wgtmac commented on code in PR #37400: URL: https://github.com/apache/arrow/pull/37400#discussion_r2689729579
########## cpp/src/parquet/bloom_filter_writer.cc: ########## @@ -0,0 +1,264 @@ +// 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. + +#include "parquet/bloom_filter_writer.h" + +#include <map> +#include <utility> + +#include "arrow/array.h" +#include "arrow/io/interfaces.h" +#include "arrow/type_traits.h" +#include "arrow/util/bit_run_reader.h" +#include "arrow/util/checked_cast.h" + +#include "parquet/exception.h" +#include "parquet/metadata.h" +#include "parquet/properties.h" +#include "parquet/schema.h" +#include "parquet/types.h" + +namespace parquet { + +constexpr int64_t kHashBatchSize = 256; + +template <typename ParquetType> +TypedBloomFilterWriter<ParquetType>::TypedBloomFilterWriter(const ColumnDescriptor* descr, + BloomFilter* bloom_filter) + : descr_(descr), bloom_filter_(bloom_filter) {} + +template <typename ParquetType> +void TypedBloomFilterWriter<ParquetType>::Update(const T* values, int64_t num_values) { + ARROW_DCHECK(bloom_filter_ != nullptr); + std::array<uint64_t, kHashBatchSize> hashes; + for (int64_t i = 0; i < num_values; i += kHashBatchSize) { + auto batch_size = static_cast<int>(std::min(kHashBatchSize, num_values - i)); + if constexpr (std::is_same_v<ParquetType, FLBAType>) { + bloom_filter_->Hashes(values + i, descr_->type_length(), batch_size, hashes.data()); + } else { + bloom_filter_->Hashes(values + i, batch_size, hashes.data()); + } + bloom_filter_->InsertHashes(hashes.data(), batch_size); + } +} + +template <> +void TypedBloomFilterWriter<BooleanType>::Update(const bool*, int64_t) { + throw ParquetException("Bloom filter is not supported for boolean type"); +} + +template <typename ParquetType> +void TypedBloomFilterWriter<ParquetType>::UpdateSpaced(const T* values, + int64_t num_values, + const uint8_t* valid_bits, + int64_t valid_bits_offset) { + ARROW_DCHECK(bloom_filter_ != nullptr); + std::array<uint64_t, kHashBatchSize> hashes; + ::arrow::internal::VisitSetBitRunsVoid( + valid_bits, valid_bits_offset, num_values, [&](int64_t position, int64_t length) { + for (int64_t i = 0; i < length; i += kHashBatchSize) { + auto batch_size = static_cast<int>(std::min(kHashBatchSize, length - i)); + if constexpr (std::is_same_v<ParquetType, FLBAType>) { + bloom_filter_->Hashes(values + i + position, descr_->type_length(), + batch_size, hashes.data()); + } else { + bloom_filter_->Hashes(values + i + position, batch_size, hashes.data()); + } + bloom_filter_->InsertHashes(hashes.data(), batch_size); + } + }); +} + +template <> +void TypedBloomFilterWriter<BooleanType>::UpdateSpaced(const bool*, int64_t, + const uint8_t*, int64_t) { + throw ParquetException("Bloom filter is not supported for boolean type"); +} + +template <typename ParquetType> +void TypedBloomFilterWriter<ParquetType>::Update(const ::arrow::Array& values) { + ParquetException::NYI("Updating bloom filter is not implemented for array of type: " + + values.type()->ToString()); +} + +namespace { + +template <typename ArrayType> +void UpdateBinaryBloomFilter(BloomFilter& bloom_filter, const ArrayType& array) { + std::array<ByteArray, kHashBatchSize> byte_arrays; + std::array<uint64_t, kHashBatchSize> hashes; + ::arrow::internal::VisitSetBitRunsVoid( + array.null_bitmap_data(), array.offset(), array.length(), + [&](int64_t position, int64_t length) { + for (int64_t i = 0; i < length; i += kHashBatchSize) { + auto batch_size = static_cast<int>(std::min(kHashBatchSize, length - i)); + for (int j = 0; j < batch_size; j++) { + byte_arrays[j] = array.GetView(position + i + j); + } + bloom_filter.Hashes(byte_arrays.data(), batch_size, hashes.data()); + bloom_filter.InsertHashes(hashes.data(), batch_size); + } + }); +} + +} // namespace + +template <> +void TypedBloomFilterWriter<ByteArrayType>::Update(const ::arrow::Array& values) { + ARROW_DCHECK(bloom_filter_ != nullptr); + if (::arrow::is_binary_view_like(values.type_id())) { + UpdateBinaryBloomFilter( + *bloom_filter_, + ::arrow::internal::checked_cast<const ::arrow::BinaryViewArray&>(values)); + } else if (::arrow::is_binary_like(values.type_id())) { + UpdateBinaryBloomFilter( + *bloom_filter_, + ::arrow::internal::checked_cast<const ::arrow::BinaryArray&>(values)); + } else if (::arrow::is_large_binary_like(values.type_id())) { + UpdateBinaryBloomFilter( + *bloom_filter_, + ::arrow::internal::checked_cast<const ::arrow::LargeBinaryArray&>(values)); + } else { + ParquetException::NYI("Bloom filter is not