Coder Social home page Coder Social logo

strogo / sonic-1 Goto Github PK

View Code? Open in Web Editor NEW

This project forked from bytedance/sonic

0.0 1.0 0.0 3.79 MB

A blazingly fast JSON serializing & deserializing library

License: Apache License 2.0

Shell 0.11% Makefile 0.10% Go 33.75% Assembly 59.56% C 6.48%

sonic-1's Introduction

Sonic

A blazingly fast JSON serializing & deserializing library, accelerated by JIT (just-in-time compiling) and SIMD (single-instruction-multiple-data).

Requirement

  • Go 1.15/1.16
  • Linux/darwin OS
  • Amd64 CPU with AVX instruction set

Features

  • Runtime object binding without code generation
  • Complete APIs for JSON value manipulation
  • Fast, fast, fast!

Benchmarks

For all sizes of json and all cases of usage, Sonic performs best.

  • Small (400B, 11 keys, 3 layers) small benchmarks
  • Large (635KB, 10000+ key, 6 layers) large benchmarks
  • Medium (13KB, 300+ key, 6 layers)

For medium data, Sonic's speed is 2.6x times of json-iterator's in decoding, 2.5x times in encoding,and 8.3x times in searching.

goos: darwin
goarch: amd64
cpu: Intel(R) Core(TM) i9-9880H CPU @ 2.30GHz
BenchmarkEncoder_Generic_Sonic-16                         100000             25547 ns/op         510.23 MB/s       13762 B/op          4 allocs/op
BenchmarkEncoder_Generic_JsonIter-16                      100000             44526 ns/op         292.75 MB/s       13433 B/op         77 allocs/op
BenchmarkEncoder_Generic_StdLib-16                        100000            134480 ns/op          96.93 MB/s       48177 B/op        827 allocs/op
BenchmarkEncoder_Binding_Sonic-16                         100000              6658 ns/op        1957.74 MB/s       14156 B/op          4 allocs/op
BenchmarkEncoder_Binding_JsonIter-16                      100000             21367 ns/op         610.05 MB/s        9487 B/op          2 allocs/op
BenchmarkEncoder_Binding_StdLib-16                        100000             17558 ns/op         742.41 MB/s        9480 B/op          1 allocs/op
BenchmarkEncoder_Parallel_Generic_Sonic-16                100000              4562 ns/op        2857.18 MB/s       10957 B/op          4 allocs/op
BenchmarkEncoder_Parallel_Generic_JsonIter-16             100000             10943 ns/op        1191.21 MB/s       13449 B/op         77 allocs/op
BenchmarkEncoder_Parallel_Generic_StdLib-16               100000             52174 ns/op         249.84 MB/s       48218 B/op        827 allocs/op
BenchmarkEncoder_Parallel_Binding_Sonic-16                100000              1422 ns/op        9168.12 MB/s       11030 B/op          4 allocs/op
BenchmarkEncoder_Parallel_Binding_JsonIter-16             100000              4630 ns/op        2815.35 MB/s        9496 B/op          2 allocs/op
BenchmarkEncoder_Parallel_Binding_StdLib-16               100000              4977 ns/op        2619.08 MB/s        9488 B/op          1 allocs/op

BenchmarkDecoder_Generic_Sonic-16                         100000             57247 ns/op         227.70 MB/s       49727 B/op        313 allocs/op
BenchmarkDecoder_Generic_StdLib-16                        100000            139698 ns/op          93.31 MB/s       50898 B/op        772 allocs/op
BenchmarkDecoder_Generic_JsonIter-16                      100000            101967 ns/op         127.84 MB/s       55787 B/op       1068 allocs/op
BenchmarkDecoder_Binding_Sonic-16                         100000             28254 ns/op         461.35 MB/s       25062 B/op         34 allocs/op
BenchmarkDecoder_Binding_StdLib-16                        100000            123779 ns/op         105.31 MB/s       10560 B/op        207 allocs/op
BenchmarkDecoder_Binding_JsonIter-16                      100000             38253 ns/op         340.75 MB/s       14674 B/op        385 allocs/op
BenchmarkDecoder_Parallel_Generic_Sonic-16                100000             10171 ns/op        1281.59 MB/s       49458 B/op        313 allocs/op
BenchmarkDecoder_Parallel_Generic_StdLib-16               100000             54916 ns/op         237.36 MB/s       50907 B/op        772 allocs/op
BenchmarkDecoder_Parallel_Generic_JsonIter-16             100000             48286 ns/op         269.95 MB/s       55811 B/op       1068 allocs/op
BenchmarkDecoder_Parallel_Binding_Sonic-16                100000              5282 ns/op        2467.83 MB/s       24683 B/op         34 allocs/op
BenchmarkDecoder_Parallel_Binding_StdLib-16               100000             31875 ns/op         408.94 MB/s       10559 B/op        207 allocs/op
BenchmarkDecoder_Parallel_Binding_JsonIter-16             100000             13810 ns/op         943.90 MB/s       14679 B/op        385 allocs/op

