ruby/benchmark/encoder.rb
Jean Boussier e52b47680e [ruby/json] Reduce encoding benchmark size
Profiling revealed that we were spending lots of time growing the buffer.
Buffer operations is definitely something we want to optimize, but for
this specific benchmark what we're interested in is UTF-8 scanning performance.

Each iteration of the two scaning benchmark were producing 20MB of JSON,
now they only produce 5MB.

Now:

```
== Encoding mostly utf8 (5001001 bytes)
ruby 3.4.0dev (2024-10-18T19:01:45Z master 7be9a333ca) +YJIT +PRISM [arm64-darwin23]
Warming up --------------------------------------
                json    35.000 i/100ms
                  oj    36.000 i/100ms
           rapidjson    10.000 i/100ms
Calculating -------------------------------------
                json    359.161 (± 1.4%) i/s    (2.78 ms/i) -      1.820k in   5.068542s
                  oj    359.699 (± 0.6%) i/s    (2.78 ms/i) -      1.800k in   5.004291s
           rapidjson     99.687 (± 2.0%) i/s   (10.03 ms/i) -    500.000 in   5.017321s

Comparison:
                json:      359.2 i/s
                  oj:      359.7 i/s - same-ish: difference falls within error
           rapidjson:       99.7 i/s - 3.60x  slower
```

1a338532d2
2024-10-26 18:44:15 +09:00

78 lines
3.4 KiB
Ruby

require "benchmark/ips"
require "json"
require "oj"
require "rapidjson"
if ENV["ONLY"]
RUN = ENV["ONLY"].split(/[,: ]/).map{|x| [x.to_sym, true] }.to_h
RUN.default = false
elsif ENV["EXCEPT"]
RUN = ENV["EXCEPT"].split(/[,: ]/).map{|x| [x.to_sym, false] }.to_h
RUN.default = true
else
RUN = Hash.new(true)
end
def implementations(ruby_obj)
state = JSON::State.new(JSON.dump_default_options)
{
json_state: ["json (reuse)", proc { state.generate(ruby_obj) }],
json: ["json", proc { JSON.dump(ruby_obj) }],
oj: ["oj", proc { Oj.dump(ruby_obj) }],
rapidjson: ["rapidjson", proc { RapidJSON.dump(ruby_obj) }],
}
end
def benchmark_encoding(benchmark_name, ruby_obj, check_expected: true, except: [])
json_output = JSON.dump(ruby_obj)
puts "== Encoding #{benchmark_name} (#{json_output.bytesize} bytes)"
impls = implementations(ruby_obj).select { |name| RUN[name] }
except.each { |i| impls.delete(i) }
Benchmark.ips do |x|
expected = ::JSON.dump(ruby_obj) if check_expected
impls.values.each do |name, block|
begin
result = block.call
if check_expected && expected != result
puts "#{name} does not match expected output. Skipping"
next
end
rescue => error
puts "#{name} unsupported (#{error})"
next
end
x.report(name, &block)
end
x.compare!(order: :baseline)
end
puts
end
# On the first two micro benchmarks, the limitting factor is that we have to create a Generator::State object for every
# call to `JSON.dump`, so we cause 2 allocations per call where alternatives only do one allocation.
# The performance difference is mostly more time spent in GC because of this extra pressure.
# If we re-use the same `JSON::State` instance, we're faster than Oj on the array benchmark, and much closer
# on the Hash one.
benchmark_encoding "small nested array", [[1,2,3,4,5]]*10
benchmark_encoding "small hash", { "username" => "jhawthorn", "id" => 123, "event" => "wrote json serializer" }
# On these benchmarks we perform well. Either on par or very closely faster/slower
benchmark_encoding "mixed utf8", ([("a" * 5000) + "" + ("a" * 5000)] * 500), except: %i(json_state)
benchmark_encoding "mostly utf8", ([("" * 3333)] * 500), except: %i(json_state)
benchmark_encoding "twitter.json", JSON.load_file("#{__dir__}/data/twitter.json"), except: %i(json_state)
benchmark_encoding "citm_catalog.json", JSON.load_file("#{__dir__}/data/citm_catalog.json"), except: %i(json_state)
# This benchmark spent the overwhelming majority of its time in `ruby_dtoa`. We rely on Ruby's implementation
# which uses a relatively old version of dtoa.c from David M. Gay.
# Oj is noticeably faster here because it limits the precision of floats, breaking roundtriping. That's not
# something we should emulate.
# Since a few years there are now much faster float to string implementations such as Ryu, Dragonbox, etc,
# but all these are implemented in C++11 or newer, making it hard if not impossible to include them.
# Short of a pure C99 implementation of these newer algorithms, there isn't much that can be done to match
# Oj speed without losing precision.
benchmark_encoding "canada.json", JSON.load_file("#{__dir__}/data/canada.json"), check_expected: false, except: %i(json_state)
benchmark_encoding "many #to_json calls", [{Object.new => Object.new, 12 => 54.3, Integer => Float, Time.now => Date.today}] * 20, except: %i(json_state)