supported for this Arrow type: " + + values.type()->ToString()); + } +} + +template class TypedBloomFilterWriter<BooleanType>; +template class TypedBloomFilterWriter<Int32Type>; +template class TypedBloomFilterWriter<Int64Type>; +template class TypedBloomFilterWriter<Int96Type>; +template class TypedBloomFilterWriter<FloatType>; +template class TypedBloomFilterWriter<DoubleType>; +template class TypedBloomFilterWriter<ByteArrayType>; +template class TypedBloomFilterWriter<FLBAType>; + +namespace { + +/// \brief A concrete implementation of BloomFilterBuilder. +/// +/// \note Column encryption for bloom filter is not implemented yet. +class BloomFilterBuilderImpl : public BloomFilterBuilder { + public: + BloomFilterBuilderImpl(const SchemaDescriptor* schema, + const WriterProperties* properties) + : schema_(schema), properties_(properties) {} + + void AppendRowGroup() override; + + BloomFilter* CreateBloomFilter(int32_t column_ordinal) override; + + IndexLocations WriteTo(::arrow::io::OutputStream* sink) override; + + private: + /// Make sure column ordinal is not out of bound and the builder is in good state. + void CheckState(int32_t column_ordinal) const { + if (finished_) { + throw ParquetException("BloomFilterBuilder is already finished."); + } + if (bloom_filters_.empty()) { + throw ParquetException("No row group appended to BloomFilterBuilder"); + } + if (column_ordinal < 0 || column_ordinal >= schema_->num_columns()) { + throw ParquetException("Invalid column ordinal: " + std::to_string(column_ordinal)); + } + if (schema_->Column(column_ordinal)->physical_type() == Type::BOOLEAN) { + throw ParquetException("BloomFilterBuilder does not support boolean type."); + } + } + + const SchemaDescriptor* schema_; + const WriterProperties* properties_; + bool finished_ = false; + + using RowGroupBloomFilters = + std::map</*column_id=*/int32_t, std::shared_ptr<BloomFilter>>; + std::vector<RowGroupBloomFilters> bloom_filters_; // indexed by row group ordinal +}; + +void BloomFilterBuilderImpl::AppendRowGroup() { + if (finished_) { + throw ParquetException( + "Cannot append a new row group to a finished BloomFilterBuilder"); + } + bloom_filters_.emplace_back(); +} + +BloomFilter* BloomFilterBuilderImpl::CreateBloomFilter(int32_t column_ordinal) { + CheckState(column_ordinal); + + auto opts = properties_->bloom_filter_options(schema_->Column(column_ordinal)->path()); + if (!opts.has_value()) { + return nullptr; + } + + auto& curr_rg_bfs = *bloom_filters_.rbegin(); + if (curr_rg_bfs.find(column_ordinal) != curr_rg_bfs.cend()) { + std::stringstream ss; + ss << "Bloom filter already exists for column: " << column_ordinal + << ", row group: " << (bloom_filters_.size() - 1); + throw ParquetException(ss.str()); + } + + auto bf = std::make_unique<BlockSplitBloomFilter>(properties_->memory_pool()); + bf->Init(BlockSplitBloomFilter::OptimalNumOfBytes(opts->ndv, opts->fpp)); + return curr_rg_bfs.emplace(column_ordinal, std::move(bf)).first->second.get(); +} + +IndexLocations BloomFilterBuilderImpl::WriteTo(::arrow::io::OutputStream* sink) { + if (finished_) { + throw ParquetException("Cannot write a finished BloomFilterBuilder"); + } + finished_ = true; + + IndexLocations locations; + + for (size_t i = 0; i != bloom_filters_.size(); ++i) { + auto& row_group_bloom_filters = bloom_filters_[i]; + for (const auto& [column_id, filter] : row_group_bloom_filters) { + if (ARROW_PREDICT_FALSE(filter == nullptr)) { + throw ParquetException("Bloom filter cannot be null"); + } Review Comment: It shouldn't happen. Let me remove it. ########## cpp/src/parquet/properties.h: ########## @@ -169,6 +169,37 @@ static constexpr bool DEFAULT_IS_PAGE_INDEX_ENABLED = true; static constexpr SizeStatisticsLevel DEFAULT_SIZE_STATISTICS_LEVEL = SizeStatisticsLevel::PageAndColumnChunk; +struct PARQUET_EXPORT BloomFilterOptions { + /// Expected number of distinct values (NDV) in the bloom filter. + /// + /// Bloom filters are most effective for high-cardinality columns. A good default + /// is to set ndv equal to the number of rows. Lower values reduce disk usage but + /// may not be worthwhile for very small NDVs. + /// + /// Increasing ndv (without increasing fpp) increases disk and memory usage. + int32_t ndv = 1 << 20; + + /// False-positive probability (FPP) of the bloom filter. + /// + /// Lower FPP values require more disk and memory space. Recommended values are Review Comment: Added -- This is an automated message from the Apache Git Service. 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