转自:https://blog.csdn.net/z69183787/article/details/53005961 fst是完全兼容JDK序列化协议的系列化框架,序列化速度大概是JDK的4-10倍,大小是JDK大小的1/3左右。
首先引入pom
<dependency>
<groupId>de.ruedigermoeller</groupId>
<artifactId>fst</artifactId>
<version>2.04</version>
</dependency>
package zookeeper.seria; import java.io.Serializable; public class FSTSeriazle { public static void main(String[] args) {
User bean = new User();
bean.setUsername("xxxxx");
bean.setPassword("123456");
bean.setAge(1000000);
System.out.println("序列化 , 反序列化 对比测试:");
long size = 0;
long time1 = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
byte[] jdkserialize = JRedisSerializationUtils.jdkserialize(bean);
size += jdkserialize.length;
JRedisSerializationUtils.jdkdeserialize(jdkserialize);
}
System.out.println("原生序列化方案[序列化10000次]耗时:"
+ (System.currentTimeMillis() - time1) + "ms size:=" + size); size = 0;
long time2 = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
byte[] serialize = JRedisSerializationUtils.serialize(bean);
size += serialize.length;
User u = (User) JRedisSerializationUtils.unserialize(serialize);
}
System.out.println("fst序列化方案[序列化10000次]耗时:"
+ (System.currentTimeMillis() - time2) + "ms size:=" + size);
size = 0;
long time3 = System.currentTimeMillis();
for (int i = 0; i < 10000; i++) {
byte[] serialize = JRedisSerializationUtils.kryoSerizlize(bean);
size += serialize.length;
User u = (User) JRedisSerializationUtils.kryoUnSerizlize(serialize);
}
System.out.println("kryo序列化方案[序列化10000次]耗时:"
+ (System.currentTimeMillis() - time3) + "ms size:=" + size); } } class User implements Serializable{ private String username;
private int age;
private String password; public String getUsername() {
return username;
} public void setUsername(String username) {
this.username = username;
} public int getAge() {
return age;
} public void setAge(int age) {
this.age = age;
} public String getPassword() {
return password;
} public void setPassword(String password) {
this.password = password;
} }
结果
序列化 , 反序列化 对比测试:
原生序列化方案[序列化10000次]耗时:458ms size:=1160000
fst序列化方案[序列化10000次]耗时:184ms size:=550000
kryo序列化方案[序列化10000次]耗时:462ms size:=390000
工具类
package zookeeper.seria; import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream; import org.nustaq.serialization.FSTConfiguration; import com.esotericsoftware.kryo.Kryo;
import com.esotericsoftware.kryo.io.Input;
import com.esotericsoftware.kryo.io.Output; public class JRedisSerializationUtils { public JRedisSerializationUtils() {
} static FSTConfiguration configuration = FSTConfiguration
// .createDefaultConfiguration();
.createStructConfiguration(); public static byte[] serialize(Object obj) {
return configuration.asByteArray(obj);
} public static Object unserialize(byte[] sec) {
return configuration.asObject(sec);
} public static byte[] kryoSerizlize(Object obj) {
Kryo kryo = new Kryo();
byte[] buffer = new byte[2048];
try(
Output output = new Output(buffer);
) { kryo.writeClassAndObject(output, obj);
return output.toBytes();
} catch (Exception e) {
}
return buffer;
} static Kryo kryo = new Kryo();
public static Object kryoUnSerizlize(byte[] src) {
try(
Input input = new Input(src);
){
return kryo.readClassAndObject(input);
}catch (Exception e) {
}
return kryo;
} // jdk原生序列换方案
public static byte[] jdkserialize(Object obj) {
try (ByteArrayOutputStream baos = new ByteArrayOutputStream();
ObjectOutputStream oos = new ObjectOutputStream(baos);) {
oos.writeObject(obj);
return baos.toByteArray();
} catch (IOException e) {
throw new RuntimeException(e);
}
} public static Object jdkdeserialize(byte[] bits) {
try (ByteArrayInputStream bais = new ByteArrayInputStream(bits);
ObjectInputStream ois = new ObjectInputStream(bais); ) {
return ois.readObject();
} catch (Exception e) {
throw new RuntimeException(e);
}
}
}