michalursa commented on a change in pull request #12067: URL: https://github.com/apache/arrow/pull/12067#discussion_r821419293
########## File path: cpp/src/arrow/compute/exec/bloom_filter_test.cc ########## @@ -0,0 +1,633 @@ +// 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 <gmock/gmock-matchers.h> + +#include <algorithm> +#include <chrono> +#include <condition_variable> +#include <set> +#include <thread> +#include "arrow/compute/exec/bloom_filter.h" +#include "arrow/compute/exec/key_hash.h" +#include "arrow/compute/exec/test_util.h" +#include "arrow/compute/exec/util.h" +#include "arrow/util/bitmap_ops.h" +#include "arrow/util/cpu_info.h" + +namespace arrow { +namespace compute { + +TEST(BloomFilter, Masks) { + BloomFilterMasks masks; + std::vector<int> sum_num_masks_with_same_n_bits(BloomFilterMasks::kMaxBitsSet + 1); + std::vector<int> num_masks_with_same_n_bits(BloomFilterMasks::kMaxBitsSet + 1); + + for (bool with_rotation : {false, true}) { + printf("With bit rotation: %s\n", with_rotation ? "ON" : "OFF"); + + for (int i = 0; i <= BloomFilterMasks::kMaxBitsSet; ++i) { + sum_num_masks_with_same_n_bits[i] = 0; + } + + for (int imask = 0; imask < BloomFilterMasks::kNumMasks; ++imask) { + uint64_t mask = masks.mask(imask); + // Verify that the number of bits set is in the required range + // + ARROW_DCHECK(ARROW_POPCOUNT64(mask) >= BloomFilterMasks::kMinBitsSet && + ARROW_POPCOUNT64(mask) <= BloomFilterMasks::kMaxBitsSet); + + for (int i = 0; i <= BloomFilterMasks::kMaxBitsSet; ++i) { + num_masks_with_same_n_bits[i] = 0; + } + for (int imask2nd = 0; imask2nd < BloomFilterMasks::kNumMasks; ++imask2nd) { + if (imask == imask2nd) { + continue; + } + uint64_t mask_to_compare_to = masks.mask(imask2nd); + for (int bits_to_rotate = 0; bits_to_rotate < (with_rotation ? 64 : 1); + ++bits_to_rotate) { + uint64_t mask_rotated = bits_to_rotate == 0 + ? mask_to_compare_to + : ROTL64(mask_to_compare_to, bits_to_rotate); + ++num_masks_with_same_n_bits[ARROW_POPCOUNT64(mask & mask_rotated)]; + } + } + for (int i = 0; i <= BloomFilterMasks::kMaxBitsSet; ++i) { + sum_num_masks_with_same_n_bits[i] += num_masks_with_same_n_bits[i]; + } + } + + printf( + "Expected fraction of masks with the same N bits as any random " + "mask:\n"); + for (int i = 0; i <= BloomFilterMasks::kMaxBitsSet; ++i) { + printf("%d. %.2f \n", i, + static_cast<float>(sum_num_masks_with_same_n_bits[i]) / + (static_cast<float>(BloomFilterMasks::kNumMasks * + BloomFilterMasks::kNumMasks) * + (with_rotation ? 64 : 1))); + } + printf("\n"); + } +} + +Status BuildBloomFilter(BloomFilterBuildStrategy strategy, size_t num_threads, + int64_t hardware_flags, MemoryPool* pool, int64_t num_rows, + std::function<void(int64_t, int, uint32_t*)> get_hash32_impl, + std::function<void(int64_t, int, uint64_t*)> get_hash64_impl, + BlockedBloomFilter* target, float* build_cost) { + constexpr int batch_size_max = 32 * 1024; + int64_t num_batches = bit_util::CeilDiv(num_rows, batch_size_max); + + // omp_set_num_threads(static_cast<int>(num_threads)); + + auto builder = BloomFilterBuilder::Make(strategy); + + std::vector<std::vector<uint32_t>> thread_local_hashes32; + std::vector<std::vector<uint64_t>> thread_local_hashes64; + thread_local_hashes32.resize(num_threads); + thread_local_hashes64.resize(num_threads); + for (size_t i = 0; i < num_threads; ++i) { + thread_local_hashes32[i].resize(batch_size_max); + thread_local_hashes64[i].resize(batch_size_max); + } + + std::vector<float> build_cost_vector; + int64_t num_repeats = + std::max(static_cast<int64_t>(1), bit_util::CeilDiv(1LL << 27, num_rows)); +#ifndef NDEBUG + num_repeats = 1LL; +#endif + build_cost_vector.resize(num_repeats); + + for (int64_t irepeat = 0; irepeat < num_repeats; ++irepeat) { + auto time0 = std::chrono::high_resolution_clock::now(); + + RETURN_NOT_OK(builder->Begin(num_threads, hardware_flags, pool, num_rows, + bit_util::CeilDiv(num_rows, batch_size_max), target)); + + // #pragma omp parallel for + for (int64_t i = 0; i < builder->num_tasks(); ++i) { + builder->RunInitTask(i); + } + + // #pragma omp parallel for + for (int64_t i = 0; i < num_batches; ++i) { + size_t thread_index = 0; // omp_get_thread_num(); + int batch_size = static_cast<int>( + std::min(num_rows - i * batch_size_max, static_cast<int64_t>(batch_size_max))); + if (target->NumHashBitsUsed() > 32) { + uint64_t* hashes = thread_local_hashes64[thread_index].data(); + get_hash64_impl(i * batch_size_max, batch_size, hashes); + Status status = builder->PushNextBatch(thread_index, batch_size, hashes); + ARROW_DCHECK(status.ok()); + } else { + uint32_t* hashes = thread_local_hashes32[thread_index].data(); + get_hash32_impl(i * batch_size_max, batch_size, hashes); + Status status = builder->PushNextBatch(thread_index, batch_size, hashes); + ARROW_DCHECK(status.ok()); + } + } + + // #pragma omp parallel for + for (int64_t i = 0; i < builder->num_tasks(); ++i) { + builder->RunFinishTask(i); + } + + auto time1 = std::chrono::high_resolution_clock::now(); + auto ns = std::chrono::duration_cast<std::chrono::nanoseconds>(time1 - time0).count(); + + builder->CleanUp(); + + build_cost_vector[irepeat] = static_cast<float>(ns) / static_cast<float>(num_rows); + } + + std::sort(build_cost_vector.begin(), build_cost_vector.end()); + *build_cost = build_cost_vector[build_cost_vector.size() / 2]; + + return Status::OK(); +} + +// FPR (false positives rate) - fraction of false positives relative to the sum +// of false positives and true negatives. +// +// Output FPR and build and probe cost. +// +Status TestBloomSmall(BloomFilterBuildStrategy strategy, int64_t num_build, + int num_build_copies, int dop, bool use_simd, bool enable_prefetch, + float* fpr, float* build_cost, float* probe_cost) { + int64_t hardware_flags = use_simd ? ::arrow::internal::CpuInfo::AVX2 : 0; + + // Generate input keys + // + int64_t num_probe = 4 * num_build; + Random64Bit rnd(/*seed=*/0); + std::vector<uint64_t> unique_keys; + { + std::set<uint64_t> unique_keys_set; + for (int64_t i = 0; i < num_build + num_probe; ++i) { + uint64_t value; + for (;;) { + value = rnd.next(); + if (unique_keys_set.find(value) == unique_keys_set.end()) { + break; + } + } + unique_keys.push_back(value); + unique_keys_set.insert(value); + } + } + + // Generate input hashes + // + std::vector<uint32_t> hashes32; + std::vector<uint64_t> hashes64; + hashes32.resize(unique_keys.size()); + hashes64.resize(unique_keys.size()); + int batch_size_max = 1024; + for (size_t i = 0; i < unique_keys.size(); i += batch_size_max) { + int batch_size = static_cast<int>( + std::min(unique_keys.size() - i, static_cast<size_t>(batch_size_max))); + int key_length = sizeof(uint64_t); + Hashing32::hash_fixed(hardware_flags, /*combine_hashes=*/false, batch_size, + key_length, + reinterpret_cast<const uint8_t*>(unique_keys.data() + i), + hashes32.data() + i, nullptr); + Hashing64::hash_fixed( + /*combine_hashes=*/false, batch_size, key_length, + reinterpret_cast<const uint8_t*>(unique_keys.data() + i), hashes64.data() + i); + } + + MemoryPool* pool = default_memory_pool(); + + // Build the filter + // + BlockedBloomFilter reference; + BlockedBloomFilter bloom; + float build_cost_single_threaded; + + RETURN_NOT_OK(BuildBloomFilter( + BloomFilterBuildStrategy::SINGLE_THREADED, dop, hardware_flags, pool, num_build, + [hashes32](int64_t first_row, int num_rows, uint32_t* output_hashes) { + memcpy(output_hashes, hashes32.data() + first_row, num_rows * sizeof(uint32_t)); + }, + [hashes64](int64_t first_row, int num_rows, uint64_t* output_hashes) { + memcpy(output_hashes, hashes64.data() + first_row, num_rows * sizeof(uint64_t)); + }, + &reference, &build_cost_single_threaded)); + + RETURN_NOT_OK(BuildBloomFilter( + strategy, dop, hardware_flags, pool, num_build * num_build_copies, + [hashes32, num_build](int64_t first_row, int num_rows, uint32_t* output_hashes) { + int64_t first_row_clamped = first_row % num_build; + int64_t num_rows_processed = 0; + while (num_rows_processed < num_rows) { + int64_t num_rows_next = + std::min(static_cast<int64_t>(num_rows) - num_rows_processed, + num_build - first_row_clamped); + memcpy(output_hashes + num_rows_processed, hashes32.data() + first_row_clamped, + num_rows_next * sizeof(uint32_t)); + first_row_clamped = 0; + num_rows_processed += num_rows_next; + } + }, + [hashes64, num_build](int64_t first_row, int num_rows, uint64_t* output_hashes) { + int64_t first_row_clamped = first_row % num_build; + int64_t num_rows_processed = 0; + while (num_rows_processed < num_rows) { + int64_t num_rows_next = + std::min(static_cast<int64_t>(num_rows) - num_rows_processed, + num_build - first_row_clamped); + memcpy(output_hashes + num_rows_processed, hashes64.data() + first_row_clamped, + num_rows_next * sizeof(uint64_t)); + first_row_clamped = 0; + num_rows_processed += num_rows_next; + } + }, + &bloom, build_cost)); + + int log_before = bloom.log_num_blocks(); + + if (num_build_copies > 1) { + reference.Fold(); + bloom.Fold(); + } else { + if (strategy != BloomFilterBuildStrategy::SINGLE_THREADED) { + bool is_same = reference.IsSameAs(&bloom); + printf("%s ", is_same ? "BUILD_CORRECT" : "BUILD_WRONG"); + ARROW_DCHECK(is_same); + } + } + + int log_after = bloom.log_num_blocks(); + + float fraction_of_bits_set = static_cast<float>(bloom.NumBitsSet()) / + static_cast<float>(64LL << bloom.log_num_blocks()); + + printf("log_before = %d log_after = %d percent_bits_set = %.1f ", log_before, log_after, + 100.0f * fraction_of_bits_set); + + // Verify no false negatives + // + bool ok = true; + for (int64_t i = 0; i < num_build; ++i) { + bool found; + if (bloom.NumHashBitsUsed() > 32) { + found = bloom.Find(hashes64[i]); + } else { + found = bloom.Find(hashes32[i]); + } + if (!found) { + ok = false; + ARROW_DCHECK(false); + break; + } + } + printf("%s\n", ok ? "success" : "failure"); + + // Measure FPR and performance + // + std::vector<uint8_t> result_bit_vector; + result_bit_vector.resize(bit_util::BytesForBits(batch_size_max)); + std::atomic<int64_t> num_positives; + num_positives.store(0); + + int64_t num_repeats = 1LL; +#ifdef NDEBUG + num_repeats = std::max(1LL, bit_util::CeilDiv(1000000ULL, num_probe)); +#endif + + auto time0 = std::chrono::high_resolution_clock::now(); + + for (int64_t irepeat = 0; irepeat < num_repeats; ++irepeat) { + for (int64_t i = num_build; i < num_build + num_probe;) { + int batch_size = + static_cast<int>(std::min(static_cast<size_t>(unique_keys.size() - i), + static_cast<size_t>(batch_size_max))); + if (bloom.NumHashBitsUsed() > 32) { + bloom.Find(hardware_flags, batch_size, hashes64.data() + i, + result_bit_vector.data(), enable_prefetch); + } else { + bloom.Find(hardware_flags, batch_size, hashes32.data() + i, + result_bit_vector.data(), enable_prefetch); + } + num_positives += arrow::internal::CountSetBits(result_bit_vector.data(), + /*offset=*/0, batch_size); + i += batch_size; + } + } + auto time1 = std::chrono::high_resolution_clock::now(); + auto ns = std::chrono::duration_cast<std::chrono::nanoseconds>(time1 - time0).count(); + *probe_cost = static_cast<float>(ns) / static_cast<float>(num_probe * num_repeats); + + *fpr = 100.0f * static_cast<float>(num_positives.load()) / + static_cast<float>(num_probe * num_repeats); + + return Status::OK(); Review comment: removed -- This is an automated message from the Apache Git Service. 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