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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
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Faster in x86_64 or aarch64, other architecture is fallback and maybe very slower.
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Requires Rust nightly versionSupport Stable Rust now. -
Please add the compile options
-C target-cpu=native
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"
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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.
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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:
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Deserialize Struct: Deserialize the JSON into Rust struct. The defined struct and testdata is from json-benchmark
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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.