Jiffy - JSON NIF for Erlang

Jiffy is a JSON NIF library that focuses on correctness over performance. It’s not the fastest JSON library for Erlang in standard benchmarks, but it endeavors to be as fast as possible while affecting total system performance as little as possible.

Build Status

Usage

Jiffy is a simple API. The only thing that might catch you off guard is that the return type of jiffy:encode/1 is an iolist even though it returns a binary most of the time.

A quick note on Unicode. Jiffy only understands UTF-8 in binaries. End of story.

Errors are raised as error exceptions.

Eshell V5.8.2  (abort with ^G)
1> jiffy:decode(<<"{\"foo\": \"bar\"}">>).
{[{<<"foo">>,<<"bar">>}]}
2> Doc = {[{foo, [<<"bing">>, 2.3, true]}]}.
{[{foo,[<<"bing">>,2.3,true]}]}
3> jiffy:encode(Doc).
<<"{\"foo\":[\"bing\",2.3,true]}">>

`jiffy:decode/1,2`

jiffy:decode(IoData)
jiffy:decode(IoData, Options)

The options for decode are:

return_maps - Tell Jiffy to return objects using the maps data type on VMs that support it. This raises an error on VMs that don't support maps.
{null_term, Term} - Returns the specified Term instead of null when decoding JSON. This is for people that wish to use undefined instead of null.
use_nil - Returns the atom nil instead of null when decoding JSON. This is a short hand for {null_term, nil}.
return_trailer - If any non-whitespace is found after the first JSON term is decoded the return value of decode/2 becomes {has_trailer, FirstTerm, RestData::iodata()}. This is useful to decode multiple terms in a single binary.
dedupe_keys - If a key is repeated in a JSON object this flag will ensure that the parsed object only contains a single entry containing the last value seen. This mirrors the parsing behavior of virtually every other JSON parser.
copy_strings - Normally, when strings are decoded, they are created as sub-binaries of the input data. With some workloads, this leads to an undesirable bloating of memory: Strings in the decode result keep a reference to the full JSON document alive. Setting this option will instead allocate new binaries for each string, so the original JSON document can be garbage collected even though the decode result is still in use.
{bytes_per_red, N} where N >= 0 - This controls the number of bytes that Jiffy will process as an equivalent to a reduction. Each 20 reductions we consume 1% of our allocated time slice for the current process. When the Erlang VM indicates we need to return from the NIF.
{bytes_per_iter, N} where N >= 0 - Backwards compatible option that is converted into the bytes_per_red value.

`jiffy:encode/1,2`

jiffy:encode(EJSON)
jiffy:encode(EJSON, Options)

where EJSON is a valid representation of JSON in Erlang according to the table below.

The options for encode are:

uescape - Escapes UTF-8 sequences to produce a 7-bit clean output
pretty - Produce JSON using two-space indentation
force_utf8 - Force strings to encode as UTF-8 by fixing broken surrogate pairs and/or using the replacement character to remove broken UTF-8 sequences in data.
use_nil - Encodes the atom nil as null.
escape_forward_slashes - Escapes the / character which can be useful when encoding URLs in some cases.
{bytes_per_red, N} - Refer to the decode options
{bytes_per_iter, N} - Refer to the decode options

Pre-encoded JSON

A {json, IoData} tuple can appear anywhere a JSON value is expected (except as an object key). The IoData is spliced into the output as is. Jiffy does not parse, validate, copy, or pretty-print it.

1> jiffy:encode([1, {json, <<"{\"cached\":true}">>}, 3]).
<<"[1,{\"cached\":true},3]">>
2> jiffy:encode({[{<<"a">>, {json, [<<"[1,">>, "2,3]"]}}]}).
<<"{\"a\":[1,2,3]}">>

The caller is responsible for ensuring it is well-formed JSON.

