kumarUjjawal commented on code in PR #23187: URL: https://github.com/apache/datafusion/pull/23187#discussion_r3556655338
########## 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 { Review Comment: The emitted DictionaryArray uses identity keys (key[i] = i), so output is fully expanded with no value sharing. Could you add a short doc-comment explaining this? ########## 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 { Review Comment: valid_bounds is guarded with assert! which panics. A Dictionary(Int8, Utf8) column with >127 distinct groups would cause a panic in production rather than a graceful error. All other error paths here use Result. converting into_dict to -> Result<ArrayRef> and returning internal_err! on overflow, or checking bounds at intern time so build / take_n stay infallible. ########## 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: a null key in rhs_rows is mapped to sentinel_idx inside dict_values (the batch's values array), and then passed to self.inner.vectorized_equal_to . But the null that was originally appended went through self.inner.append_val(&self.null_array, 0), a null from a different array than this batch's dict_values . Can you confirm that all inner builder implementations (bytes, primitive, etc.) short-circuit on null equality before reading the array content so comparing "null from null_array " vs "null from dict_values [sentinel]" always returns true ? ########## 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. Review Comment: can we use use bit-level null iteration? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
