用rocketMQ写文件传输有意义吗?
rt,我也不清楚用rocketMQ写文件传输是否有意义,突然觉得可以试一下,于是这么写了。我不清楚rocketMQ在这些场景是否存在优势,或者存在什么劣势,我只管写,写完之后我去对比,尝试,然后得出结论:我再也不会考虑使用rocketMQ来写文件同步了。
功能需求
本demo实现的功能是监听本地某个文件夹的文件创建和修改,并实现和服务器的同步。
环境配置
本文采用的环境如下:
Redis-x64-3.0.504
Apache RocketMQ-4.2.0
pom配置如下:
<?xml version="1.0" encoding="UTF-8"?><project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>2.2.4.RELEASE</version>
<relativePath/> <!-- lookup parent from repository -->
</parent>
<groupId>com.ezsyncxz</groupId>
<artifactId>efficiency</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>efficiency</name>
<description>How to improve transmission efficiency</description>
<properties>
<java.version>1.8</java.version>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.mybatis.spring.boot</groupId>
<artifactId>mybatis-spring-boot-starter</artifactId>
<version>2.1.1</version>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.directory.studio/org.apache.commons.io -->
<dependency>
<groupId>org.apache.directory.studio</groupId>
<artifactId>org.apache.commons.io</artifactId>
<version>2.4</version>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
<exclusions>
<exclusion>
<groupId>org.junit.vintage</groupId>
<artifactId>junit-vintage-engine</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>com.alibaba.rocketmq</groupId>
<artifactId>rocketmq-client</artifactId>
<version>3.2.6</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>druid</artifactId>
<version>1.0.9</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>
efficiency流程图
文件监听
参考代码:
package com.ezsyncxz.efficiency.fileMonitor;import org.apache.commons.io.monitor.FileAlterationListener;
import org.apache.commons.io.monitor.FileAlterationMonitor;
import org.apache.commons.io.monitor.FileAlterationObserver;
import java.io.File;
public class FileMonitor {
FileAlterationMonitor monitor = null;
public FileMonitor(long interval) {
monitor = new FileAlterationMonitor(interval);
}
public void monitor(String path, FileAlterationListener listener) {
FileAlterationObserver observer = new FileAlterationObserver(new File(path));
monitor.addObserver(observer);
observer.addListener(listener);
}
public void stop() throws Exception {
monitor.stop();
}
public void start() throws Exception {
monitor.start();
}
}
package com.ezsyncxz.efficiency.fileMonitor;import com.alibaba.rocketmq.client.exception.MQBrokerException;
import com.alibaba.rocketmq.client.exception.MQClientException;
import com.alibaba.rocketmq.remoting.exception.RemotingException;
import com.ezsyncxz.efficiency.data.DataCollection;
import com.ezsyncxz.efficiency.utils.ApplicationContextUtil;
import org.apache.commons.io.monitor.FileAlterationListener;
import org.apache.commons.io.monitor.FileAlterationObserver;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.File;
public class FileListener implements FileAlterationListener {
private static final Logger logger = LoggerFactory.getLogger(FileListener.class);
FileMonitor monitor = null;
@Override
public void onStart(FileAlterationObserver observer) {
// logger.warn("正在监控文件 文件夹:{}", observer.getDirectory().getAbsolutePath());
}
@Override
public void onDirectoryCreate(File directory) {