BenchmarkSearchOne_Gjson-16                               100000              8992 ns/op        1448.28 MB/s           0 B/op          0 allocs/op
BenchmarkSearchOne_Jsoniter-16                            100000             58313 ns/op         223.33 MB/s       27936 B/op        647 allocs/op
BenchmarkSearchOne_Sonic-16                               100000             10497 ns/op        1240.61 MB/s          29 B/op          1 allocs/op
BenchmarkSearchOne_Parallel_Gjson-16                      100000              1046 ns/op        12449.59 MB/s          0 B/op          0 allocs/op
BenchmarkSearchOne_Parallel_Jsoniter-16                   100000             16080 ns/op         809.88 MB/s       27942 B/op        647 allocs/op
BenchmarkSearchOne_Parallel_Sonic-16                      100000              1435 ns/op        9074.18 MB/s         285 B/op          1 allocs/op

More detail see decoder/decoder_test.go, encoder/encoder_test.go, ast/search_test.go, ast/parser_test.go, ast/node_test.go

How it works

See INTRODUCTION.md

Fuzzing

sonic-fuzz is the repository for fuzzing tests. If you find any bug, please report the issue to sonic.

Usage

Marshal/Unmarshal

The behaviors are mostly consistent with encoding/json, except some uncommon escaping (see issue4)

import "github.com/bytedance/sonic"

var data YourSchema
// Marshal
output, err := sonic.Marshal(&data) 
// Unmarshal
err := sonic.Unmarshal(output, &data) 

Use Number/Use Int64

import "github.com/bytedance/sonic/decoder"

var input = `1`
var data interface{}

// default float64
dc := decoder.NewDecoder(input) 
dc.Decode(&data) // data == float64(1)
// use json.Number
dc = decoder.NewDecoder(input)
dc.UseNumber()
dc.Decode(&data) // data == json.Number("1")
// use int64
dc = decoder.NewDecoder(input)
dc.UseInt64()
dc.Decode(&data) // data == int64(1)

root, err := sonic.GetFromString(input)
// Get json.Number
jn := root.Number()
jm := root.InterfaceUseNumber().(json.Number) // jn == jm
// Get float64
fn := root.Float64()
fm := root.Interface().(float64) // jn == jm

Sort Keys

On account of the performance loss from sorting (roughly 10%), sonic doesn't enable this feature by default. If your component depends on it to work (like zstd), Use it like this:

import "github.com/bytedance/sonic/encoder"

m := map[string]interface{}{}
v, err := encoder.Encode(m, encoder.SortMapKeys)

Caution: sonic encode struct in order of its original field declaration, so if you want to sort a struct's keys like the map's, just rewrite your struct.

Print Syntax Error

import "github.com/bytedance/sonic/decoder"

var data interface{}
dc := decoder.NewDecoder("[[[}]]")
if err := dc.Decode(&data); err != nil {
    if e, ok := err.(decoder.SyntaxError); ok {
        
        /*Syntax error at index 3: invalid char

            [[[}]]
            ...^..
        */
        print(e.Description())

        /*"Syntax error at index 3: invalid char\n\n\t[[[}]]\n\t...^..\n"*/
        println(fmt.Sprintf("%q", e.Description()))
    }

    /*Decode: Syntax error at index 3: invalid char*/
    t.Fatalf("Decode: %v", err) 
}

Ast.Node

Sonic/ast.Node is a completely self-contained AST for JSON. It implements serialization and deserialization both, and provides robust APIs for obtaining and modification of generic data.

