Tags: #octave 

Update: Support for the JSON data format after GSoC 2020

The Google Summer of Code (GSoC) 2020 is over and I had the pleasure to mentor Abdallah Elshamy, who enriched Octave with the jsondecode() and jsonencode() functions. A remaining issue was the translation of the Octave function matlab.lang.makeValidName to the C++ language. This is now accomplished and the overall results are great.

See the previous benchmark of this Jupyter Notebook (August 19, 2020) with matlab.lang.makeValidName as Octave code.

Again a larger JSON data set was used, with test cases collected from the excellent nativejson-benchmark, but with focus on Octave.

Only the running times for reading and writing JSON data are regarded in this benchmark. Another test by Abdallah has been carried out in June to test the compatibility for Matlab.

The test environment is a laptop with

octave_version = version ()
octave_hg_id   = version ('-hgid')
octave_version = 7.0.0
octave_hg_id = 38e22065d9ec

The following JSON extensions for Octave are under test.

name description
Octave (builtin) Based on RapidJSON, reading DOM API.
octave-rapidjson Based on RapidJSON, reading SAX API.
octave-jsonstuff Based on RapidJSON, reading DOM API, writing m-file.
JSONio Based on JSMN, writing m-file.
jsonlab m-file only

The JSON test files are described in the following table.

name size (byte) description
citm_catalog.json 1,727,204 Structured data with mixed text and numeric.
canada.json 2,251,060 Numeric data set in GeoJSON format.
large-file.json 26,141,343 Structured data with mixed text and numeric.

Benchmark setup

Create a directory to keep track of the mess.

mkdir ('benchmark');
cd ('benchmark');

Load the benchmark JSON files.

if (exist ('citm_catalog.json', 'file') ~= 2)
  urlwrite ( ...
    'https://github.com/RichardHightower/json-parsers-benchmark/raw/master/data/citm_catalog.json', ...

if (exist ('canada.json', 'file') ~= 2)
  urlwrite ( ...
    'https://github.com/mloskot/json_benchmark/raw/master/data/canada.json', ...

if (exist ('large-file.json', 'file') ~= 2)
  urlwrite ( ...
    'https://github.com/json-iterator/test-data/raw/master/large-file.json', ...

Setup octave-rapidjson.

if (exist ('octave-rapidjson', 'dir') == 0)
  urlwrite ( ...
    'https://github.com/Andy1978/octave-rapidjson/archive/2d88511712032b14dea4c2272d82249e7547772a.zip', ...
  unzip  ('octave-rapidjson.zip');
  rename ('octave-rapidjson-2d88511712032b14dea4c2272d82249e7547772a', ...
  cd ('octave-rapidjson')
  urlwrite ( ...
    'https://github.com/Tencent/rapidjson/archive/35e480fc4ddf4ec4f7ad34d96353eef0aabf002d.zip', ...
  unzip  ('rapidjson.zip');
  rename ('rapidjson-35e480fc4ddf4ec4f7ad34d96353eef0aabf002d', 'rapidjson');
  mkoctfile -Wall -Wextra -I./rapidjson/include load_json.cc
  mkoctfile -Wall -Wextra -I./rapidjson/include save_json.cc
  cd ('..')

Setup octave-jsonstuff.

if (isempty (pkg ('list', 'jsonstuff')))
  pkg install https://github.com/apjanke/octave-jsonstuff/releases/download/v0.3.3/jsonstuff-0.3.3.tar.gz

Setup JSONio.

if (exist ('JSONio', 'dir') == 0)
  urlwrite ( ...
    'https://github.com/gllmflndn/JSONio/archive/6c699a315ac2c578864d8b740a061bff47b718bf.zip', ...
  unzip  ('JSONio.zip');
  rename ('JSONio-6c699a315ac2c578864d8b740a061bff47b718bf', 'JSONio');
  cd ('JSONio')
  mkoctfile --mex jsonread.c jsmn.c -DJSMN_PARENT_LINKS
  cd ('..')

