序列化战争：主流序列化框架Benchmark
序列化战争：主流序列化框架Benchmark
GitHub上有这样一个关于序列化的Benchmark，被好多文章引用。但这个项目考虑到完整性，代码有些复杂。为了个人学习，自己实现了个简单的Benchmark测试类，也算是总结一下当今主流序列化框架的用法。
1.序列化的战争
按照序列化后的数据格式，主流的序列化框架主要可以分为四大类：JSON、二进制、XML、RPC。从更高层次来说，JSON和XML都可以算作是文本类的，而RPC类因为不只是序列化，框架往往还提供了底层RPC以及跨语言代码生成等基础设施，所以单列作一类。具体说来，本次测试涵盖了以下这些：
- JSON类
- 非常流行的Jackson
- Google的Gson
- 类JSON的MessagePack
- 阿里的FastJSON
- 二进制类
- XML类
- StAX(Streaming API for XML)
- Thoughwork的XStream
- RPC类
- Protobuf：这里“偷了点懒”，因为Protobuf和Thrift都要安装、编译，所以这里使用了Protostuff，可以在运行时自动获取对象的Schema信息，省去了额外安装和手动编写协议格式文件的过程(Protostuff真是太好了！)。
- Thrift、Apache Avro：同上，都需要预编译。
Why does Jackson-JSON call BSON the “smile format” of JSON?
BSON and Smile are two distinct binary formats. They are related in that they are both based on the logical format of JSON (i.e., key-value objects) but they are distinct in that they write incompatible binary formats (you can neither directly read Smile as BSON nor vice-versa). They also have different incompatible features (e.g., BSON defines a date type, while Smile does not as far as I can tell.) BSON is the binary serialization used by MongoDB for network transfer and disk serialization. Smile is the binary JSON format used by the Jackson project.
<!-- JSON BEGIN -->
<dependency>
<groupId>com.fasterxml.jackson.core</groupId>
<artifactId>jackson-databind</artifactId>
<version>2.5.4</version>
</dependency>
<dependency>
<groupId>com.fasterxml.jackson.module</groupId>
<artifactId>jackson-module-afterburner</artifactId>
<version>2.5.4</version>
</dependency>
<dependency>
<groupId>com.fasterxml.jackson.module</groupId>
<artifactId>jackson-module-scala_2.10</artifactId>
<version>2.5.3</version>
</dependency>
<dependency>
<groupId>com.google.code.gson</groupId>
<artifactId>gson</artifactId>
<version>2.3.1</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>1.2.6</version>
</dependency>
<dependency>
<groupId>io.fastjson</groupId>
<artifactId>boon</artifactId>
<version>0.33</version>
</dependency>
<!-- JSON END -->
<!-- JSON-like BEGIN -->
<dependency>
<groupId>com.fasterxml.jackson.dataformat</groupId>
<artifactId>jackson-dataformat-smile</artifactId>
<version>2.5.4</version>
</dependency>
<dependency>
<groupId>org.msgpack</groupId>
<artifactId>msgpack</artifactId>
<version>0.6.12</version>
</dependency>
<dependency>
<groupId>org.mongodb</groupId>
<artifactId>bson</artifactId>
<version>3.0.2</version>
</dependency>
<dependency>
<groupId>com.fasterxml.jackson.dataformat</groupId>
<artifactId>jackson-dataformat-yaml</artifactId>
<version>2.5.4</version>
</dependency>
<!-- JSON-like END -->
<!-- Binary BEGIN -->
<dependency>
<groupId>com.caucho</groupId>
<artifactId>hessian</artifactId>
<version>4.0.38</version>
</dependency>
<dependency>
<groupId>de.ruedigermoeller</groupId>
<artifactId>fst</artifactId>
<version>2.31</version>
</dependency>
<dependency>
<groupId>com.esotericsoftware</groupId>
<artifactId>kryo</artifactId>
<version>3.0.2</version>
</dependency>
<!-- Binary END -->
<!-- XML BEGIN -->
<dependency>
<groupId>com.thoughtworks.xstream</groupId>
<artifactId>xstream</artifactId>
<version>1.4.8</version>
</dependency>
<dependency>
<groupId>com.fasterxml</groupId>
<artifactId>aalto-xml</artifactId>
<version>0.9.11</version>
</dependency>
<!-- XML END -->
<!-- RPC BEGIN -->
<dependency>
<groupId>io.protostuff</groupId>
<artifactId>protostuff-core</artifactId>
<version>1.3.5</version>
</dependency>
<dependency>
<groupId>io.protostuff</groupId>
<artifactId>protostuff-runtime</artifactId>
<version>1.3.5</version>
</dependency>
<dependency>
<groupId>org.apache.avro</groupId>
<artifactId>avro</artifactId>
<version>1.7.7</version>
</dependency>
<!-- RPC END -->2.Benchmark代码
2.1 测试对象
用Serializer接口实现表示不同的序列化框架，作为测试对象集合。测试主要关注序列化数据大小、序列化时间消耗、反序列化时间消耗三个指标。
public class SerializerBenchmark {
