Java序列化
Java提供了一種對(duì)象序列化的機(jī)制,該機(jī)制中,一個(gè)對(duì)象可以被表示為一個(gè)字節(jié)序列化,該字節(jié)序列化包括該對(duì)象的數(shù)據(jù),有關(guān)對(duì)象的類(lèi)型的信息和存儲(chǔ)在對(duì)象中的數(shù)據(jù)類(lèi)型。
將序列化對(duì)象寫(xiě)入文件后,可以從文件中讀取出來(lái),并且對(duì)它進(jìn)行反序列化,也就是說(shuō),對(duì)象的類(lèi)型信息、對(duì)象的數(shù)據(jù),還有對(duì)象中的數(shù)據(jù)類(lèi)型可用用來(lái)在內(nèi)存中新建對(duì)象。
整個(gè)過(guò)程都是java虛擬機(jī)(JVM)獨(dú)立的,也就是說(shuō),在一個(gè)平臺(tái)上序列化的對(duì)象可以在另一個(gè)完全不同的平臺(tái)上反序列化該對(duì)象。
一個(gè)類(lèi)的對(duì)象想要序列化成功需要滿足:
1、該類(lèi)必須實(shí)現(xiàn)java.io.Serializable接口。
2、該類(lèi)中所有屬性必須是可序列化的,如果有一個(gè)屬性不可序列化,則該屬性必須注明是短暫的(transient)
注意
當(dāng)序列化一個(gè)對(duì)象到文件時(shí),按照J(rèn)ava的標(biāo)準(zhǔn)約定是給文件一個(gè).ser擴(kuò)展名(只是約定)
對(duì)于jvm可以反序列化對(duì)象,它必須是能夠找到字節(jié)碼的類(lèi),如果jvm在反序列化對(duì)象的過(guò)程中找不到該類(lèi),則拋出一個(gè)ClassNotFoundException異常。
@Data
@ToString
public class SerializeEntiy implements Serializable {
private String name;
private String address;
private transient int SSN;
private int number;
}
public class SerializeDemo {
public static void main(String[] args) {
//序列化
serialize();
//反序列化
deserialization();
}
//反序列化
private static void deserialization() {
SerializeEntiy serialize = null;
try {
FileInputStream fileInput = new FileInputStream("/Users/Desktop/serilaize/serialize.ser");
ObjectInputStream input = new ObjectInputStream(fileInput);
serialize = (SerializeEntiy) input.readObject();
input.close();
fileInput.close();
System.out.println(serialize);
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
} catch (ClassNotFoundException e) {
e.printStackTrace();
}
}
//序列化
private static void serialize() {
SerializeEntiy serialize = new SerializeEntiy();
serialize.setName("序列化");
serialize.setAddress("北京市朝陽(yáng)區(qū)酒仙橋中路24號(hào)院");
serialize.setNumber(878);
serialize.setSSN(11);
try {
FileOutputStream fileOut = new FileOutputStream("/Users/Desktop/serilaize/serialize.ser");
ObjectOutputStream out = new ObjectOutputStream(fileOut);
out.writeObject(serialize);
out.close();
fileOut.close();
System.out.println("Serialized data is saved in /Users/qiangzhang/Desktop/serilaize/serialize.ser");
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
}
字段無(wú)法序列化的幾種場(chǎng)景:
1、靜態(tài)變量不會(huì)序列化
2、transient關(guān)鍵字指定的屬性
3、子類(lèi)實(shí)現(xiàn)Serializable接口而父類(lèi)沒(méi)有實(shí)現(xiàn)時(shí),父類(lèi)中的屬性是不會(huì)序列化的(父類(lèi)實(shí)現(xiàn)了子類(lèi)可以不用實(shí)現(xiàn))
4、當(dāng)序列化的類(lèi)的serializversionUID 發(fā)生改變時(shí),反序列化會(huì)失敗
主流的序列化技術(shù)有哪些:
JSON/Hessian(2)/xml/protobuf/kryo/MsgPack/FST/thrift/protosbuff/Avro
FST/kryo不支持跨語(yǔ)言
實(shí)現(xiàn)工具:(因環(huán)境不同,測(cè)試結(jié)果也有不同)

JSON
<!-- google -->
<dependency>
<groupId>org.codehaus.jackson</groupId>
<artifactId>jackson-mapper-asl</artifactId>
<version>1.9.2</version>
</dependency>
<!-- alibaba -->
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>1.2.74</version>
</dependency>
性能分析:(可能會(huì)有差)Google的Jackson的序列化性能比Alibaba的fastjson性能要好,Alibaba的fastjson的反序列化性能比Google的Jackson性能要好,各有長(zhǎng)短
public static void main(String[] args) throws IOException {
excuteWithJackson();
excuteWithFastJson();
}
//谷歌
protected static void excuteWithJackson() throws IOException {
User user = new User();
