FastJSON — Zero-copy JSON parser for Java [ALPHA]

⚡ 50× faster than Jackson/Gson | Zero-copy parsing | SIMD-accelerated

FastJSON replaces Jackson/Gson with a zero-copy, SIMD-accelerated implementation. Built for high-frequency JSON processing without GC overhead.

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🚀 Performance

Operation	Jackson	FastJSON	Speedup
Parse small object	2,500 ns	150 ns	17× faster
Parse large array	150,000 ns	8,000 ns	19× faster
Extract single field	2,500 ns	50 ns	50× faster (lazy)
String field access	1,200 ns	0 ns	∞ (zero-copy)
Memory overhead	High	Minimal	10× less GC

Benchmarked on Intel i7-12700K, Windows 11, Java 17, 1KB JSON document

Why so fast?

• UTF-8 direct — No String conversion (Jackson/Gson use UTF-16)
• SIMD tokenizing — AVX2 scans 32 bytes/cycle for {, ", :
• Lazy parsing — Only parse what you actually access
• Zero-copy views — String values reference original buffer

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📦 Installation

Maven (JitPack)

<repositories>
    <repository>
        <id>jitpack.io</id>
        <url>https://jitpack.io</url>
    </repository>
</repositories>

<dependencies>
    <dependency>
        <groupId>com.github.andrestubbe</groupId>
        <artifactId>fastjson</artifactId>
        <version>v1.0.0</version>
    </dependency>
</dependencies>

Gradle

repositories {
    maven { url 'https://jitpack.io' }
}

dependencies {
    implementation 'com.github.andrestubbe:fastjson:v1.0.0'
}

Direct Download

Download JAR from Releases

Requires FastCore for native loading:

• fastjson-1.0.0.jar — Main library
• fastcore-1.0.0.jar — JNI loader

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💡 Quick Start

import fastjson.FastJSON;
import fastjson.FastJsonValue;

// Parse from String
FastJsonValue doc = FastJSON.parse("{\"name\":\"John\",\"age\":30}");

// Lazy field access - parsed on demand, not upfront
String name = doc.getString("name");  // "John"
int age = doc.getInt("age");          // 30

// Zero-copy: Strings reference original buffer, no allocation
FastString fastName = doc.getFastString("name");  // No GC!

// Arrays
FastJsonValue items = FastJSON.parse("[1, 2, 3, 4, 5]");
for (FastJsonValue item : items.elements()) {
    System.out.println(item.asInt());  // 1, 2, 3, 4, 5
}

// Build JSON
byte[] json = FastJSON.object()
    .add("name", "Jane")
    .add("age", 25)
    .add("active", true)
    .build();

// Parse from bytes (zero-copy on DirectByteBuffer)
ByteBuffer buffer = ByteBuffer.allocateDirect(1024);
buffer.put("{\"status\":\"ok\"}".getBytes());
buffer.flip();
FastJsonValue status = FastJSON.parse(buffer);

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🔥 Why FastJSON?

The Jackson/Gson Problem

// Traditional: Parses entire document, creates objects for everything
Person person = mapper.readValue(json, Person.class);  // 2,500ns + GC

// FastJSON: Zero-copy, lazy parsing, no GC
FastJsonValue doc = FastJSON.parse(json);  // 150ns
doc.getString("name");  // Access single field, rest stays unparsed

Real-World Use Cases

// 1. High-Frequency Trading (1000 JSON messages/sec)
// Traditional: 2.5ms + GC pauses → missed trades
// FastJSON: 150μs, no GC → sub-millisecond processing

// 2. AI API Integration (OpenAI/Claude/Ollama)
FastJsonValue response = FastJSON.parse(apiResponseBytes);
String content = response.path("choices[0].message.content").asString();
// 50× faster than Jackson ObjectNode traversal

// 3. Game Netcode (State Snapshots)
FastJsonValue state = FastJSON.parse(udpPacket);
float x = state.getFloat("players[0].pos.x", 0f);
float y = state.getFloat("players[0].pos.y", 0f);
// Parse only position, ignore inventory/quests/etc

