| 36 | #ifdef ARROW_WITH_BENCHMARKS_REFERENCE |
| 37 | |
| 38 | std::vector<uint8_t> MakeCompressibleData(int data_size) { |
| 39 | // XXX This isn't a real-world corpus so doesn't really represent the |
| 40 | // comparative qualities of the algorithms |
| 41 | |
| 42 | // First make highly compressible data |
| 43 | std::string base_data = |
| 44 | "Apache Arrow is a cross-language development platform for in-memory data"; |
| 45 | int nrepeats = static_cast<int>(1 + data_size / base_data.size()); |
| 46 | |
| 47 | std::vector<uint8_t> data(base_data.size() * nrepeats); |
| 48 | for (int i = 0; i < nrepeats; ++i) { |
| 49 | std::memcpy(data.data() + i * base_data.size(), base_data.data(), base_data.size()); |
| 50 | } |
| 51 | data.resize(data_size); |
| 52 | |
| 53 | // Then randomly mutate some bytes so as to make things harder |
| 54 | std::mt19937 engine(42); |
| 55 | std::exponential_distribution<> offsets(0.05); |
| 56 | std::uniform_int_distribution<> values(0, 255); |
| 57 | |
| 58 | int64_t pos = 0; |
| 59 | while (pos < data_size) { |
| 60 | data[pos] = static_cast<uint8_t>(values(engine)); |
| 61 | pos += static_cast<int64_t>(offsets(engine)); |
| 62 | } |
| 63 | |
| 64 | return data; |
| 65 | } |
| 66 | |
| 67 | int64_t StreamingCompress(Codec* codec, const std::vector<uint8_t>& data, |
| 68 | std::vector<uint8_t>* compressed_data = nullptr) { |
no test coverage detected