user.setName("zhang");
user.setAge(18);
byte[] bytes = null;
ObjectMapper objectMapper = new ObjectMapper();
long start = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
bytes = objectMapper.writeValueAsBytes(user);
}
System.out.println("Jackson序列化,time:" + (System.currentTimeMillis() - start) + "ms,總大小->" + bytes.length);
long start1 = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
User user1 = objectMapper.readValue(bytes, User.class);
}
System.out.println("Jackson反序列化,time:" + (System.currentTimeMillis() - start1) + "ms,總大小->" + bytes.length);
// System.out.println(user1);
}
//alibaba
protected static void excuteWithFastJson() {
User user = new User();
user.setName("zhang");
user.setAge(18);
String json = null;
long start = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
json = JSON.toJSONString(user);
}
System.out.println("FastJson序列化,time:" + (System.currentTimeMillis() - start) + "ms,總大小->" + json.getBytes().length);
long start1 = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
User user1 = JSON.parseObject(json, User.class);
}
System.out.println("FastJson反序列化,time:" + (System.currentTimeMillis() - start1) + "ms,總大小->" + json.getBytes().length);
}
結(jié)果:
Jackson序列化,time:60ms,總大小->25
Jackson反序列化,time:65ms,總大小->25
FastJson序列化,time:80ms,總大小->25
FastJson反序列化,time:40ms,總大小->25
protobuff(Google)
性能:壓縮率高(字節(jié)數(shù)?。?,耗時(shí)短
<dependency>
<groupId>com.baidu</groupId>
<artifactId>jprotobuf</artifactId>
<version>2.4.4</version>
</dependency>
protected static void excuteWithProtoBuff() throws IOException {
User user = new User();
user.setName("zhang");
user.setAge(18);
byte[] encode = null;
Codec<User> userCodec = ProtobufProxy.create(User.class, false);
long start = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
encode = userCodec.encode(user);
}
System.out.println("ProtoBuff序列化,time:" + (System.currentTimeMillis() - start) + "ms,總大小->" + encode.length);
long start1 = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
User user1 = userCodec.decode(encode);
}
System.out.println("ProtoBuff反序列化,time:" + (System.currentTimeMillis() - start1) + "ms");
}
ProtoBuff序列化,time:29ms,總大小->9
ProtoBuff反序列化,time:2ms
Hessian
性能:壓縮率比較低(字節(jié)數(shù)大),時(shí)間短
<dependency>
<groupId>com.caucho</groupId>
<artifactId>hessian</artifactId>
<version>4.0.63</version>
</dependency>
protected static void excuteWithHessian() throws IOException {
User user = new User();
user.setName("zhang");
user.setAge(18);
ByteArrayOutputStream os = new ByteArrayOutputStream();
HessianOutput hessianOutput = new HessianOutput(os);
long start = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
hessianOutput.writeObject(user);
if(i == 1){
System.out.println("總大小->" +os.toByteArray().length);
}
}
System.out.println("Hessian序列化,time:" + (System.currentTimeMillis() - start) + "ms,");
HessianInput hessianInput = new HessianInput(new ByteArrayInputStream(os.toByteArray()));
long start1 = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
User user1 = (User)hessianInput.readObject();
}
System.out.println("Hessian反序列化,time:" + (System.currentTimeMillis() - start1) + "ms");
}
總大小->61
Hessian序列化,time:2ms,
Hessian反序列化,time:5ms