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* Add input_nullable to UDAF args StateField/AccumulatorArgs This follows how it done for input_type and only provide a single value. But might need to be changed into a Vec in the future. This is need when we are moving `arrag_agg` to udaf where one of the states nullability will depend on the nullability of the input. * Make ArragAgg (not ordered or distinct) into a UDAF * Add roundtrip_expr_api test case * Address PR comments * Propegate input nullability for aggregates * Remove from accumulator args * first draft Signed-off-by: jayzhan211 <[email protected]> * cleanup Signed-off-by: jayzhan211 <[email protected]> * fix test Signed-off-by: jayzhan211 <[email protected]> * distinct Signed-off-by: jayzhan211 <[email protected]> * fix Signed-off-by: jayzhan211 <[email protected]> * address comment Signed-off-by: jayzhan211 <[email protected]> --------- Signed-off-by: jayzhan211 <[email protected]> Co-authored-by: Emil Ejbyfeldt <[email protected]>
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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. | ||
|
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//! `ARRAY_AGG` aggregate implementation: [`ArrayAgg`] | ||
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use arrow::array::{Array, ArrayRef, AsArray}; | ||
use arrow::datatypes::DataType; | ||
use arrow_schema::Field; | ||
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use datafusion_common::cast::as_list_array; | ||
use datafusion_common::utils::array_into_list_array_nullable; | ||
use datafusion_common::ScalarValue; | ||
use datafusion_common::{internal_err, Result}; | ||
use datafusion_expr::function::{AccumulatorArgs, StateFieldsArgs}; | ||
use datafusion_expr::utils::format_state_name; | ||
use datafusion_expr::AggregateUDFImpl; | ||
use datafusion_expr::{Accumulator, Signature, Volatility}; | ||
use std::collections::HashSet; | ||
use std::sync::Arc; | ||
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make_udaf_expr_and_func!( | ||
ArrayAgg, | ||
array_agg, | ||
expression, | ||
"input values, including nulls, concatenated into an array", | ||
array_agg_udaf | ||
); | ||
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#[derive(Debug)] | ||
/// ARRAY_AGG aggregate expression | ||
pub struct ArrayAgg { | ||
signature: Signature, | ||
alias: Vec<String>, | ||
} | ||
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impl Default for ArrayAgg { | ||
fn default() -> Self { | ||
Self { | ||
signature: Signature::any(1, Volatility::Immutable), | ||
alias: vec!["array_agg".to_string()], | ||
} | ||
} | ||
} | ||
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impl AggregateUDFImpl for ArrayAgg { | ||
fn as_any(&self) -> &dyn std::any::Any { | ||
self | ||
} | ||
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// TODO: change name to lowercase | ||
fn name(&self) -> &str { | ||
"ARRAY_AGG" | ||
} | ||
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fn aliases(&self) -> &[String] { | ||
&self.alias | ||
} | ||
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fn signature(&self) -> &Signature { | ||
&self.signature | ||
} | ||
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fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> { | ||
Ok(DataType::List(Arc::new(Field::new( | ||
"item", | ||
arg_types[0].clone(), | ||
true, | ||
)))) | ||
} | ||
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fn state_fields(&self, args: StateFieldsArgs) -> Result<Vec<Field>> { | ||
if args.is_distinct { | ||
return Ok(vec![Field::new_list( | ||
format_state_name(args.name, "distinct_array_agg"), | ||
Field::new("item", args.input_type.clone(), true), | ||
true, | ||
)]); | ||
} | ||
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Ok(vec![Field::new_list( | ||
format_state_name(args.name, "array_agg"), | ||
Field::new("item", args.input_type.clone(), true), | ||
true, | ||
)]) | ||
} | ||
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fn accumulator(&self, acc_args: AccumulatorArgs) -> Result<Box<dyn Accumulator>> { | ||
if acc_args.is_distinct { | ||
return Ok(Box::new(DistinctArrayAggAccumulator::try_new( | ||
acc_args.input_type, | ||
)?)); | ||
} | ||
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Ok(Box::new(ArrayAggAccumulator::try_new(acc_args.input_type)?)) | ||
} | ||
} | ||
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#[derive(Debug)] | ||
pub struct ArrayAggAccumulator { | ||
values: Vec<ArrayRef>, | ||
datatype: DataType, | ||
} | ||
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impl ArrayAggAccumulator { | ||
/// new array_agg accumulator based on given item data type | ||
pub fn try_new(datatype: &DataType) -> Result<Self> { | ||
Ok(Self { | ||
values: vec![], | ||
datatype: datatype.clone(), | ||