private static final int WARMUP_COUNT = 100;
private static final int TEST_COUNT = 1000 * 1000;
/** Column index */
private static final int COL_SER_SIZE = 0;
private static final int COL_SER_COST = 1;
private static final int COL_DER_COST = 2;
/** Dictionary for random generation */
private static final char[] ALPHA =
"abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ".toCharArray();
public static void main(String[] args) throws Exception {
Serializer[] serializers =
{
// ============= JSON ==============
new Serializer<Person>() {
private ObjectMapper mapper = new ObjectMapper();
@Override
public String name() {
return "Jackson";
}
@Override
public byte[] serialize(Person obj) throws Exception {
return mapper.writeValueAsBytes(obj);
}
@Override
public Person deserialize(byte[] data, Class<Person> type) throws Exception {
return mapper.readValue(data, type);
}
},
new Serializer<Person>() {
private Gson gson = new GsonBuilder().create();
@Override
public String name() {
return "Gson";
}
@Override
public byte[] serialize(Person obj) {
return gson.toJson(obj).getBytes();
}
@Override
public Person deserialize(byte[] data, Class<Person> type) {
return gson.fromJson(new String(data), type);
}
},
new Serializer<Person>() {
@Override
public String name() {
return "FastJSON";
}
@Override
public byte[] serialize(Person obj) {
return JSON.toJSONBytes(obj);
}
@Override
public Person deserialize(byte[] data, Class<Person> type) {
return JSON.parseObject(data, type);
}
},
// ============= JSON-like ==============
new Serializer<Person>() {
private ObjectMapper mapper = new ObjectMapper(new SmileFactory());
@Override
public String name() {
return "Jackson-smile";
}
@Override
public byte[] serialize(Person obj) throws Exception {
return mapper.writeValueAsBytes(obj);
}
@Override
public Person deserialize(byte[] data, Class<Person> type) throws Exception {
return mapper.readValue(data, type);
}
},
new Serializer<Person>() {
private ObjectMapper mapper = new ObjectMapper(new SmileFactory());
{
mapper.registerModule(new AfterburnerModule());
}
@Override
public String name() {
return "Jackson-smile-afterburner";
}
@Override
public byte[] serialize(Person obj) throws Exception {
return mapper.writeValueAsBytes(obj);
}
@Override
public Person deserialize(byte[] data, Class<Person> type) throws Exception {
return mapper.readValue(data, type);
}
},
new Serializer<Person>() {
private ObjectMapper mapper = new ObjectMapper(new SmileFactory());
{
mapper.registerModule(new DefaultScalaModule());
}
@Override
public String name() {
return "Jackson-smile-scala";
}
@Override
public byte[] serialize(Person obj) throws Exception {
return mapper.writeValueAsBytes(obj);
}
@Override
public Person deserialize(byte[] data, Class<Person> type) throws Exception {
return mapper.readValue(data, type);
}
},
new Serializer<Person>() {
private ObjectMapper mapper = new ObjectMapper(new YAMLFactory());
@Override
public String name() {
return "Jackson-yaml";
}
@Override
public byte[] serialize(Person obj) throws Exception {
return mapper.writeValueAsBytes(obj);
}
@Override
public Person deserialize(byte[] data, Class<Person> type) throws Exception {
return mapper.readValue(data, type);
}
},
new Serializer<Person>() {
private MessagePack msgpack = new MessagePack();
{
msgpack.register(Person.class);
}
@Override
public String name() {
return "MessagePack";
}
@Override
public byte[] serialize(Person obj) throws Exception {
return msgpack.write(obj);
}
@Override
public Person deserialize(byte[] data, Class type) throws Exception {
return msgpack.read(data, Person.class);
}
},
// ============= Binary ==============
new Serializer<Person>() {
private Schema<Person> schema = RuntimeSchema.getSchema(Person.class);
private LinkedBuffer buffer = LinkedBuffer.allocate();