Setup jsonlab.

if (exist ('jsonlab', 'dir') == 0)
  urlwrite ( ...
    'https://github.com/fangq/jsonlab/archive/d0fb684bd43165d312063345bdb795b628b2c679.zip', ...
  unzip  ('jsonlab.zip');
  rename ('jsonlab-d0fb684bd43165d312063345bdb795b628b2c679', 'jsonlab');

Benchmark run

The benchmark function reads the respective JSON file into a string and calls the libraries reading and writing function.

function t = benchmark (json_read_fcn, json_write_fcn)
  test_files = {'citm_catalog.json', 'canada.json', 'large-file.json'};
  N = length (test_files);
  t = nan (N, 2);
  for i = 1:N
    json_str = fileread (test_files{i});
    tic ();
    octave_obj = json_read_fcn (json_str);
    t(i,1) = toc ();
    tic ();
    json_str2 = json_write_fcn (octave_obj);
    t(i,2) = toc ();

The results for the Matlab (R2020b, prerelease) have been measured on the same system without JupyterLab.

t.matlab = [
  0.0768, 0.0853;
  0.1510, 0.5405;
  1.2222, 0.6521];

Octave (7.0.0, development version)

t.octave = benchmark (@jsondecode, @jsonencode);


addpath ('octave-rapidjson')
t.rapid_json = benchmark (@load_json, @save_json);
rmpath ('octave-rapidjson')

octave-jsonstuff: No results due to an error.

%pkg load jsonstuff
%t.jsonstuff = benchmark (@jsondecode, @jsonencode);
%error: cat: field names mismatch in concatenating structs
%error: called from
%    jsondecode>condense_decoded_json_recursive at line 116 column 9
%    jsondecode>condense_decoded_json at line 67 column 7
%    jsondecode at line 63 column 7
%    benchmark at line 8 column 16
%pkg unload jsonstuff

JSONio: Because of the long running time, the results of the first run are saved here.

addpath ('JSONio')
%t.jsonio = benchmark (@jsonread, @jsonwrite);
t.jsonio = [ ...
  0.9583,  30.5410;
  6.1333,  17.4022;
  4.3382, 552.8929];
rmpath ('JSONio')

Jsonlab: Because of the long running time, the results of the first run are saved here.

addpath ('jsonlab')
%t.jsonlab = benchmark (@loadjson, @savejson);
t.jsonlab = [ ...
   35.6242,  26.0625;
    6.1303,   0.7365;
  372.2456, 601.5318];
rmpath ('jsonlab')

Benchmark results

graphics_toolkit ('qt')
titles = {'citm\_catalog.json (2 MB, mixed)', ...
          'canada.json (2 MB, numeric)', ...
          'large-file.json (26 MB, mixed)'};
for i = 1:3
  subplot (3, 1, i);
  bar ([t.matlab(i,:); t.octave(i,:); t.rapid_json(i,:)]');
  legend ({'Matlab (R2020b, pre)', 'Octave (7.0.0, dev)', ...
           'octave-rapidjson'}, 'Location', 'bestoutside');
  ylabel ('time in seconds');
  title (titles{i});


for i = 1:3
  subplot (3, 1, i);
  bar ([t.jsonio(i,:); t.jsonlab(i,:)]');
  legend ({'JSONio', 'jsonlab'}, 'Location', 'bestoutside');
  ylabel ('time in seconds');
  title (titles{i});


The first figure compares the running times of Matlab, Octave, and octave-rapidjson. Both Octave and octave-rapidjson are based on RapidJSON and perform in many cases better than the Matlab implementation.

octave-rapidjson is using the SAX API of RapidJSON, while the new Octave implementation uses the DOM API. This decision was made to achieve best compatibility to Matlab, which was in some cases difficult with the SAX API and is no pririty for the octave-rapidjson project. The results show, that both APIs perform similarly in the tested data sets, even though there is a claim, that the SAX API is faster in some cases.

The results of JSONio and jsonlab are split into a second figure, as the running times are significantly larger than those of the first figure. For octave-jsonstuff we could due to an error not obtain any results and the maintainer is informed about it.

November 23, 2020 (Version 1)

Download the Jupyter Notebook.

(C) 2017 — 2021 Kai Torben Ohlhus. This work is licensed under CC BY 4.0. Page design adapted from minima and researcher. Get the sources on GitHub.