michalursa commented on a change in pull request #12067: URL: https://github.com/apache/arrow/pull/12067#discussion_r826473427
########## File path: cpp/src/arrow/compute/exec/vector_hash_test.cc ########## @@ -0,0 +1,234 @@ +// 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 <chrono> +#include <map> +#include <set> +#include "arrow/compute/exec/key_hash.h" +#include "arrow/compute/exec/test_util.h" +#include "arrow/compute/exec/util.h" +#include "arrow/util/cpu_info.h" + +namespace arrow { +namespace compute { + +void TestVectorHashImp(Random64Bit& random, bool use_32bit_hash, bool use_varlen_input, + int min_length, int max_length) { + ARROW_DCHECK(use_varlen_input || min_length == max_length); + + constexpr int min_num_unique = 100; + constexpr int max_num_unique = 1000; + constexpr int min_num_rows = 4000; + constexpr int max_num_rows = 64000; + int num_unique = + min_num_unique + (random.next() % (max_num_unique - min_num_unique + 1)); + int num_rows = min_num_rows + (random.next() % (max_num_rows - min_num_rows + 1)); + + SCOPED_TRACE("num_bits = " + std::to_string(use_32bit_hash ? 32 : 64) + + " varlen = " + std::string(use_varlen_input ? "yes" : "no") + + " num_unique " + std::to_string(num_unique) + " num_rows " + + std::to_string(num_rows) + " min_length " + std::to_string(min_length) + + " max_length " + std::to_string(max_length)); + + if (max_length == 1) { + num_unique &= 0x7f; + } + + std::vector<uint32_t> unique_keys_offsets; + unique_keys_offsets.resize(num_unique + 1); + unique_keys_offsets[0] = 0; + + const int num_bytes = unique_keys_offsets[num_unique]; + std::vector<uint8_t> unique_keys; + unique_keys.resize(num_bytes); + std::set<std::string> unique_key_strings; + for (int i = 0; i < num_unique; ++i) { + for (;;) { + int next_length; + if (use_varlen_input) { + next_length = min_length + random.next() % (max_length - min_length + 1); + } else { + next_length = max_length; + } + unique_keys_offsets[i + 1] = unique_keys_offsets[i] + next_length; + unique_keys.resize(unique_keys_offsets[i + 1]); + uint8_t* next_key = unique_keys.data() + unique_keys_offsets[i]; + + for (int iword = 0; iword < next_length / static_cast<int>(sizeof(uint64_t)); + ++iword) { + reinterpret_cast<uint64_t*>(next_key)[iword] = random.next(); + } + if (next_length % sizeof(uint64_t) > 0) { + uint8_t* tail = next_key + next_length - (next_length % sizeof(uint64_t)); + for (int ibyte = 0; ibyte < (next_length % static_cast<int>(sizeof(uint64_t))); + ++ibyte) { + tail[ibyte] = static_cast<uint8_t>(random.next() & 0xff); + } + } + std::string next_key_string = + std::string(reinterpret_cast<const char*>(next_key), next_length); + if (unique_key_strings.find(next_key_string) == unique_key_strings.end()) { + unique_key_strings.insert(next_key_string); + break; + } + } + } + + std::vector<int> row_ids; + row_ids.resize(num_rows); + std::vector<uint8_t> keys; + std::vector<uint32_t> keys_offsets; + keys_offsets.resize(num_rows + 1); + keys_offsets[0] = 0; + for (int i = 0; i < num_rows; ++i) { + int row_id = random.next() % num_unique; + row_ids[i] = row_id; + int next_length = unique_keys_offsets[row_id + 1] - unique_keys_offsets[row_id]; + keys_offsets[i + 1] = keys_offsets[i] + next_length; + } + keys.resize(keys_offsets[num_rows]); + for (int i = 0; i < num_rows; ++i) { + int row_id = row_ids[i]; + int next_length = keys_offsets[i + 1] - keys_offsets[i]; + memcpy(keys.data() + keys_offsets[i], + unique_keys.data() + unique_keys_offsets[row_id], next_length); + } + + constexpr int min_rows_for_timing = 1 << 23; + int num_repeats = static_cast<int>(bit_util::CeilDiv(min_rows_for_timing, num_rows)); +#ifndef NDEBUG + num_repeats = 1; +#endif + + std::vector<uint32_t> hashes_scalar32; + std::vector<uint64_t> hashes_scalar64; + hashes_scalar32.resize(num_rows); + hashes_scalar64.resize(num_rows); + std::vector<uint32_t> hashes_simd32; + std::vector<uint64_t> hashes_simd64; + hashes_simd32.resize(num_rows); + hashes_simd64.resize(num_rows); + + int64_t hardware_flags_scalar = 0LL; + int64_t hardware_flags_simd = ::arrow::internal::CpuInfo::AVX2; + + constexpr int mini_batch_size = 1024; + std::vector<uint32_t> temp_buffer; + temp_buffer.resize(mini_batch_size * 4); + + for (bool use_simd : {false, true}) { + for (int i = 0; i < num_repeats; ++i) { + if (use_32bit_hash) { + if (!use_varlen_input) { + Hashing32::hash_fixed(use_simd ? hardware_flags_simd : hardware_flags_scalar, + /*combine_hashes=*/false, num_rows, max_length, + keys.data(), + use_simd ? hashes_simd32.data() : hashes_scalar32.data(), + temp_buffer.data()); + } else { + for (int first_row = 0; first_row < num_rows;) { + int batch_size_next = std::min(num_rows - first_row, mini_batch_size); + + Hashing32::hash_varlen( + use_simd ? hardware_flags_simd : hardware_flags_scalar, + /*combine_hashes=*/false, batch_size_next, + keys_offsets.data() + first_row, keys.data(), + (use_simd ? hashes_simd32.data() : hashes_scalar32.data()) + first_row, + temp_buffer.data()); + + first_row += batch_size_next; + } + } + } else { + if (!use_varlen_input) { + Hashing64::hash_fixed(/*combine_hashes=*/false, num_rows, max_length, + keys.data(), + use_simd ? hashes_simd64.data() : hashes_scalar64.data()); + } else { + Hashing64::hash_varlen( + /*combine_hashes=*/false, num_rows, keys_offsets.data(), keys.data(), + use_simd ? hashes_simd64.data() : hashes_scalar64.data()); + } + } + } + } + if (use_32bit_hash) { + for (int i = 0; i < num_rows; ++i) { + hashes_scalar64[i] = hashes_scalar32[i]; + hashes_simd64[i] = hashes_simd32[i]; + } + } + + // Verify that both scalar and AVX2 implementations give the same hashes + // + for (int i = 0; i < num_rows; ++i) { + if (hashes_scalar64[i] != hashes_simd64[i]) { + ARROW_DCHECK(false); + } + } + + // Verify that the same key appearing multiple times generates the same hash + // each time. Measure the number of unique hashes and compare to the number + // of unique keys. + // + std::map<int, uint64_t> unique_key_to_hash; + std::set<uint64_t> unique_hashes; + for (int i = 0; i < num_rows; ++i) { + std::map<int, uint64_t>::iterator iter = unique_key_to_hash.find(row_ids[i]); + if (iter == unique_key_to_hash.end()) { + unique_key_to_hash.insert(std::make_pair(row_ids[i], hashes_scalar64[i])); + } else { + ARROW_DCHECK(iter->second == hashes_scalar64[i]); + } + if (unique_hashes.find(hashes_scalar64[i]) == unique_hashes.end()) { + unique_hashes.insert(hashes_scalar64[i]); + } + } + float percent_hash_collisions = 100.0f * + static_cast<float>(num_unique - unique_hashes.size()) / + static_cast<float>(num_unique); + SCOPED_TRACE("percent_hash_collisions " + std::to_string(percent_hash_collisions)); + ARROW_DCHECK(percent_hash_collisions < 5.0f); +} + +TEST(VectorHash, Basic) { + Random64Bit random(/*seed=*/0); + + int numtest = 100; Review comment: This is not the number of repeats for a single test but the number of different randomly generated inputs. 10 randomly generated inputs will not produce enough variety for testing. Also, this test should be fairly fast compared to for instance hash group by or hash join tests, so trying to save execution time by reducing the number of test cases won't help much with having faster test runs. -- 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: github-unsubscr...@arrow.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
