json/tests/benchmarks/README.md

# Benchmarks

Micro-benchmarks for parsing, serialization and the binary formats, written with
[Google Benchmark](https://github.com/google/benchmark). They are not run by CI; see
[When to run them](#when-to-run-them).

## What is measured

| benchmark | what it does |
|---|---|
| `ParseFile`, `ParseString` | parse JSON from a file stream or a string |
| `Accept` | validate JSON from a string (`json::accept`) |
| `ParseIndented` | parse the large files re-indented by 4 spaces, for the lexer's whitespace handling |
| `Dump` | serialize, compact (`-`) and indented (`4`) |
| `ToCbor`, `BinaryToCbor` | write CBOR; `BinaryToCbor` writes binary values of growing size |
| `FromMsgpack` | read MessagePack; unchanged over the years, so its numbers stay comparable across releases |
| `FromBinaryBuffer`, `FromBinaryFile` | read CBOR, MessagePack, UBJSON, BJData and BSON from a buffer or a `FILE*` |
| `FromBinaryShape` | read deeply nested, container-heavy and scalar-heavy documents in every binary format |
| `FromCborChunkedString` | read CBOR strings split into indefinite-length chunks |
| `ViewParse`, `ViewRead` | parse with [`json_document`](https://json.nlohmann.me/features/json_view/) into a new document, or into one that is reused; compare with `ParseString` |
| `ViewParseIndented` | as `ParseIndented`, with a reused `json_document` |
| `ViewAccept` | validate with `json_document::accept`; compare with `Accept` |
| `ViewMaterialize` | convert a parsed `json_document` into a `json` value |
| `ViewDump` | serialize a parsed `json_document`; compare with `Dump` |

The input files are those of [nativejson-benchmark](https://github.com/miloyip/nativejson-benchmark) (`canada`,
`citm_catalog`, `twitter`), a large `jeopardy` file, and number-heavy files (`floats`, `signed_ints`, ...).
`bytes_per_second` counts the bytes read or written: the JSON text when parsing, the output when serializing.

## Requirements

- CMake 3.14 or later, a C++11 compiler, and Ninja for the `make` target.
- Network access on the first configure: CMake downloads Google Benchmark and the
  [test data](https://github.com/nlohmann/json_test_data) into the build directory. To reuse a download of the test
  data, pass `-DJSON_TestDataDirectory=<build directory>/test_files`.
- Google Benchmark is pinned to a release (1.9.5), so that results from different days stay comparable. To update it,
  change `JSON_GOOGLE_BENCHMARK_VERSION` and the archive's `URL_HASH` in `CMakeLists.txt` together.
- The benchmarks include `single_include/nlohmann/json.hpp`, so run `make amalgamate` after changing anything in
  `include/`.

GCC and Clang builds use `-O3 -flto -DNDEBUG`.

## Running them

From the repository root, this builds everything from scratch in `cmake-build-benchmarks` and runs all benchmarks:

```sh
make run_benchmarks
```

To build once and run selectively:

```sh
cmake -S tests/benchmarks -B build-benchmarks -G Ninja -DCMAKE_BUILD_TYPE=Release
cmake --build build-benchmarks
build-benchmarks/json_benchmarks --benchmark_filter='ParseString|Dump'
```

Useful options of `json_benchmarks`:

| option | effect |
|---|---|
| `--benchmark_list_tests` | list the benchmarks instead of running them |
| `--benchmark_filter=<regex>` | run only the benchmarks whose names match |
| `--benchmark_repetitions=<n>` | run every benchmark `n` times and add mean, median, standard deviation and coefficient of variation |
| `--benchmark_enable_random_interleaving=true` | run the repetitions in random order, which spreads out drifts such as thermal throttling |
| `--benchmark_min_time=<seconds>s` | run each benchmark at least this long (e.g. `2s`) |
| `--benchmark_out=<file> --benchmark_out_format=json` | also write the results to a file, e.g. for `compare.py` |

## Reading the output

Each line shows the wall-clock `Time` and the `CPU` time per iteration, the number of `Iterations` Google Benchmark
chose, and the throughput in `bytes_per_second`. With repetitions, the lines ending in `_median` are the ones to
compare. A `_cv` (coefficient of variation) above a few percent means the machine was too noisy for small
differences to mean anything.

## Comparing two versions

To see what a change or a release did, build the same benchmarks twice: once against the header of the version to
compare with, and once against the current one. `JSON_BENCHMARK_INCLUDE_DIR` names the directory holding the
`nlohmann/json.hpp` to benchmark. For example, to compare the current checkout with 3.12.0:

```sh
# the header of the version to compare with
mkdir -p build-baseline-header/nlohmann
git show v3.12.0:single_include/nlohmann/json.hpp > build-baseline-header/nlohmann/json.hpp

# the same benchmarks, built against either header
cmake -S tests/benchmarks -B build-baseline -G Ninja -DCMAKE_BUILD_TYPE=Release \
      -DJSON_BENCHMARK_INCLUDE_DIR="$PWD/build-baseline-header"
cmake -S tests/benchmarks -B build-current -G Ninja -DCMAKE_BUILD_TYPE=Release
cmake --build build-baseline
cmake --build build-current

# run both, back to back
build-baseline/json_benchmarks --benchmark_repetitions=10 --benchmark_enable_random_interleaving=true \
                               --benchmark_out=build-baseline/results.json --benchmark_out_format=json
build-current/json_benchmarks --benchmark_repetitions=10 --benchmark_enable_random_interleaving=true \
                              --benchmark_out=build-current/results.json --benchmark_out_format=json
```

Google Benchmark ships a tool to compare the two result files. It needs NumPy and SciPy:

```sh
python3 -m venv build-venv
build-venv/bin/pip install numpy scipy
build-venv/bin/python build-current/_deps/benchmark-src/tools/compare.py -a benchmarks build-baseline/results.json build-current/results.json
```

The tool's own `tools/requirements.txt` pins NumPy and SciPy versions that need Python 3.11 or later; with an older
Python, unpinned versions work as well. In its output:

- the `Time` and `CPU` columns are relative changes: `-0.35` means 35% faster, `+0.10` means 10% slower;
- `_pvalue` lines report a Mann-Whitney U test of whether the two versions differ. It needs at least 9
  repetitions, and a p-value below 0.05 means the difference is unlikely to be noise;
- `OVERALL_GEOMEAN` summarizes all benchmarks;
- `-a` shows only the aggregates, not every repetition.

The header you compare with must support everything the benchmarks use. The current benchmarks build against 3.12.0;
the `View*` benchmarks (in `src/benchmarks_view.cpp`) are only built if the directory also holds
`nlohmann/json_view.hpp`.
Only benchmarks present in both result files are compared, so for older releases, either filter the benchmarks or
build that release's own `tests/benchmarks` against its own header.

## Getting stable numbers

- Build and run both versions on the same machine, one right after the other.
- Keep the machine otherwise idle: no builds, no browser, and a laptop plugged in.
- On Linux, set the CPU frequency governor to `performance`, e.g. `sudo cpupower frequency-set --governor performance`.
  Google Benchmark prints a warning when frequency scaling is enabled. Pinning the process to a core
  (`taskset -c 2 ...`) helps as well.
- Use 10 or more repetitions with random interleaving, compare medians, and treat changes within the `_cv` as noise.

## When to run them

They are a manual step, not part of CI: shared CI runners vary more between runs than most of the effects measured.
Run the comparison above before a release, comparing the previous release tag with `develop`, and for pull requests
that claim to change performance.