logger.warn("监控到文件夹创建动作,开始同步数据 文件夹:{}", directory.getName());
}
@Override
public void onDirectoryChange(File directory) {
logger.warn("监听到文件夹变化动作,开始增量同步 文件夹:{}", directory.getName());
}
@Override
public void onDirectoryDelete(File directory) {
logger.warn("监听到文件夹删除动作 文件夹:{}", directory.getName());
}
@Override
public void onFileCreate(File file) {
logger.warn("监听到文件新建动作,启动同步任务,开始文件同步 文件名:{}", file.getName());
try {
DataCollection dataCollection = ApplicationContextUtil.getBean(DataCollection.class);
dataCollection.collect(file.getAbsolutePath());
} catch (InterruptedException e) {
e.printStackTrace();
} catch (RemotingException e) {
e.printStackTrace();
} catch (MQClientException e) {
e.printStackTrace();
} catch (MQBrokerException e) {
e.printStackTrace();
}
}
@Override
public void onFileChange(File file) {
logger.warn("监听到文件变化动作,开始增量同步 文件名:{}", file.getName());
}
@Override
public void onFileDelete(File file) {
logger.warn("监听到文件删除动作 文件名:{}", file.getName());
}
@Override
public void onStop(FileAlterationObserver observer) {
// logger.warn("关闭文件监控");
}
}
监听文件夹,我们用到的是Apache的commons.io包。通过这个包,我们可以监听到文件、文件夹的创建和修改,这样我们就能针对文件的创建进行全量同步,文件的修改利用Rsync算法进行增量同步,对文件夹我们可以进行归档压缩的方式进行同步,当然也可以对文件夹进行递归同步,但是我觉得这样实现的话可能会比较麻烦。这里暂时是只实现了文件创建时候的同步动作。
文件采集
参考代码:
package com.ezsyncxz.efficiency.data;import com.alibaba.fastjson.JSONObject;
import com.alibaba.rocketmq.client.exception.MQBrokerException;
import com.alibaba.rocketmq.client.exception.MQClientException;
import com.alibaba.rocketmq.client.producer.DefaultMQProducer;
import com.alibaba.rocketmq.common.message.Message;
import com.alibaba.rocketmq.remoting.exception.RemotingException;
import com.ezsyncxz.efficiency.entity.FileFragment;
import com.ezsyncxz.efficiency.utils.ByteUtils;
import com.ezsyncxz.efficiency.utils.CompressUtils;
import com.ezsyncxz.efficiency.utils.FileUtils;
import com.ezsyncxz.efficiency.utils.MD5Utils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
import java.io.File;
import java.io.IOException;
/**
* @ClassName DataCollection
* @Description 采集指定文件夹数据,将数据读取,归档,分块写入消息队列中,rocketMq能够存入的消息大小最大为4MB,因此我们需要对过大的数据进行切割
* @Author chenwj
* @Date 2020/2/24 15:46
* @Version 1.0
**/
@Component
public class DataCollection {
private static final Logger logger = LoggerFactory.getLogger(DataCollection.class);
@Autowired
private DefaultMQProducer producer;
public static final String tar = "D:\chenwj\dev\test\efficiency_tar\";
/**
* 采集文件夹下所有的文件,包括文件夹
* @param src
*/
public void collect(String src) throws InterruptedException, RemotingException, MQClientException, MQBrokerException {
File file = new File(src);
String filename = file.getName();
// 文件不存在则返回
if(!file.exists()) {
logger.error("不存在该文件路径: {}", src);
return;
}
boolean needCompress = false;
// 读取文件为字节数组
byte[] message = FileUtils.File2byte(src);
int msgTotalSize = message.length;
int orderID = 0;
int maxSize = 3000000;
String tag = MD5Utils.MD54bytes(message);
int msgCount = (int) Math.ceil((message.length / maxSize));
// 切割消息,rocket能够接受的消息大小为4mb
while (message.length > maxSize) {
byte[] subBytes = ByteUtils.subBytes(message, 0, maxSize);
// 调用消息队列进行传输
FileFragment fileFragment = FileFragment.newBuilder()
.body(subBytes)
.msgCount(msgCount)
.needCompress(needCompress)
