Crates.io Documentation Website License Build Status
English | 中文
A fast Rust JSON library based on SIMD. It has some references to other open-source libraries like sonic_cpp, serde_json, sonic, simdjson, rust-std and more.
For Golang users to use sonic_rs, please see for_Golang_user.md
For users to migrate from serde_json to sonic_rs, can see serdejson_compatibility
-
Faster in x86_64 or aarch64, other architecture is fallback and maybe very slower.
-
(削除) Requires Rust nightly version (削除ここまで)Support Stable Rust now. -
Please add the compile options
-C target-cpu=native -
Should enable
sanitizefeature to avoid false-positive if you are using LLVM-sanitizer in your program. Don't enable this feature in production, since it will cause 30% performance loss in serialize.
To ensure that SIMD instruction is used in sonic-rs, you need to add rustflags -C target-cpu=native and compile on the host machine. For example, Rust flags can be configured in Cargo config.
Add sonic-rs in Cargo.toml
[dependencies]
sonic-rs = "0.3"
-
Serde into Rust struct as
serde_jsonandserde. -
Parse/Serialize JSON for untyped
sonic_rs::Value, which can be mutable. -
Get specific fields from a JSON with the blazing performance.
-
Use JSON as a lazy array or object iterator with the blazing performance.
-
Support
LazyValue,NumberandRawNumber(just like Golang'sJsonNumber) in default. -
The floating parsing precision is as Rust std in default.
The main optimization in sonic-rs is the use of SIMD. However, we do not use the two-stage SIMD algorithms from simd-json. We primarily use SIMD in the following scenarios:
- parsing/serialize long JSON strings
- parsing the fraction of float number
- Getting a specific elem or field from JSON
- Skipping white spaces when parsing JSON
More details about optimization can be found in performance.md.
Benchmarks environment:
Architecture: x86_64
Model name: Intel(R) Xeon(R) Platinum 8260 CPU @ 2.40GHz
AArch64 benchmark data can be found in benchmark_aarch64.md.
Benchmarks:
-
Deserialize Struct: Deserialize the JSON into Rust struct. The defined struct and testdata is from json-benchmark
-
Deseirlize Untyped: Deseialize the JSON into an untyped document
The serialize benchmarks work oppositely.
All deserialized benchmarks enabled UTF-8 validation and enabled float_roundtrip in serde-json to get sufficient precision as Rust std.
The benchmark will parse JSON into a Rust struct, and there are no unknown fields in JSON text. All fields are parsed into struct fields in the JSON.
Sonic-rs is faster than simd-json because simd-json (Rust) first parses the JSON into a tape, then parses the tape into a Rust struct. Sonic-rs directly parses the JSON into a Rust struct, and there are no temporary data structures. The flamegraph is profiled in the citm_catalog case.
cargo bench --bench deserialize_struct -- --quiet
twitter/sonic_rs::from_slice_unchecked
time: [694.74 μs 707.83 μs 723.19 μs]
twitter/sonic_rs::from_slice
time: [796.44 μs 827.74 μs 861.30 μs]
twitter/simd_json::from_slice
time: [1.0615 ms 1.0872 ms 1.1153 ms]
twitter/serde_json::from_slice
time: [2.2659 ms 2.2895 ms 2.3167 ms]
twitter/serde_json::from_str
time: [1.3504 ms 1.3842 ms 1.4246 ms]
citm_catalog/sonic_rs::from_slice_unchecked
time: [1.2271 ms 1.2467 ms 1.2711 ms]
citm_catalog/sonic_rs::from_slice
time: [1.3344 ms 1.3671 ms 1.4050 ms]
citm_catalog/simd_json::from_slice
time: [2.0648 ms 2.0970 ms 2.1352 ms]
citm_catalog/serde_json::from_slice
time: [2.9391 ms 2.9870 ms 3.0481 ms]
citm_catalog/serde_json::from_str
time: [2.5736 ms 2.6079 ms 2.6518 ms]
canada/sonic_rs::from_slice_unchecked
time: [3.7779 ms 3.8059 ms 3.8368 ms]
canada/sonic_rs::from_slice
time: [3.9676 ms 4.0212 ms 4.0906 ms]
canada/simd_json::from_slice
time: [7.9582 ms 8.0932 ms 8.2541 ms]
canada/serde_json::from_slice
time: [9.2184 ms 9.3560 ms 9.5299 ms]
canada/serde_json::from_str
time: [9.0383 ms 9.2563 ms 9.5048 ms]
The benchmark will parse JSON into a document. Sonic-rs seems faster for several reasons:
- There are also no temporary data structures in sonic-rs, as detailed above.