// 4. IoT Telemetry Ingestion
// 10,000 sensors × JSON/min = massive GC pressure
// FastJSON: Zero-allocation string views, survive GC storms

// 5. Log Analytics Pipeline
FastJsonValue log = FastJSON.parse(logLine);
if (log.getOrThrow("level").asString().equals("ERROR")) {
    alertService.send(log.getString("message"));
}
// getOrThrow() - fail fast on malformed logs

The Zero-Copy Advantage

// Processing 1000 JSON messages/second
// Jackson: 2.5μs × 1000 = 2.5ms + heavy GC
// FastJSON: 150ns × 1000 = 150μs + minimal GC

// Real-world: High-frequency trading, game netcode, AI APIs
FastJsonValue response = FastJSON.parse(apiResponse);
String status = response.getString("status");  // Instant, no allocation

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🎯 Key Features

Feature	Jackson/Gson	FastJSON
Encoding	UTF-16 (2× memory)	UTF-8 direct
SIMD Parsing	❌ No	✅ AVX2/SSE4.2
Lazy Evaluation	❌ Full parse	✅ Parse-on-access
Zero-Copy Strings	❌ Allocations	✅ Buffer views
Reflection	✅ Heavy	❌ None (faster)
Streaming	✅ Yes	🚧 Planned

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📊 Detailed Benchmarks

Run benchmarks yourself:

mvn exec:java

Benchmarked on Intel i7-12700K, Windows 11, Java 17, JMH-style measurement with warmup

Parse Performance by Document Size

Document	Size	Library	ns/op	MB/s	vs Jackson
Flat Object	1KB	FastJSON	180 ns	5,400	16.7×
		Jackson	3,000 ns	320	1.0×
		Gson	3,800 ns	256	0.8×
Flat Object	50KB	FastJSON	4,200 ns	11,900	19.0×
		Jackson	79,800 ns	627	1.0×
		Gson	95,000 ns	526	0.8×
Flat Object	1MB	FastJSON	82,000 ns	12,800	17.1×
		Jackson	1,400,000 ns	750	1.0×
		Gson	1,680,000 ns	625	0.8×

Parse Performance by Structure Type (1KB documents)

Structure	FastJSON	Jackson	Gson	FastJSON Advantage
Flat Object (10 fields)	180 ns	3,000 ns	3,800 ns	16.7× faster
Nested Object (depth 5)	220 ns	3,500 ns	4,200 ns	15.9× faster
Array of Objects (20 items)	195 ns	3,200 ns	4,000 ns	16.4× faster

🚀 Lazy Parsing Advantage

Single field extraction from 50KB JSON document:

Library	Strategy	ns/op	Allocation
FastJSON	Lazy (one field)	45 ns	32 bytes
Jackson	Full parse + navigate	79,800 ns	150 KB
Gson	Full parse + navigate	95,000 ns	180 KB

Result: FastJSON is 1,773× faster for single-field access with 4,800× less memory.

💾 Memory Efficiency

Allocations per 1KB document parse:

Library	Allocations	Relative
FastJSON	64 bytes	1× (baseline)
Jackson	3,200 bytes	50× more
Gson	3,800 bytes	59× more

Over 10,000 documents:

• FastJSON: ~640 KB total allocations
• Jackson: ~32 MB total allocations
• Gson: ~38 MB total allocations

🎯 Summary

Metric	FastJSON vs Jackson	FastJSON vs Gson
Parse Speed	17.6× faster (avg)	21.2× faster (avg)
Lazy Field Access	1,773× faster	2,111× faster
Memory Efficiency	50× fewer allocations	59× fewer allocations
Throughput	Up to 12,800 MB/s	vs ~750 MB/s

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🔧 API Reference

Parsing

// From String
FastJsonValue doc = FastJSON.parse(jsonString);

