Rich-T-kid commented on code in PR #21765: URL: https://github.com/apache/datafusion/pull/21765#discussion_r3455196070
########## datafusion/physical-plan/src/aggregates/group_values/single_group_by/dictionary.rs: ########## @@ -0,0 +1,1003 @@ +// 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::GroupValues; +use crate::hash_utils::RandomState; +use arrow::array::{ + Array, ArrayRef, AsArray, DictionaryArray, LargeStringArray, LargeStringBuilder, + ListArray, ListBuilder, PrimitiveArray, PrimitiveBuilder, StringArray, StringBuilder, + StringViewArray, StringViewBuilder, +}; +use arrow::datatypes::{ArrowDictionaryKeyType, ArrowNativeType, DataType}; +use datafusion_common::DataFusionError::{Internal, NotImplemented}; +use datafusion_common::Result; +use datafusion_common::hash_utils::create_hashes; +use datafusion_expr::EmitTo; +use hashbrown::HashTable; +use std::borrow::Cow; +use std::marker::PhantomData; +use std::sync::Arc; + +/// Heuristic for sizing the values buffer of string builders during emit: +/// dictionary-encoded values are short by design (categorical strings, short +/// identifiers), so 16 B/item avoids the realloc-doubling chain in the common +/// case while keeping over-allocation cheap when values are smaller. +const AVG_BYTES_PER_DICT_VALUE: usize = 16; + +macro_rules! decode_list { + ($raw:expr, $builder:expr) => {{ + let mut builder = $builder; + for raw_bytes in $raw { + match raw_bytes { + None => builder.append_null(), + Some(raw_vector) => { + let mut offset = 0; + while offset < raw_vector.len() { + let len = i64::from_ne_bytes( + raw_vector[offset..offset + 8] + .try_into() + .expect("slice of length 8"), + ); + offset += 8; + if len == -1 { + builder.values().append_null(); + } else { + let s = unsafe { + std::str::from_utf8_unchecked( + &raw_vector[offset..offset + len as usize], + ) + }; + builder.values().append_value(s); + offset += len as usize; + } + } + builder.append(true); + } + } + } + Ok(Arc::new(builder.finish()) as ArrayRef) + }}; +} +macro_rules! decode_scalar_string { + ($raw:expr, $builder:expr) => {{ + let mut builder = $builder; + for raw_bytes in $raw { + match raw_bytes { + Some(raw_vector) => { + let s = unsafe { std::str::from_utf8_unchecked(raw_vector) }; + builder.append_value(s); + } + None => builder.append_null(), + } + } + Ok(Arc::new(builder.finish()) as ArrayRef) + }}; +} +struct DictEntry { + hash: u64, + group_id: usize, + offset: usize, + len: usize, +} + +pub struct GroupValuesDictionary<K: ArrowDictionaryKeyType + Send> { + /// Packed byte storage for all group values. + row_buffer: Vec<u8>, + /// `row_offsets[g]` = start of group `g` in `row_buffer`; + row_offsets: Vec<usize>, + value_dt: DataType, + _phantom: PhantomData<K>, + // keeps track of which values weve already seen, keyed by raw value hash. + unique_dict_value_mapping: HashTable<DictEntry>, + + random_state: RandomState, + + // cache the group id for nulls since they all map to the same group + null_group_id: Option<usize>, + // key to group vector scratch space, used to avoid re-allocating a new vector on each call to intern + key_to_group: Vec<Option<usize>>, + // 0. cache pointer of arrays, this avoids having to re-compute hashing for arrays weve already seen on past iterations + // 1. avoid re-allocating buffer inbetween calls, instead of allocating a new vector each time re-use inbetween calls + values_cache: (Option<ArrayRef>, Vec<u64>), +} + +impl<K: ArrowDictionaryKeyType + Send> GroupValuesDictionary<K> { + pub fn new(data_type: &DataType) -> Self { + Self { + row_buffer: Vec::new(), + row_offsets: Vec::new(), + unique_dict_value_mapping: HashTable::new(), + value_dt: data_type.clone(), + _phantom: PhantomData, + random_state: RandomState::with_seed(0), + null_group_id: None, + key_to_group: Vec::new(), + values_cache: (None, Vec::new()), + } + } + + fn lookup_or_insert_in_table(&mut self, hash: u64, raw: &[u8]) -> usize { + let row_buffer = &self.row_buffer; + if let Some(e) = self.unique_dict_value_mapping.find(hash, |e| { + e.hash == hash && &row_buffer[e.offset..e.offset + e.len] == raw + }) { + return e.group_id; + } + let new_group_id = self.row_offsets.len(); + let offset = self.row_buffer.len(); + self.row_offsets.push(offset); + self.row_buffer.extend_from_slice(raw); + self.unique_dict_value_mapping.insert_unique( + hash, + DictEntry { + hash, + group_id: new_group_id, + offset, + len: raw.len(), + }, + |e| e.hash, + ); + new_group_id + } + fn compute_value_hashes(&mut self, values: &ArrayRef) -> Result<()> { + self.values_cache.1.clear(); + self.values_cache.1.resize(values.len(), 0); + create_hashes( + [Arc::clone(values)], + &self.random_state, + &mut self.values_cache.1, + )?; + Ok(()) + //Ok(hashes) + } + + fn get_raw_bytes(values: &ArrayRef, index: usize) -> Cow<'_, [u8]> { + match values.data_type() { + DataType::Utf8 => Cow::Borrowed( + values + .as_any() + .downcast_ref::<StringArray>() + .expect("Expected StringArray") + .value(index) + .as_bytes(), + ), + DataType::LargeUtf8 => Cow::Borrowed( + values + .as_any() + .downcast_ref::<LargeStringArray>() + .expect("Expected LargeStringArray") + .value(index) + .as_bytes(), + ), + DataType::Utf8View => Cow::Borrowed( + values + .as_any() + .downcast_ref::<StringViewArray>() + .expect("Expected StringViewArray") + .value(index) + .as_bytes(), + ), + DataType::List(_) => { + let list_array = values + .as_any() + .downcast_ref::<ListArray>() + .expect("Expected ListArray"); + + debug_assert!(!list_array.is_null(index)); + + let start = list_array.value_offsets()[index] as usize; + let end = list_array.value_offsets()[index + 1] as usize; + let child = list_array.values(); + + let mut bytes = Vec::new(); + for i in start..end { + if child.is_null(i) { + // acts as a marker for transform_into_array to write a null + bytes.extend_from_slice(&(-1i64).to_ne_bytes()); + } else { + let raw = Self::get_raw_bytes(child, i); + bytes.extend_from_slice(&(raw.len() as i64).to_ne_bytes()); + bytes.extend_from_slice(&raw); + } + } + Cow::Owned(bytes) + } + other => unimplemented!("get_raw_bytes not implemented for {other:?}"), + } + } + + #[inline] + fn get_null_group_id(&mut self) -> usize { + if let Some(group_id) = self.null_group_id { + group_id + } else { + let new_group_id = self.row_offsets.len(); + self.row_offsets.push(self.row_buffer.len()); // null: empty span + self.null_group_id = Some(new_group_id); + new_group_id + } + } + + fn transform_into_array( + &self, + n: usize, + null_group_id: Option<usize>, + ) -> Result<ArrayRef> { + let data_capacity = n * AVG_BYTES_PER_DICT_VALUE; + let raw = (0..n).map(|i| { + if Some(i) == null_group_id { + return None; + } + let start = self.row_offsets[i]; + // last group has no i+1 entry; its end is the buffer tail. + let end = self + .row_offsets + .get(i + 1) + .copied() + .unwrap_or(self.row_buffer.len()); + Some(&self.row_buffer[start..end]) + }); + match &self.value_dt { Review Comment: I touched on this in the above comment but there are properties of single-column dictionary group bys that multi-column group bys can't practically take advantage of: **null handling**: in a single-column group by, all nulls map to the same group id. This avoids the combinatorial null space that emerges with multiple columns -- (null, _, _), (_, null, _), (_, _, null), etc. In the singular case we can store the null group id directly and look it up with no hashing, a meaningful win for data with a high null percentage. **arc pointer identity cache**: consecutive batches of the same dictionary column often share the same underlying Arc buffer; a pointer equality check lets us skip re-hashing the values buffer entirely across batches. **group id precomputation**: group ids can be computed once per unique dictionary key and stored in a flat lookup table, avoiding per-row hashing. In the multi-column case the number of possible key combinations grows multiplicatively -- two columns with cardinalities 100 and 200 produce up to 20,000 combinations, making this impractical. -- 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. 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