- Sonic-rs uses a memory arena for the whole document, resulting in fewer memory allocations, better cache-friendliness, and mutability.
- The JSON object in
sonic_rs::Valueis an array. Sonic-rs does not build a hashmap.
cargo bench --bench deserialize_value -- --quiet
twitter/sonic_rs_dom::from_slice
time: [550.95 μs 556.10 μs 562.89 μs]
twitter/sonic_rs_dom::from_slice_unchecked
time: [525.97 μs 530.26 μs 536.06 μs]
twitter/serde_json::from_slice
time: [3.7599 ms 3.8009 ms 3.8513 ms]
twitter/serde_json::from_str
time: [2.8618 ms 2.8960 ms 2.9396 ms]
twitter/simd_json::slice_to_owned_value
time: [1.7302 ms 1.7557 ms 1.7881 ms]
twitter/simd_json::slice_to_borrowed_value
time: [1.1870 ms 1.1951 ms 1.2039 ms]
canada/sonic_rs_dom::from_slice
time: [4.9060 ms 4.9568 ms 5.0213 ms]
canada/sonic_rs_dom::from_slice_unchecked
time: [4.7858 ms 4.8728 ms 4.9803 ms]
canada/serde_json::from_slice
time: [16.689 ms 16.980 ms 17.335 ms]
canada/serde_json::from_str
time: [16.398 ms 16.640 ms 16.932 ms]
canada/simd_json::slice_to_owned_value
time: [12.627 ms 12.846 ms 13.070 ms]
canada/simd_json::slice_to_borrowed_value
time: [12.030 ms 12.164 ms 12.323 ms]
citm_catalog/sonic_rs_dom::from_slice
time: [1.6657 ms 1.6981 ms 1.7341 ms]
citm_catalog/sonic_rs_dom::from_slice_unchecked
time: [1.5109 ms 1.5253 ms 1.5424 ms]
citm_catalog/serde_json::from_slice
time: [8.1618 ms 8.2566 ms 8.3653 ms]
citm_catalog/serde_json::from_str
time: [7.8652 ms 8.0706 ms 8.3074 ms]
citm_catalog/simd_json::slice_to_owned_value
time: [3.9834 ms 4.0325 ms 4.0956 ms]
citm_catalog/simd_json::slice_to_borrowed_value
time: [3.3196 ms 3.3433 ms 3.3689 ms]
cargo bench --bench serialize_value -- --quiet
We serialize the document into a string. In the following benchmarks, sonic-rs appears faster for the twitter JSON. The twitter JSON contains many long JSON strings, which fit well with sonic-rs's SIMD optimization.
twitter/sonic_rs::to_string
time: [380.90 μs 390.00 μs 400.38 μs]
twitter/serde_json::to_string
time: [788.98 μs 797.34 μs 807.69 μs]
twitter/simd_json::to_string
time: [965.66 μs 981.14 μs 998.08 μs]
citm_catalog/sonic_rs::to_string
time: [805.85 μs 821.99 μs 841.06 μs]
citm_catalog/serde_json::to_string
time: [1.8299 ms 1.8880 ms 1.9498 ms]
citm_catalog/simd_json::to_string
time: [1.7356 ms 1.7636 ms 1.7972 ms]
canada/sonic_rs::to_string
time: [6.5808 ms 6.7082 ms 6.8570 ms]
canada/serde_json::to_string
time: [6.4800 ms 6.5747 ms 6.6893 ms]
canada/simd_json::to_string
time: [7.3751 ms 7.5690 ms 7.7944 ms]
cargo bench --bench serialize_struct -- --quiet
The explanation is as mentioned above.