.tarPath(tar)
.filename(filename)
.score(orderID)
.build();
Message sendMessage = new Message("DemoTopic", tag, JSONObject.toJSONString(fileFragment).getBytes());
message = ByteUtils.subBytes(message, maxSize, message.length - maxSize);
producer.send(sendMessage, (mqs, msg, arg) -> {
int o = (int) arg;
int index = o % mqs.size();
return mqs.get(index);
}, orderID);
// logger.warn("发送的消息id为: {}", orderID);
orderID += 1;
}
// 传输最后一段消息
if(message.length > 0) {
// 调用消息队列进行传输
FileFragment fileFragment = FileFragment.newBuilder()
.needCompress(needCompress)
.body(message)
.msgCount(msgCount)
.tarPath(tar)
.filename(filename)
.score(orderID)
.build();
Message sendMessage = new Message("DemoTopic", tag, JSONObject.toJSONString(fileFragment).getBytes());
producer.send(sendMessage, (mqs, msg, arg) -> {
int o = (int) arg;
int index = o % mqs.size();
return mqs.get(index);
}, orderID);
// logger.warn("发送的消息id为:{}", orderID);
}
logger.warn("消息传输完毕 消息总大小:{}字节 消息总数:{} 消息哈希:{} 消息目标路径: {}", msgTotalSize, msgCount, tag, tar + filename);
}
}
文件采集程序实际上是将本地文件读取成字节数组,切割字节数组为一个个文件片段,因为本文采用的是rocketMq,rocketMq不支持大文件传输,他支持的每个消息大小为4mb,预保留对象结构可能占用的大小,我这里保守地每次传输3000000个字节,对于文件稍微大一点的数据传输可能会产生巨多的消息。这里发送顺序消息或者普通消息对结果不会有影响,只要对文件片段编号,消费者会根据编号顺序重组消息,所以消费者可以并发地消费消息,生产者也可以并发地生产消息。
消费端重组文件
package com.ezsyncxz.efficiency.consumer;import com.alibaba.fastjson.JSONObject;
import com.alibaba.rocketmq.common.message.MessageExt;
import com.ezsyncxz.efficiency.entity.FileFragment;
import com.ezsyncxz.efficiency.mq.annotation.MQConsumeService;
import com.ezsyncxz.efficiency.mq.entity.MQConsumeResult;
import com.ezsyncxz.efficiency.mq.processor.AbstractMQMsgProcessor;
import com.ezsyncxz.efficiency.redis.RedisUtil;
import com.ezsyncxz.efficiency.utils.ByteUtils;
import com.ezsyncxz.efficiency.utils.FileUtils;
import org.springframework.beans.factory.annotation.Autowired;
import java.util.List;
import java.util.Set;
/**
* @ClassName DataCollectionConsumer
* @Description TODO
* @Author chenwj
* @Date 2020/2/25 15:49
* @Version 1.0
**/
@MQConsumeService(topic = "DemoTopic", tags = {"*"})
public class DataCollectionConsumer extends AbstractMQMsgProcessor {
@Autowired
private RedisUtil redisUtil;
@Override
protected MQConsumeResult consumeMessage(String tag, List<String> keys, MessageExt messageExt) {
// logger.warn("{}接收到来自{}的消息,开始处理...", Thread.currentThread().getName(), tag);
try {
byte[] body = messageExt.getBody();
String bodyString = new String(body);
FileFragment fileFragment = JSONObject.parseObject(bodyString, FileFragment.class);
// logger.warn("接收到消息 消息编号:{}", fileFragment.getScore());
redisUtil.zsSetAndSorte(tag, bodyString, fileFragment.getScore());
// logger.warn("消息已写入缓存!");
// 当文件的所有片段读完,开始写入磁盘
byte[] fileBody = new byte[0];
long size = redisUtil.zsGetSize(tag);
if (size == fileFragment.getMsgCount()) {
Set<Object> objects = redisUtil.zsGetAsc(tag);
for (Object object : objects) {
String fragmentString = (String) object;
FileFragment fragment = JSONObject.parseObject(fragmentString, FileFragment.class);
fileBody = ByteUtils.concateBytes(fileBody, fragment.getBody());
}
FileUtils.byte2File(fileBody, fileFragment.getTarPath(), fileFragment.getFilename());
redisUtil.del(tag);