@Override
public String name() {
return "Protostuff";
}
@Override
public byte[] serialize(Person obj) {
byte[] data = ProtobufIOUtil.toByteArray(obj, schema, buffer);
buffer.clear();
return data;
}
@Override
public Person deserialize(byte[] data, Class<Person> type) {
Person obj = new Person();
ProtobufIOUtil.mergeFrom(data, obj, schema);
return obj;
}
},
new Serializer<Person>() {
@Override
public String name() {
return "Hessian";
}
@Override
public byte[] serialize(Person obj) throws Exception {
ByteArrayOutputStream bytes = new ByteArrayOutputStream();
Hessian2Output output = new Hessian2Output(bytes);
output.writeObject(obj);
output.close(); // flush to avoid EOF error
return bytes.toByteArray();
}
@Override
public Person deserialize(byte[] data, Class<Person> type) throws Exception {
Hessian2Input input = new Hessian2Input(new ByteArrayInputStream(data));
return (Person) input.readObject();
}
},
new Serializer<Person>() {
private FSTObjectInput input = new FSTObjectInput();
private FSTObjectOutput output = new FSTObjectOutput();
@Override
public String name() {
return "FST";
}
@Override
public byte[] serialize(Person obj) throws Exception {
output.resetForReUse();
output.writeObject(obj);
return output.getCopyOfWrittenBuffer();
}
@Override
public Person deserialize(byte[] data, Class<Person> type) throws Exception {
input.resetForReuseUseArray(data);
return (Person) input.readObject();
}
},
new Serializer<Person>() {
private Kryo kryo = new Kryo();
{
kryo.setReferences(false);
kryo.setRegistrationRequired(true);
kryo.register(Person.class);
}
private byte[] buffer = new byte[512];
private Output output = new Output(buffer, -1);
private Input input = new Input(buffer);
@Override
public String name() {
return "Kryo";
}
@Override
public byte[] serialize(Person obj) {
output.setBuffer(buffer, -1); // reset
kryo.writeObject(output, obj);
return output.toBytes();
}
@Override
public Person deserialize(byte[] data, Class<Person> type) {
input.setBuffer(data);
return kryo.readObject(input, type);
}
},
new Serializer<Person>() {
@Override
public String name() {
return "JDK Built-in";
}
@Override
public byte[] serialize(Person obj) throws Exception {
ByteArrayOutputStream out = new ByteArrayOutputStream();
new ObjectOutputStream(out).writeObject(obj);
return out.toByteArray();
}
@Override
public Person deserialize(byte[] data, Class<Person> type) throws Exception {
return (Person) new ObjectInputStream(new ByteArrayInputStream(data)).readObject();
}
},
// ============= XML ==============
new Serializer<Person>() {
private XStream xstream = new XStream();
@Override
public String name() {
return "XStream";
}
@Override
public byte[] serialize(Person obj) throws Exception {
ByteArrayOutputStream out = new ByteArrayOutputStream();
xstream.toXML(obj, out);
return out.toByteArray();
}
@Override
public Person deserialize(byte[] data, Class<Person> type) throws Exception {
return (Person) xstream.fromXML(new ByteArrayInputStream(data));
}
},
};
// Sheet
int[] testCase = { 10, 100, 1000 };
String[] sheetNames = new String[testCase.length];
for (int i = 0; i < sheetNames.length; i++) {
sheetNames[i] = "Size=" + testCase[i];
}
// Row
String[] rowNames = new String[serializers.length];
for (int i = 0; i < rowNames.length; i++) {
rowNames[i] = serializers[i].name();
}
// Column
String[] colNames = new String[3];
colNames[0] = "Size";
colNames[1] = "Ser";
colNames[2] = "Der";
Reporter reporter = new Reporter(sheetNames, rowNames, colNames);
for (int i = 0; i < testCase.length; i++) {
int length = testCase[i];
System.out.printf("===== Round [%d]: %d =====\n", i, length);
for (int j = 0; j < serializers.length; j++) {
testSerializer(reporter, length, i, j, serializers[j]);
}
}
System.out.println(reporter.generateFinalReport());
}
...