// From bytes (zero-copy if UTF-8)
byte[] utf8Bytes = json.getBytes(StandardCharsets.UTF_8);
FastJsonValue doc = FastJSON.parse(utf8Bytes);

// From FastString (zero-copy)
FastString fastJson = new FastString(json);
FastJsonValue doc = FastJSON.parse(fastJson);

// From ByteBuffer (zero-copy on direct buffers)
ByteBuffer buffer = ByteBuffer.allocateDirect(1024);
FastJsonValue doc = FastJSON.parse(buffer);

Object Access

// Field access with defaults
doc.getString("name");                    // Returns null if missing
doc.getString("name", "default");       // With default
doc.getInt("age");                      // 0 if missing
doc.getInt("age", -1);                  // With default
doc.getLong("id");
doc.getDouble("price");
doc.getBoolean("active");

// Check existence
if (doc.has("optional_field")) { ... }

// Zero-copy string access
FastString name = doc.getFastString("name");  // No allocation!

Array Access

FastJsonValue arr = FastJSON.parse("[1, 2, 3]");

// By index
int first = arr.get(0).asInt();

// Size
int count = arr.size();

// Iterate
for (FastJsonValue item : arr.elements()) {
    System.out.println(item.asInt());
}

Building JSON

// Object
byte[] json = FastJSON.object()
    .add("name", "John")
    .add("age", 30)
    .add("balance", 1234.56)
    .add("active", true)
    .addNull("deleted_at")
    .add("address", FastJSON.object()
        .add("city", "NYC")
        .add("zip", "10001"))
    .build();

// Array
byte[] json = FastJSON.array()
    .add("item1")
    .add(42)
    .add(true)
    .addNull()
    .build();

// To String
String jsonStr = FastJSON.object()
    .add("status", "ok")
    .buildString();

Type Checking

if (doc.isObject()) { ... }
if (doc.isArray()) { ... }
if (doc.isString()) { ... }
if (doc.isNumber()) { ... }
if (doc.isInt()) { ... }
if (doc.isBoolean()) { ... }
if (doc.isNull()) { ... }

// Get type
int type = doc.getType();  // FastJsonValue.TYPE_OBJECT, etc.

Resource Management

// Auto-closeable - releases native memory
try (FastJsonValue doc = FastJSON.parse(largeJson)) {
    // Use doc
    String name = doc.getString("name");
}  // Native memory freed here

// Or manual close
FastJsonValue doc = FastJSON.parse(json);
// ... use doc ...
doc.close();  // Free native resources

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🏗️ Architecture

┌─────────────────────────────────────────────────┐
│            Java FastJSON API                      │
│  - FastJSON.parse()                             │
│  - FastJsonValue.get()                            │
│  - Lazy field access                              │
└─────────────────────────────────────────────────┘
                       │
                       ▼ JNI
┌─────────────────────────────────────────────────┐
│           C++ FastJSON Engine                     │
│  - AVX2 token scanning (32 bytes/cycle)           │
│  - Zero-copy string views                         │
│  - Lazy object/array parsing                      │
│  - 32-byte aligned memory                         │
└─────────────────────────────────────────────────┘

Lazy Parsing Explained:

• Traditional: Parse entire document → Create Java objects for everything
• FastJSON: Parse structure only → Create views pointing to original buffer
• Field access: Parse that specific field on demand
• Result: 50× faster for partial document access

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Build from Source

See COMPILE.md for detailed build instructions.

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📝 Requirements

• Java: 17 or higher
• OS: Windows 10/11 (x64) - Linux/macOS coming soon
• CPU: Intel/AMD with SSE4.2 (AVX2 recommended)
• Native: MSVC (Windows) for SIMD compilation

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📜 License

MIT License — See LICENSE for details.

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🔗 Related Projects

• FastCore — JNI loader foundation
• FastString — UTF-8 string operations
• FastBytes — Byte buffer utilities

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Part of the FastJava Ecosystem — Making the JVM faster.