logger.warn("文件写入完毕!已删除缓存 文件路径:{}", fileFragment.getTarPath() + fileFragment.getFilename());
}
return MQConsumeResult.newBuilder().isSuccess(true).build();
}catch (Exception e) {
logger.warn("文件写入异常,删除缓存");
e.printStackTrace();
redisUtil.del(tag);
}
return MQConsumeResult.newBuilder().isSuccess(true).build();
}
}
消费端接收到文件片段之后会暂存到redis缓存,以tag,也就是文件哈希为键,片段编号为score存入到有序集合中,当文件全部读取完毕则从缓存中按正序取出拼接后写入磁盘,再删除缓存。
测试结果
从测试结果不难看出,用redis发生了并发的问题。问题不难分析,消费者并发地消费消息,没有加锁,所以在if (size == fileFragment.getMsgCount()) {
这里发生了并发问题,导致将文件多次写入磁盘,这种并发问题不会影响结果,因为不论文件多少次写入磁盘,结果都是一样的,但是它造成了不必要的浪费。
这里用到了redis应该是一大败笔,以前在工作中用到redis能明显的感觉到redis的维护是一个十分艰巨的过程,一不留心在redis中留下一点脏数据,长久之后就会变得难以维护,此外,redis是一个作为缓存数据库,他并不考虑被用作文件的中转缓存,因为文件太大了,他更多地被考虑缓存维护一些对象的中间状态,或者说作为影子设备的存在。因此在实现了以redis作为文件中转的方案后,我听取了一些大佬的意见,用RandomAccessFile对这一块进行改进。
用RandomAccessFile改进
改进后的DataCollection:
package com.ezsyncxz.efficiency.data;import com.alibaba.fastjson.JSONObject;
import com.alibaba.rocketmq.client.exception.MQBrokerException;
import com.alibaba.rocketmq.client.exception.MQClientException;
import com.alibaba.rocketmq.client.producer.DefaultMQProducer;
import com.alibaba.rocketmq.common.message.Message;
import com.alibaba.rocketmq.remoting.exception.RemotingException;
import com.ezsyncxz.efficiency.entity.FileFragment;
import com.ezsyncxz.efficiency.utils.ByteUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
import java.io.File;
import java.io.IOException;
import java.io.RandomAccessFile;
import java.util.UUID;
/**
* @ClassName DataCollection
* @Description 采集指定文件夹数据,将数据读取,归档,分块写入消息队列中,rocketMq能够存入的消息大小最大为4MB,因此我们需要对过大的数据进行切割
* @Author chenwj
* @Date 2020/2/24 15:46
* @Version 1.0
**/
@Component
public class DataCollection {
private static final Logger logger = LoggerFactory.getLogger(DataCollection.class);
@Autowired
private DefaultMQProducer producer;
public static final String tar = "D:\chenwj\dev\test\efficiency_tar\";
/**
* 采集文件夹下所有的文件,包括文件夹
*
* @param src
*/
public void collect(String src) throws IOException, InterruptedException, RemotingException, MQClientException, MQBrokerException {
File file = new File(src);
String filename = file.getName();
// 文件不存在则返回
if (!file.exists()) {
logger.error("不存在该文件路径: {}", src);
return;
}
// 用文件随机读写的方式读取文件片段
int len = 3000000; // 每个消息文件片段的大小
int off = 0; // 每个消息片段的偏移量
byte[] bytes = new byte[len]; // 缓冲接收文件
long length = file.length(); // 文件大小
RandomAccessFile r = new RandomAccessFile(src, "r");
int rLen = 0; // 每次读取的字节数
String tag = UUID.randomUUID().toString();
long startTime = System.currentTimeMillis();
while ((rLen = r.read(bytes)) > 0) {
if(rLen != bytes.length) {
bytes = ByteUtils.subBytes(bytes, 0, rLen);
logger.warn("最后一个文件不足{}B", len);
}
FileFragment fileFragment = FileFragment.newBuilder()
.filename(filename)
.tarPath(tar)
.body(bytes)
.needCompress(false)
.length(length)
.off(off)
.startTime(startTime)
.build();
Message sendMessage = new Message("DemoTopic", tag, JSONObject.toJSONString(fileFragment).getBytes());
producer.send(sendMessage);
off += rLen;
}
r.close();
}
public static void main(String[] args){
}
}
改进后的DataCollectionConsumer:
package com.ezsyncxz.efficiency.consumer;import com.alibaba.fastjson.JSONObject;