Data Format

Erlang                          JSON            Erlang
==========================================================================

null                       -> null           -> null
true                       -> true           -> true
false                      -> false          -> false
"hi"                       -> [104, 105]     -> [104, 105]
<<"hi">>                   -> "hi"           -> <<"hi">>
hi                         -> "hi"           -> <<"hi">>
1                          -> 1              -> 1
1.25                       -> 1.25           -> 1.25
[]                         -> []             -> []
[true, 1.0]                -> [true, 1.0]    -> [true, 1.0]
{[]}                       -> {}             -> {[]}
{[{foo, bar}]}             -> {"foo": "bar"} -> {[{<<"foo">>, <<"bar">>}]}
{[{123, bar}]}             -> {"123": "bar"} -> {[{<<"123">>, <<"bar">>}]}
{[{1.5, bar}]}             -> {"1.5": "bar"} -> {[{<<"1.5">>, <<"bar">>}]}
{[{<<"foo">>, <<"bar">>}]} -> {"foo": "bar"} -> {[{<<"foo">>, <<"bar">>}]}
#{<<"foo">> => <<"bar">>}  -> {"foo": "bar"} -> #{<<"foo">> => <<"bar">>}
#{123 => <<"bar">>}        -> {"123": "bar"} -> #{<<"123">> => <<"bar">>}
#{1.5 => <<"bar">>}        -> {"1.5": "bar"} -> #{<<"1.5">> => <<"bar">>}

N.B. The last three entries in this table are only valid for VM's that support the maps data type (i.e., 17.0 and newer) and client code must pass the return_maps option to jiffy:decode/2.

Scheduler Usage

Jiffy specifically avoids using shared resources like the dirty CPU schedulers, since those are used for large heap garbage collection, crypto functions, large binary matching, etc. Instead, it works with Erlang's regular VM schedulers and yields appropriately after consuming a fraction of available reductions. Yielding behavior can be explicitly controlled via the {bytes_per_red, N} option.

To get an idea of how this works, use the bench_scheduling.sh benchmark from https://github.com/nickva/bench. It check concurrent encoding and decoding scaled by the number of schedulers. An example run comparing against other JSON libraries may look like:

./bench_scheduling.sh
...
scheduler responsiveness check
  input:       citm-catalog.json duration: 2000
  schedulers:  12 online
  impls:       json, jiffy, simdjsone, jsone, jsx

[json]
  1x encdec       n=84 p50=135.0ms p95=182.9ms p99=191.9ms max=196.7ms
  12x encdec      n=86 p50=129.7ms p95=189.9ms p99=203.0ms max=206.2ms
  24x encdec      n=87 p50=263.0ms p95=461.2ms p99=506.1ms max=527.1ms

[jiffy]
  1x encdec       n=309 p50=38.3ms p95=51.9ms p99=57.4ms max=66.5ms
  12x encdec      n=300 p50=41.2ms p95=52.5ms p99=59.7ms max=66.2ms
  24x encdec      n=306 p50=80.2ms p95=111.8ms p99=118.8ms max=140.1ms

[simdjsone]
  1x encdec       n=20 p50=690.1ms p95=784.6ms p99=784.6ms max=784.8ms
  12x encdec      n=16 p50=790.9ms p95=887.5ms p99=887.5ms max=899.9ms
  24x encdec      n=24 p50=1448.4ms p95=1876.7ms p99=1879.5ms max=1882.7ms

[jsone]
  1x encdec       n=60 p50=213.1ms p95=261.8ms p99=263.9ms max=264.8ms
  12x encdec      n=60 p50=204.9ms p95=329.8ms p99=345.0ms max=350.9ms
  24x encdec      n=52 p50=440.1ms p95=700.3ms p99=773.3ms max=817.3ms

[jsx]
  1x encdec       n=24 p50=398.8ms p95=539.0ms p99=544.1ms max=548.3ms
  12x encdec      n=24 p50=391.5ms p95=684.9ms p99=687.0ms max=689.6ms
  24x encdec      n=24 p50=1181.3ms p95=1479.0ms p99=1558.1ms max=1654.7ms