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Benchmarks

This section compares the performance of Boost.JSON with two widely used libraries with similar functionality: RapidJSON which is known for its performance, and JSON for Modern C++ which is known for feature-richness. The bench program measures the throughput of parsing and serialization for the a set of JSON representing typical workloads. These implementations are evaluated:

Table 1.10. Implementations

Name

Description

boost(pool)

Parses the input using a monotonic_resource, which is optimized for parsing without subsequent modification. The stream_parser object is reused between trials, allowing temporary memory allocated by the implementation to persist and improve performance.

boost

Parses the input using the default memory resource, which uses the standard C++ allocator, and is designed for general use including mutation of the document after it is parsed. The stream_parser object is reused between trials, allowing temporary memory allocated by the implementation to persist and improve performance.

rapidjson(pool)

Parses the input using an instance of MemoryPoolAllocator, which is optimized for parsing without subsequent modification. The Document object holding temporary memory is not reused between trials, otherwise memory consumption grows without bounds and invalidates the benchmark.

rapidjson

Parses the input using an instance of CrtAllocator, which uses the standard C++ allocator, and is designed for general use including mutation of the document after it is parsed. The Document object holding temporary memory is not reused between trials, otherwise memory consumption grows without bounds and invalidates the benchmark.

nlohmann

Parses the input using the static member function json::parse, which uses the default std allocator, and is designed for general use including mutation of the document after it is parsed. This library does not provide an interface to reuse temporary storage used during parsing or serialization on subsequent operations.


Methodology

The input files are all loaded first. Then each configuration is run for a sufficient number of trials to last at least 5 seconds. The elapsed time, number of invocations (of parse or serialize), and bytes transferred are emitted as a sample along with a calculation of throughput expressed in megabytes per second. Several samples (currently five) are generated for each configuration. All but the median two samples are discarded, with the remaining samples averaged to produce a single number which is reported as the benchmark result.

The input files, available in the bench/data directory, are laid out thusly:

Table 1.11. Input Files

Name

Size

Description

apache_builds.json

125KB

Data from the Apache Jenkins installation.

canada.json

2.2MB

The largest file, containing a large number of 2-element arrays holding floating-point coordinate pairs.

citm_catalog.json

1.69MB

A large JSON with a variety of nesting, types, and lengths.

github_events.json

64KB

An export of data from the Github Events API.

gsoc-2018.json

3.25MB

Google Summer of Code 2018 data.

instruments.json

216KB

An array of large objects.

marine_ik.json

2.91MB

A three.js example model serialized to JSON.

mesh.json

707KB

A JSON representing a 3D mesh. Contains many floating-point numbers.

mesh.pretty.json

1.54MB

mesh.json with whitespace added.

numbers.json

147KB

A array containing only floating-point numbers.

random.json

499KB

A JSON with lots of Cyrillic characters.

twitter.json

617KB

An export of data from Twitter's API.

twitterescaped.json

550KB

twitter.json with whitespace removed and non-ASCII characters replaced with Unicode escapes.

update-center.json

521KB

An export of data from Twitter's API.


Hardware used for testing: Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz, Windows 10, 32GB RAM.

Compilers and optimization flags: gcc 8.1 (-O3), clang 12.0 (-O3), and msvc 19.26 (/O2).

Parse apache_builds.json

Parse canada.json

Parse citm_catalog.json

Parse github_events.json

Parse gsoc-2018.json

Parse instruments.json

Parse marine_ik.json

Parse mesh.json

Parse mesh.pretty.json

Parse numbers.json

Parse random.json

Parse twitter.json

Parse twitterescaped.json

Parse update-center.json

Parse apache_builds.json

Serialize canada.json

Serialize citm_catalog.json

Serialize github_events.json

Serialize gsoc-2018.json

Serialize instruments.json

Serialize marine_ik.json

Serialize mesh.json

Serialize mesh.pretty.json

Serialize numbers.json

Serialize random.json

Serialize twitter.json

Serialize twitterescaped.json

Serialize update-center.json


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