(array) -> ScalarValue for string types
Expand Down Expand Up @@ -926,6 +988,20 @@ impl Default for Min {
}
}

impl FromColumnStatistics for Min {
fn value_from_column_statistics(
&self,
col_stats: &ColumnStatistics,
) -> Option<ScalarValue> {
if let Precision::Exact(ref val) = col_stats.min_value {
if !val.is_null() {
return Some(val.clone());
}
}
None
}
}

impl AggregateUDFImpl for Min {
fn as_any(&self) -> &dyn std::any::Any {
self
Expand Down Expand Up @@ -1052,6 +1128,14 @@ impl AggregateUDFImpl for Min {
Some(false)
}

fn value_from_stats(
&self,
statistics: &Statistics,
data_type: &DataType,
arguments: &[Arc<dyn PhysicalExpr>],
) -> Option<ScalarValue> {
self.value_from_statistics(statistics, data_type, arguments)
}
fn order_sensitivity(&self) -> datafusion_expr::utils::AggregateOrderSensitivity {
datafusion_expr::utils::AggregateOrderSensitivity::Insensitive
}
Expand Down
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