Rich-T-kid commented on code in PR #23187: URL: https://github.com/apache/datafusion/pull/23187#discussion_r3559452901
########## datafusion/physical-plan/src/aggregates/group_values/multi_group_by/dictionary.rs: ########## @@ -0,0 +1,365 @@ +// 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. + +use crate::aggregates::group_values::multi_group_by::GroupColumn; +use arrow::array::{ + Array, ArrayRef, AsArray, BooleanBufferBuilder, DictionaryArray, PrimitiveArray, +}; +use arrow::datatypes::{ArrowDictionaryKeyType, ArrowNativeType, DataType, Field}; +use datafusion_common::Result; +use std::marker::PhantomData; +use std::sync::Arc; + +/// A [`GroupColumn`] implementation for dictionary arrays. +/// wraps an inner [`GroupColumn`] that stores the dictionary values, and uses a null sentinel for null keys. +pub struct DictionaryGroupValuesColumn<K: ArrowDictionaryKeyType + Send + Sync> { + inner: Box<dyn GroupColumn>, + // unary array used as a null sentinel for dictionary keys that are null + null_array: ArrayRef, + _phantom: PhantomData<K>, +} + +impl<K: ArrowDictionaryKeyType + Send + Sync> DictionaryGroupValuesColumn<K> { + pub fn new(inner: Box<dyn GroupColumn>, field: &Field) -> Self { + let null_array = arrow::array::new_null_array(field.data_type(), 1); + Self { + inner, + null_array, + _phantom: PhantomData, + } + } + + fn into_dict(values: ArrayRef) -> ArrayRef { + let num_values = values.len(); + assert!( + Self::valid_bounds::<K>(num_values), + "Dictionary key type {:?} cannot hold {} values", + K::DATA_TYPE, + num_values + ); + let keys: PrimitiveArray<K> = (0..num_values) + .map(|i| (!values.is_null(i)).then(|| K::Native::usize_as(i))) + .collect(); + Arc::new(DictionaryArray::<K>::new(keys, values)) + } + + /// Returns the index of the first null in `values`, or `None` if there are no nulls. + fn null_sentinel_index(values: &ArrayRef) -> Option<usize> { + (values.null_count() > 0) + .then(|| (0..values.len()).find(|&i| values.is_null(i)).unwrap()) + } + + fn valid_bounds<T: ArrowDictionaryKeyType>(num_values: usize) -> bool { + let max: usize = match T::DATA_TYPE { + DataType::Int8 => i8::MAX as usize, + DataType::Int16 => i16::MAX as usize, + DataType::Int32 => i32::MAX as usize, + DataType::Int64 => i64::MAX as usize, + DataType::UInt8 => u8::MAX as usize, + DataType::UInt16 => u16::MAX as usize, + DataType::UInt32 => u32::MAX as usize, + DataType::UInt64 => usize::MAX, + _ => return false, + }; + num_values == 0 || num_values - 1 <= max + } +} + +impl<K: ArrowDictionaryKeyType + Send + Sync> GroupColumn + for DictionaryGroupValuesColumn<K> +{ + fn equal_to(&self, lhs_row: usize, array: &ArrayRef, rhs_row: usize) -> bool { + let dict = array.as_dictionary::<K>(); + match dict.key(rhs_row) { + None => self.inner.equal_to(lhs_row, &self.null_array, 0), + Some(key) => self.inner.equal_to(lhs_row, dict.values(), key), + } + } + + fn append_val(&mut self, array: &ArrayRef, row: usize) -> Result<()> { + let dict = array.as_dictionary::<K>(); + match dict.key(row) { + None => self.inner.append_val(&self.null_array, 0), + Some(key) => self.inner.append_val(dict.values(), key), + } + } + + fn vectorized_equal_to( + &self, + lhs_rows: &[usize], + array: &ArrayRef, + rhs_rows: &[usize], + equal_to_results: &mut BooleanBufferBuilder, + ) { + let dict = array.as_dictionary::<K>(); + let dict_values = dict.values(); + let dict_keys = dict.keys(); + + if dict_keys.null_count() == 0 { + // Fast path: no nulls in the key array, resolve all indices up front and + // delegate to the inner column's vectorized comparison. + let value_indices: Vec<usize> = rhs_rows + .iter() + .map(|&row_index| dict_keys.value(row_index).as_usize()) + .collect(); + self.inner.vectorized_equal_to( + lhs_rows, + dict_values, + &value_indices, + equal_to_results, + ); + } else if let Some(sentinel) = Self::null_sentinel_index(dict_values) { Review Comment: Yes each of the traits use `nulls_equal_to()` to short-circuit null array checks. `bytes.rs/180` ```rust let exist_null = self.nulls.is_null(lhs_row); let input_null = array.is_null(rhs_row); if let Some(result) = nulls_equal_to(exist_null, input_null) { return result; } ``` `bytes_view.rs/263` ```rust // Check if nulls equal firstly if HAS_NULLS { let exist_null = self.nulls.is_null(lhs_row); let input_null = array.is_null(rhs_row); if let Some(result) = nulls_equal_to(exist_null, input_null) { return result; } } ``` `primitive.rs/154` ```rust // Perf: skip null check (by short circuit) if input is not nullable if NULLABLE { let exist_null = self.nulls.is_null(lhs_row); let input_null = array.is_null(rhs_row); if let Some(result) = nulls_equal_to(exist_null, input_null) { return result; } // Otherwise, we need to check their values } ``` `boolean.rs/51` ```rust if NULLABLE { let exist_null = self.nulls.is_null(lhs_row); let input_null = array.is_null(rhs_row); if let Some(result) = nulls_equal_to(exist_null, input_null) { return result; } } ``` `mod.rs/116` ```rust pub fn nulls_equal_to(lhs_null: bool, rhs_null: bool) -> Option<bool> { match (lhs_null, rhs_null) { (true, true) => Some(true), (false, true) | (true, false) => Some(false), _ => None, } } ``` since we know that `rhs_null` will always be true this function will always return `Some(true/false)` meaning further comparisons never run. -- This is an automated message from the Apache Git Service. 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