}2.2 测试Runner
每轮测试前都先Warmup并GC，避免JIT和GC对测试的影响。同时，Warmup时检测序列化和反序列化的正确性。
private static void testSerializer(Reporter reporter,
int length,
int sheet,
int row,
Serializer<Person> serializer)
throws Exception {
System.out.println("===== " + serializer.name() + " =====");
// 1.Warm-up and validate
System.out.println("Pre-warmup & Check correctness...");
Person p1 = newPerson(length);
for (int i = 0; i < WARMUP_COUNT; i++) {
byte[] bytes = serializer.serialize(p1);
Person p2 = serializer.deserialize(bytes, Person.class);
if (!p1.equals(p2)) {
throw new IllegalStateException(p1 + " not equals to " + p2);
}
}
int serSize = serializer.serialize(p1).length;
System.out.printf("%s serialization size[%d]\n", serializer.name(), serSize);
reporter.report(sheet, row, COL_SER_SIZE, serSize);
doGc();
// 2.Serialization
long startTime = System.currentTimeMillis();
for (int i = 0; i < TEST_COUNT; i++) {
serializer.serialize(p1);
}
long serCostTime = System.currentTimeMillis() - startTime;
System.out.printf("%s serialization benchmark[%d]\n", serializer.name(), serCostTime);
reporter.report(sheet, row, COL_SER_COST, serCostTime);
// Warm up again
for (int i = 0; i < WARMUP_COUNT; i++) {
byte[] bytes = serializer.serialize(p1);
serializer.deserialize(bytes, Person.class);
}
doGc();
// 3.De-Serialization
byte[] bytes = serializer.serialize(p1);
startTime = System.currentTimeMillis();
for (int i = 0; i < TEST_COUNT; i++) {
serializer.deserialize(bytes, Person.class);
}
long derCostTime = System.currentTimeMillis() - startTime;
System.out.printf("%s de-serialization benchmark[%d]\n", serializer.name(), derCostTime);
reporter.report(sheet, row, COL_DER_COST, derCostTime);
System.out.println();
}3.测试报告
3.1 报告生成
这里“偷了点小懒”，用Apache Common Lang提供的StringUtils中的pad()方法排版。
static class Reporter {
private final String[] sheetNames;
private final String[] rowNames;
private final String[] colNames;
private final long[][][] table;
Reporter(String[] sheetNames,
String[] rowNames,
String[] colNames) {
this.sheetNames = sheetNames;
this.rowNames = rowNames;
this.colNames = colNames;
this.table = new long[sheetNames.length]
[rowNames.length]
[colNames.length];
}
public void report(int sheet, int row, int col, long val) {
table[sheet][row][col] = val;
}
public String generateFinalReport() {
StringBuilder report = new StringBuilder();
for (int i = 0; i < table.length; i++) {
report.append(center(sheetNames[i], 50, '*'))
.append("\n");
// 1.Header
final int width0 = 30;
final int width1 = 10;
report.append(rightPad("", width0));
for (String colName : colNames) {
report.append(rightPad(colName, width1));
}
report.append("\n");
// 2.Row
for (int j = 0; j < table[i].length; j++) {
report.append(rightPad(rowNames[j], width0));
for (int k = 0; k < table[i][j].length; k++) {
report.append(rightPad(
String.valueOf(table[i][j][k]), width1));
}
report.append("\n");
}
report.append("\n");
}
return report.toString();
}
}3.2 测试结果
测试结果可以简单总结如下：
- Kryo占用空间最小，其次是MessagePack和Protostuff(Protobuf)。
- Protostuff在不同数据长度下表现都非常出色！
- JSON以及类JSON框架中，Jackson+Smile格式+Afterburner模块的组合表现最好。
- XStream出奇地慢，印象中XStream挺快的吧，难道有优化参数没配？
*********************Size=10**********************
Size Ser Der
Jackson 39 602 758
Gson 38 1204 1181
FastJSON 38 573 608
Jackson-smile 35 415 465
Jackson-smile-afterburner 35 305 377
Jackson-smile-scala 34 522 590
Jackson-yaml 39 4233 5638
MessagePack 15 891 1075
Protostuff 17 148 130
Hessian 84 2459 1233
FST 73 334 481
Kryo 13 98 117
JDK Built-in 138 1462 4526
XStream 169 6088 13007
*********************Size=100*********************
Size Ser Der
Jackson 129 403 565
Gson 128 1056 1248
FastJSON 129 522 571
Jackson-smile 126 426 472
Jackson-smile-afterburner 126 454 371
Jackson-smile-scala 126 452 639
Jackson-yaml 129 5250 5330
MessagePack 108 948 976
Protostuff 107 172 192
Hessian 176 2528 1513
FST 163 288 470
Kryo 105 440 134
JDK Built-in 228 1332 4559
XStream 259 5913 12797
********************Size=1000*********************
Size Ser Der
Jackson 1029 1412 1411
Gson 1029 4614 3855
FastJSON 1029 2476 2011
Jackson-smile 1026 1052 1343
Jackson-smile-afterburner 1025 1105 1232
Jackson-smile-scala 1025 1058 1452
Jackson-yaml 1029 18983 13065
MessagePack 1008 2101 2010
Protostuff 1008 1172 838
Hessian 1075 4358 6587
FST 1063 1083 1567
Kryo 1005 2675 921
JDK Built-in 1128 2502 8537
XStream 1158 10633 16981 序列化战争：主流序列化框架Benchmark的更多相关文章
- DRF框架之Serializer序列化器的序列化操作
在DRF框架中,有两种序列化器,一种是Serializer,另一种是ModelSerializer. 今天,我们就先来学习一下Serializer序列化器. 使用Serializer序列化器的开发步骤 ...