twitter/sonic_rs::to_string
time: [434.03 μs 448.25 μs 463.97 μs]
twitter/simd_json::to_string
time: [506.21 μs 515.54 μs 526.35 μs]
twitter/serde_json::to_string
time: [719.70 μs 739.97 μs 762.69 μs]
canada/sonic_rs::to_string
time: [4.6701 ms 4.7481 ms 4.8404 ms]
canada/simd_json::to_string
time: [5.8072 ms 5.8793 ms 5.9625 ms]
canada/serde_json::to_string
time: [4.5708 ms 4.6281 ms 4.6967 ms]
citm_catalog/sonic_rs::to_string
time: [624.86 μs 629.54 μs 634.57 μs]
citm_catalog/simd_json::to_string
time: [624.10 μs 633.55 μs 644.78 μs]
citm_catalog/serde_json::to_string
time: [802.10 μs 814.15 μs 828.10 μs]
cargo bench --bench get_from -- --quiet
The benchmark is getting a specific field from the twitter.json.
- sonic-rs::get_unchecked_from_str: without validate
- sonic-rs::get_from_str: with validate
- gjson::get_from_str: without validate
Sonic-rs utilize SIMD to quickly skip unnecessary fields in the unchecked case, thus enhancing the performance.
twitter/sonic-rs::get_unchecked_from_str
time: [75.671 μs 76.766 μs 77.894 μs]
twitter/sonic-rs::get_from_str
time: [430.45 μs 434.62 μs 439.43 μs]
twitter/gjson::get_from_str
time: [359.61 μs 363.14 μs 367.19 μs]
Directly use the Deserialize or Serialize trait.
use sonic_rs::{Deserialize, Serialize}; // sonic-rs re-exported them from serde // or use serde::{Deserialize, Serialize}; #[derive(Serialize, Deserialize)] struct Person { name: String, age: u8, phones: Vec<String>, } fn main() { let data = r#"{ "name": "Xiaoming", "age": 18, "phones": [ "+123456" ] }"#; let p: Person = sonic_rs::from_str(data).unwrap(); assert_eq!(p.age, 18); assert_eq!(p.name, "Xiaoming"); let out = sonic_rs::to_string_pretty(&p).unwrap(); assert_eq!(out, data); }
Get a specific field from a JSON with the pointer path. The return is a LazyValue, which is a wrapper of a raw valid JSON slice.
We provide the get and get_unchecked apis. get_unchecked apis should be used in valid JSON, otherwise it may return unexpected result.
use sonic_rs::JsonValueTrait; use sonic_rs::{get, get_unchecked, pointer}; fn main() { let path = pointer!["a", "b", "c", 1]; let json = r#" {"u": 123, "a": {"b" : {"c": [null, "found"]}}} "#; let target = unsafe { get_unchecked(json, &path).unwrap() }; assert_eq!(target.as_raw_str(), r#""found""#); assert_eq!(target.as_str().unwrap(), "found"); let target = get(json, &path); assert_eq!(target.as_str().unwrap(), "found"); assert_eq!(target.unwrap().as_raw_str(), r#""found""#); let path = pointer!["a", "b", "c", "d"]; let json = r#" {"u": 123, "a": {"b" : {"c": [null, "found"]}}} "#; // not found from json let target = get(json, &path); assert!(target.is_err()); }
Parse a JSON into a sonic_rs::Value.