import com.alibaba.rocketmq.common.message.MessageExt;
import com.ezsyncxz.efficiency.entity.FileFragment;
import com.ezsyncxz.efficiency.mq.annotation.MQConsumeService;
import com.ezsyncxz.efficiency.mq.entity.MQConsumeResult;
import com.ezsyncxz.efficiency.mq.processor.AbstractMQMsgProcessor;
import com.ezsyncxz.efficiency.redis.RedisUtil;
import org.springframework.beans.factory.annotation.Autowired;
import java.io.*;
import java.util.List;
/**
* @ClassName DataCollectionConsumer
* @Description TODO
* @Author chenwj
* @Date 2020/2/25 15:49
* @Version 1.0
**/
@MQConsumeService(topic = "DemoTopic", tags = {"*"})
public class DataCollectionConsumer extends AbstractMQMsgProcessor {
@Autowired
private RedisUtil redisUtil;
@Override
protected MQConsumeResult consumeMessage(String tag, List<String> keys, MessageExt messageExt) {
// 用RandomAccessFile直接将拿到的片段写入磁盘
byte[] body = messageExt.getBody();
String bodyString = new String(body);
FileFragment fileFragment = JSONObject.parseObject(bodyString, FileFragment.class);
String tarPath = fileFragment.getTarPath();
String filename = fileFragment.getFilename();
String path = tarPath + File.separator + filename;
File file = new File(path);
if (!file.exists()) {
try {
file.createNewFile();
logger.warn("创建新文件 文件名: {}", file.getName());
} catch (IOException e) {
e.printStackTrace();
}
}
try {
RandomAccessFile w = new RandomAccessFile(path, "rw");
w.seek(fileFragment.getOff());
w.write(fileFragment.getBody());
logger.warn("写入文件片段 文件名:{} 偏移量:{}", filename, fileFragment.getOff());
w.close();
} catch (Exception e) {
e.printStackTrace();
}
long incr = redisUtil.incr(tag, fileFragment.getBody().length);
if(incr == fileFragment.getLength()) {
long endTime = System.currentTimeMillis();
logger.warn("文件写入完毕 总耗时:{}ms 文件:{}", endTime - fileFragment.getStartTime(), tarPath + File.separator + filename);
redisUtil.del(tag);
}
return MQConsumeResult.newBuilder().isSuccess(true).build();
}
}
之后测试文件同步,同步之后的文件对比文件哈希是没有任何问题的,证明同步是可以的。但是在同步一个800多MB的文件时,基于消息队列的同步方式花费了差不多40s,而直接建立socket连接的方式则差不多是8s左右。原因大概是通过消息队列的方式同步文件,存在对文件的多次io,在消费端,频繁地开启和关闭和本地磁盘的通道,花费了大量时间,以及多个消息在生产消费的过程中也存在时间消耗。此外,还测试了多个小文件同步,我原本想法是mq并发消费,在处理多个小文件同步上或许能够优于socket传输,事实证明,在多个小文件的传输上还是用socket更有优势,在776个小文件的传输中,mq的方式花费了22s左右,而socket的方式花费了8s左右。
用socket替换掉mq
替换后的DataCollection
package com.ezsyncxz.efficiency.data;import com.alibaba.rocketmq.client.exception.MQBrokerException;
import com.alibaba.rocketmq.client.exception.MQClientException;
import com.alibaba.rocketmq.client.producer.DefaultMQProducer;
import com.alibaba.rocketmq.remoting.exception.RemotingException;
import com.ezsyncxz.efficiency.utils.ByteUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
import java.io.*;
import java.net.InetSocketAddress;
import java.net.Socket;
/**
* @ClassName DataCollection
* @Description 采集指定文件夹数据,将数据读取,归档,分块写入消息队列中,rocketMq能够存入的消息大小最大为4MB,因此我们需要对过大的数据进行切割
* @Author chenwj
* @Date 2020/2/24 15:46
* @Version 1.0
**/
@Component
public class DataCollection {
private static final Logger logger = LoggerFactory.getLogger(DataCollection.class);
@Autowired
private DefaultMQProducer producer;
public static final String tar = "D:\chenwj\dev\test\efficiency_tar\";
/**
* 采集文件夹下所有的文件,包括文件夹
*