- Flask（1）- 主流web框架、初识flask
一.Python 现阶段三大主流Web框架 Django.Tornado.Flask 对比 Django 主要特点是大而全,集成了很多组件(例如Models.Admin.Form等等), 不管你用得到 ...
- 主流RPC框架详解，以及与SOA、REST的区别
什么是RPC RPC(Remote Procedure Call Protocol)——远程过程调用协议,它是一种通过网络从远程计算机程序上请求服务,而不需要了解底层网络技术的协议. 简言之,RPC使 ...
- 一篇文章带你掌握主流办公框架——SpringBoot
一篇文章带你掌握主流办公框架--SpringBoot 在之前的文章中我们已经学习了SSM的全部内容以及相关整合 SSM是Spring的产品,主要用来简化开发,但我们现在所介绍的这款框架--Spring ...
- C#中的二进制序列化和Json序列化
序列化就是把一个对象变成流的形式,方便传输和还原.小弟不才,总结下对二进制序列化和Json序列化的使用: 1.首先,二进制序列化(BinaryFormatter)要求要序列化的类必须是可序列化的(即在 ...
- Django-Rest-Framework的序列化之serializers 序列化组件
Django-Rest-Framework的序列化之serializers 序列化组件 restful framework 正常的序列化 from django.http import HttpRes ...
- [LeetCode] Serialize and Deserialize BST 二叉搜索树的序列化和去序列化
Serialization is the process of converting a data structure or object into a sequence of bits so tha ...
- [LeetCode] Serialize and Deserialize Binary Tree 二叉树的序列化和去序列化
Serialization is the process of converting a data structure or object into a sequence of bits so tha ...
- 几款主流PHP框架的优缺点评比
PHP是一种在国内外都比较流行的开源服务器端脚本开发语言.能够适应大中小型项目的开发需求.我们将在这篇文章中向大家介绍几款主流PHP框架及其相关优缺点评比,作为一个参考分享给朋友们. 主要参考的PHP ...
随机推荐
- urlopen()&urlretrieve()
1.urlopen()方法 urllib.request.urlopen(url[,data[,proxies]]) 创建一个表示远程url的类文件对象,然后像本地文件一样的操作这个类文件对象来获取远 ...
- git checkout+文件丢失
坑:不知什么时候, 应该是初学git的时候, 在桌面git init了一下, 这次忘记切目录直接在桌面git checkout了, 导致文件丢失了. 解决: 简单复原: git reflog # 查看 ...
- js将一个数组插入另一个数组
var cont =[1,2,3,4]; var res =[4,5,6] for(var i=0;i<res;i++){ cont.push( res.data.list[i]); } con ...
- [LeetCode] Replace Words 替换单词
In English, we have a concept called root, which can be followed by some other words to form another ...
- js if for 详解 获取元素方式 及一些js 基础知识
##获取元素的新方法## --document.querySelector('Css Selector{css选择器}') 接收一个css选择器(通配,群组,类,包含,id....等) 若这个选择器对 ...
- ASwipeLayout一个强大的侧滑菜单控件
Android中侧滑的场景有很大,大部分是基于RecyclerView,但是有些时候你可以动态地addView到一个布局当中,也希望它实现侧滑,所以就产生了ASwipeLayout,该控件不仅支持在R ...
- HDU 1724 Ellipse
Problem Description Math is important!! Many students failed in 2+2’s mathematical test, so let's AC ...
- Go学习——new()和 make()的区别详解（转载）
这篇文章主要介绍了Go语言中new()和 make()的区别详解,本文讲解了new 的主要特性.make 的主要特性,并对它们的区别做了总结,需要的朋友可以参考下 概述 Go 语言中的 new 和 m ...
- AQS
AQS介绍 AQS,即AbstractQueuedSynchronizer, 队列同步器,它是Java并发用来构建锁和其他同步组件的基础框架. AQS的核心思想是基于volatile int stat ...
- 00-Unit_Common综述-RecyclerView封装
自学安卓也有一年的时间了,与代码相伴的日子里,苦乐共存.能坚持到现在确实已见到了"往日所未曾见证的风采".今2018年4月2日,决定用一个案例:Unit_Common,把安卓基础的 ...