use sonic_rs::{from_str, json}; use sonic_rs::JsonValueMutTrait; use sonic_rs::{pointer, JsonValueTrait, Value}; fn main() { let json = r#"{ "name": "Xiaoming", "obj": {}, "arr": [], "age": 18, "address": { "city": "Beijing" }, "phones": [ "+123456" ] }"#; let mut root: Value = from_str(json).unwrap(); // get key from value let age = root.get("age").as_i64(); assert_eq!(age.unwrap_or_default(), 18); // get by index let first = root["phones"][0].as_str().unwrap(); assert_eq!(first, "+123456"); // get by pointer let phones = root.pointer(&pointer!["phones", 0]); assert_eq!(phones.as_str().unwrap(), "+123456"); // convert to mutable object let obj = root.as_object_mut().unwrap(); obj.insert(&"inserted", true); assert!(obj.contains_key(&"inserted")); let mut object = json!({ "A": 65, "B": 66, "C": 67 }); *object.get_mut("A").unwrap() = json!({ "code": 123, "success": false, "payload": {} }); let mut val = json!(["A", "B", "C"]); *val.get_mut(2).unwrap() = json!("D"); // serialize assert_eq!(serde_json::to_string(&val).unwrap(), r#"["A","B","D"]"#); }
Parse an object or array JSON into a lazy iterator.
use bytes::Bytes; use faststr::FastStr; use sonic_rs::JsonValueTrait; use sonic_rs::{to_array_iter, to_object_iter_unchecked}; fn main() { let json = Bytes::from(r#"[1, 2, 3, 4, 5, 6]"#); let iter = to_array_iter(&json); for (i, v) in iter.enumerate() { assert_eq!(i + 1, v.as_u64().unwrap() as usize); } let json = Bytes::from(r#"[1, 2, 3, 4, 5, 6"#); let iter = to_array_iter(&json); for elem in iter { // do something for each elem // deal with errors when invalid json if elem.is_err() { assert_eq!( elem.err().unwrap().to_string(), "Expected this character to be either a ',' or a ']' while parsing at line 1 column 17" ); } } let json = FastStr::from(r#"{"a": null, "b":[1, 2, 3]}"#); let iter = unsafe { to_object_iter_unchecked(&json) }; for ret in iter { // deal with errors if ret.is_err() { println!("{}", ret.unwrap_err()); return; } let (k, v) = ret.unwrap(); if k == "a" { assert!(v.is_null()); } else if k == "b" { let iter = to_array_iter(v.as_raw_str()); for (i, v) in iter.enumerate() { assert_eq!(i + 1, v.as_u64().unwrap() as usize); } } } }
If we need to parse a JSON value as a raw string, we can use LazyValue.
If we need to parse a JSON number into an untyped type, we can use Number.
If we need to parse a JSON number without loss of precision, we can use RawNumber. It likes encoding/json.Number in Golang, and can also be parsed from a JSON string.
Detailed examples can be found in raw_value.rs and json_number.rs.
Sonic's errors are followed as serde-json and have a display around the error position, examples in handle_error.rs.
By default, sonic-rs enable the UTF-8 validation, except for xx_unchecked APIs.
By default, sonic-rs uses floating point precision consistent with the Rust standard library, and there is no need to add an extra float_roundtrip feature like serde-json to ensure floating point precision.
If you want to achieve lossless precision when parsing floating-point numbers, such as Golang encoding/json.Number and serde-json arbitrary_precision, you can use sonic_rs::RawNumber.
Thanks the following open-source libraries. sonic-rs has some references to other open-source libraries like sonic_cpp, serde_json, sonic, simdjson, yyjson, rust-std and so on.
We rewrote many SIMD algorithms from sonic-cpp/sonic/simdjson/yyjson for performance. We reused the de/ser codes and modified necessary parts from serde_json to make high compatibility with serde. We reused part codes about floating parsing from rust-std to make it more accurate.
Referenced papers:
- Parsing Gigabytes of JSON per Second
- JSONSki: streaming semi-structured data with bit-parallel fast-forwarding
Please read CONTRIBUTING.md for information on contributing to sonic-rs.