1. 程式人生 > >高效能序列化框架FST

高效能序列化框架FST

fst是完全相容JDK序列化協議的系列化框架,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>
 測試程式碼
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 對比測試:"); 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]耗時:" + (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]耗時:" + (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]耗時:" + (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; } }
 結果
序列化 , 反序列化 對比測試:
原生序列化方案[序列化10000次]耗時:458ms size:=1160000
fst序列化方案[序列化10000次]耗時:184ms size:=550000
kryo序列化方案[序列化10000次]耗時:462ms size:=390000
 工具類
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原生序列換方案
	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);
		}
	}
}