Get/Index

Search partial JSON by given paths, which must be non-negative integer or string or nil

import "github.com/bytedance/sonic"

input := []byte(`{"key1":[{},{"key2":{"key3":[1,2,3]}}]}`)

// no path, returns entire json
root, err := sonic.Get(input)
raw := root.Raw() // == string(input)

// multiple pathes
root, err := sonic.Get(input, "key1", 1, "key2")
sub := root.Get("key3").Index(2).Int64() // == 3

Tip: since Index() uses offset to locate data, which is faster much than scanning like Get(), we suggest you use it as much as possible. And sonic also provides another API IndexOrGet() to underlying use offset as well as ensuring the key is matched.

Set/Unset

Modify the json content by Set()/Unset()

import "github.com/bytedance/sonic"

// Set
exist, err := root.Set("key4", NewBool(true)) // exist == false
alias1 := root.Get("key4") 
println(alias1.Valid()) // true
alias2 := root.Index(1)
println(alias1 == alias2) // true

// Unset
exist, err := root.UnsetByIndex(1) // exist == true
println(root.Get("key4").Check()) // "value not exist"

Serialize

To encode ast.Node as json, use MarshalJson() or json.Marshal() (MUST pass the node's pointer)

import (
    "encoding/json"
    "github.com/bytedance/sonic"
)

buf, err := root.MarshalJson()
println(string(buf))                // {"key1":[{},{"key2":{"key3":[1,2,3]}}]}
exp, err := json.Marshal(&root)     // WARN: use pointer
println(string(buf) == string(exp)) // true

APIs

  • validation: Check(), Error(), Valid(), Exist()
  • searching: Index(), Get(), IndexPair(), IndexOrGet(), GetByPath()
  • go-type casting: Int64(), Float64(), String(), Number(), Bool(), Map[UseNumber|UseNode](), Array[UseNumber|UseNode](), Interface[UseNumber|UseNode]()
  • go-type packing: NewRaw(), NewNumber(), NewNull(), NewBool(), NewString(), NewObject(), NewArray()
  • iteration: Values(), Properties()
  • modification: Set(), SetByIndex(), Add(), Cap(), Len()

Tips

Pretouch

Since Sonic uses golang-asm as a JIT assembler, which is NOT very suitable for runtime compiling, first-hit running of a huge schema may cause request-timeout or even process-OOM. For better stability, we advise to use Pretouch() for huge-schema or compact-memory application before Marshal()/Unmarshal().

import (
    "reflect"
    "github.com/bytedance/sonic"
)

func init() {
    var v HugeStruct
    err := sonic.Pretouch(reflect.TypeOf(v))
}

CAUTION: use the STRUCT instead of its POINTER to Pretouch(), otherwise it won't work when you pass the pointer to Marshal()/Unmarshal()!

Pass string or []byte?

For alignment to encoding/json, we provide API to pass []byte as argument, but the string-to-bytes copy is conducted at the same time considering safety, which may lose performance when origin JSON is huge. Therefore, you can use UnmarshalString, GetFromString to pass a string, as long as your origin data is a string or nocopy-cast is safe for your []byte.

Better performance for generic deserializing

In most cases, Unmarshal() with schemalized data performs better than ast.Loads()/node.Interface() with generic data. But if you only have a schema for partial json, you can combine Get() and Unmarshal() together:

import "github.com/bytedance/sonic"

node, err := sonic.GetFromString(_TwitterJson, "statuses", 3, "user")
var user User // your partial schema...
err = sonic.UnmarshalString(node.Raw(), &user)

Even if you don't have any schema, Use InterfaceUseNode() as the container of generic values instead of Map() or Interface():

import "github.com/bytedance/sonic"

node, err := sonic.GetFromString(_TwitterJson, "statuses", 3, "user")
user := node.InterfaceUseNode() // use node.Interface() as little as possible

Why?

  1. using Interface() means Sonic must parse all the underlying values, while in most cases you only need several of them;
  2. map[x] is not efficient enough compared to array[x], but ast.Node can use Index(), for either array or object node;
  3. map's performance degrades a lot once rehashing triggered, but ast.Node doesn't has this concern;

sonic-1's People

Contributors

asterdy avatar chenzhuoyu avatar goccy avatar liuq19 avatar purewhitewu avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.