* @param src
*/
public void collect(String src) throws IOException, InterruptedException, RemotingException, MQClientException, MQBrokerException {
File file = new File(src);
String filename = file.getName();
// 文件不存在则返回
if (!file.exists()) {
logger.error("不存在该文件路径: {}", src);
return;
}
RandomAccessFile accessFile = new RandomAccessFile(src, "r");
int length = 0;
double sumL = 0 ;
byte[] sendBytes = null;
Socket socket = null;
DataOutputStream dos = null;
boolean bool = false;
try {
long l = file.length();
socket = new Socket();
socket.connect(new InetSocketAddress("127.0.0.1", 48123));
dos = new DataOutputStream(socket.getOutputStream());
sendBytes = new byte[1024];
//传输文件路径,前4个字节是长度
String fileName = file.getName();
String filePath = tar + File.separator + fileName;
int len = filePath.getBytes().length;
byte[] lenBytes = ByteUtils.intToByteArray(len);
byte[] bytes = ByteUtils.concateBytes(lenBytes, filePath.getBytes());
dos.write(bytes);
dos.flush();
// 传输文件内容
while ((length = accessFile.read(sendBytes)) > 0) {
sumL += length;
logger.warn("已传输:{}", ((sumL/l)*100)+"%");
dos.write(sendBytes, 0, length);
dos.flush();
}
if(sumL==l){
bool = true;
}
}catch (Exception e) {
System.out.println("客户端文件传输异常");
bool = false;
e.printStackTrace();
} finally{
if (dos != null)
dos.close();
if (socket != null)
socket.close();
}
if(bool) {
logger.warn("传输完毕!");
} else {
logger.warn("文件传输失败!");
}
}
}
新增服务端BxServerSocket代码:
package com.ezsyncxz.efficiency.socket;import java.io.DataInputStream;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.net.ServerSocket;
import java.net.Socket;
/**
* 接收文件服务
* @author admin_Hzw
*
*/
public class BxServerSocket {
/**
* 工程main方法
* @param args
*/
public static void main(String[] args) {
try {
final ServerSocket server = new ServerSocket(48123);
Thread th = new Thread(new Runnable() {
public void run() {
while (true) {
try {
System.out.println("开始监听...");
/*
* 如果没有访问它会自动等待
*/
Socket socket = server.accept();
System.out.println("有链接");
receiveFile(socket);
} catch (Exception e) {
System.out.println("服务器异常");
e.printStackTrace();
}
}
}
});
th.run(); //启动线程运行
} catch (Exception e) {
e.printStackTrace();
}
}
public void run() {
}
/**
* 接收文件方法
* @param socket
* @throws IOException
*/
public static void receiveFile(Socket socket) throws IOException {
byte[] inputByte = null;
int length = 0;
DataInputStream dis = null;
FileOutputStream fos = null;
try {
try {
dis = new DataInputStream(socket.getInputStream());
/*
* 文件存储位置
*/
int len = dis.readInt();
byte[] bytes = new byte[len];
dis.read(bytes);
java.lang.String filePath = new java.lang.String(bytes);
fos = new FileOutputStream(new File(filePath));
inputByte = new byte[1024];
System.out.println("开始接收数据...");
while ((length = dis.read(inputByte)) > 0) {
fos.write(inputByte, 0, length);
fos.flush();
}
System.out.println("完成接收:"+"");
} finally {
if (fos != null)
fos.close();
if (dis != null)
dis.close();
if (socket != null)
socket.close();
}
} catch (Exception e) {
e.printStackTrace();
}
}
}
取消了队列的生产者消费者模式,而是直接在服务端开启一个socket端口,直接传输数据。
上面相关的代码,我已上传到github,有兴趣的可以下载来看看。
参考
SpringBoot整合Redis及Redis工具类撰写
RocketMq消息监听程序中消除大量的if..else
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