}) | ||
} | ||
} | ||
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impl Accumulator for ArrayAggAccumulator { | ||
fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> { | ||
// Append value like Int64Array(1,2,3) | ||
if values.is_empty() { | ||
return Ok(()); | ||
} | ||
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if values.len() != 1 { | ||
return internal_err!("expects single batch"); | ||
} | ||
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let val = Arc::clone(&values[0]); | ||
if val.len() > 0 { | ||
self.values.push(val); | ||
} | ||
Ok(()) | ||
} | ||
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fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> { | ||
// Append value like ListArray(Int64Array(1,2,3), Int64Array(4,5,6)) | ||
if states.is_empty() { | ||
return Ok(()); | ||
} | ||
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if states.len() != 1 { | ||
return internal_err!("expects single state"); | ||
} | ||
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let list_arr = as_list_array(&states[0])?; | ||
for arr in list_arr.iter().flatten() { | ||
self.values.push(arr); | ||
} | ||
Ok(()) | ||
} | ||
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fn state(&mut self) -> Result<Vec<ScalarValue>> { | ||
Ok(vec![self.evaluate()?]) | ||
} | ||
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fn evaluate(&mut self) -> Result<ScalarValue> { | ||
// Transform Vec<ListArr> to ListArr | ||
let element_arrays: Vec<&dyn Array> = | ||
self.values.iter().map(|a| a.as_ref()).collect(); | ||
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if element_arrays.is_empty() { | ||
return Ok(ScalarValue::new_null_list(self.datatype.clone(), true, 1)); | ||
} | ||
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let concated_array = arrow::compute::concat(&element_arrays)?; | ||
let list_array = array_into_list_array_nullable(concated_array); | ||
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Ok(ScalarValue::List(Arc::new(list_array))) | ||
} | ||
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fn size(&self) -> usize { | ||
std::mem::size_of_val(self) | ||
+ (std::mem::size_of::<ArrayRef>() * self.values.capacity()) | ||
+ self | ||
.values | ||
.iter() | ||
.map(|arr| arr.get_array_memory_size()) | ||
.sum::<usize>() | ||
+ self.datatype.size() | ||
- std::mem::size_of_val(&self.datatype) | ||
} | ||
} | ||
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#[derive(Debug)] | ||
struct DistinctArrayAggAccumulator { | ||
values: HashSet<ScalarValue>, | ||
datatype: DataType, | ||
} | ||
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impl DistinctArrayAggAccumulator { | ||
pub fn try_new(datatype: &DataType) -> Result<Self> { | ||
Ok(Self { | ||
values: HashSet::new(), | ||
datatype: datatype.clone(), | ||
}) | ||
} | ||
} | ||
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impl Accumulator for DistinctArrayAggAccumulator { | ||
fn state(&mut self) -> Result<Vec<ScalarValue>> { | ||
Ok(vec![self.evaluate()?]) | ||
} | ||
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fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> { | ||
if values.len() != 1 { | ||
return internal_err!("expects single batch"); | ||
} | ||
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let array = &values[0]; | ||
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for i in 0..array.len() { | ||
let scalar = ScalarValue::try_from_array(&array, i)?; | ||
self.values.insert(scalar); | ||
} | ||
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Ok(()) | ||
} | ||
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fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> { | ||
if states.is_empty() { | ||
return Ok(()); | ||
} | ||
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if states.len() != 1 { | ||
return internal_err!("expects single state"); | ||
} | ||
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states[0] | ||
.as_list::<i32>() | ||
.iter() | ||
.flatten() | ||
.try_for_each(|val| self.update_batch(&[val])) | ||
} | ||
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fn evaluate(&mut self) -> Result<ScalarValue> { | ||
let values: Vec<ScalarValue> = self.values.iter().cloned().collect(); | ||
if values.is_empty() { | ||
return Ok(ScalarValue::new_null_list(self.datatype.clone(), true, 1)); | ||
} | ||
let arr = ScalarValue::new_list(&values, &self.datatype, true); | ||
Ok(ScalarValue::List(arr)) | ||
} | ||
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fn size(&self) -> usize { | ||
std::mem::size_of_val(self) + ScalarValue::size_of_hashset(&self.values) | ||
- std::mem::size_of_val(&self.values) | ||
+ self.datatype.size() | ||
- std::mem::size_of_val(&self.datatype) | ||
} | ||
} |
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