扫码关注官方微信

扫码下载APP
返回顶部
首页 > 资讯 > 数据库 >分享一份关于Hadoop2.2.0集群环境搭建文档
  • 595

0
分享到

分享一份关于Hadoop2.2.0集群环境搭建文档

分享一份关于Hadoop2.2.0集群环境搭建文档 2019-03-26 07:03:00 595人浏览 无得
摘要

目录 一，准备环境 三，克隆VM 四，搭建集群 五，hadoop启动与测试 六，安装过程中遇到的问题及其解决方案

目录

  • 一，准备环境
  • 三，克隆VM
  • 四，搭建集群
  • 五，hadoop启动与测试
  • 六，安装过程中遇到的问题及其解决方案

一，准备环境

  • PC基本配置如下：
处理器：Intel(R) Core(TM) i5-3230M CPU @ 2.6GHz 2.60GHz
安装内存（RAM）: 12.0GB
系统类型：64位操作系统

PC配置

内存：2GB
处理器：1
硬盘：40G
网络适配器：NAT
系统：linux ubuntu 4.4.0-142-generic #168~14.04.1-Ubuntu SMP Sat Jan 19 11:26:28 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

虚拟机配置

  • 修改系统时区
 ~ sudo timedatectl set-timezone "Asia/Shanghai"
  • 为方便使用建议如下配置：

安装oh-my-zsh插件；

设置VIM行号；

安装ssh插件服务；

安装vsftpd插件服务并加以配置，方便文件上传下载；

在PC上安装Xshell客户端；

在PC上安装FTP客户端。

  • 需要的软件：
jdk-7u51-linux-x64.gz  链接：Http://pan.baidu.com/s/1dFFT1GP  密码：cc5t

hadoop-2.2.0-x64.tar.gz https://download.csdn.net/download/wwyymmddbb/10203840

  • 在虚拟机做如下步骤：创建目录，存储工具包/home/zhangbocheng，并利用FTP上传相关软件包。
    FTP
    软件包

    二，安装单机环境

  • 安装Java1.7.0

~ mkdir java
~ cd java   
➜  java tar -xf /home/zhangbocheng/jdk-7u51-linux-x64.gz 
➜  java ln -s jdk1.7.0_51 JDK
➜  java vi ~/.bashrc 
➜  java vi ~/.zshrc
export JAVA_HOME=$HOME/java/java
export PATH=$JAVA_HOME/bin:$PATH

:wq            
➜  java source ~/.bashrc 
➜  java source ~/.zshrc
➜  java java -version 
java version "1.7.0_51"
Java(TM) SE Runtime Environment (build 1.7.0_51-b13)
Java HotSpot(TM) 64-Bit Server VM (build 24.51-b03, mixed mode)

Java

  • 安装Hadoop2.2.0
➜  ~ tar -xf /home/zhangbocheng/hadoop-2.2.0-x64.tar.gz
➜  ~ mv hadoop-2.2.0 hadoop2.2.0    
➜  ~ mkdir hadoop2.2.0/hdfs  
➜  ~ mkdir hadoop2.2.0/hdfs/name
➜  ~ mkdir hadoop2.2.0/hdfs/data
➜  ~ mkdir hadoop2.2.0/logs     
➜  ~ mkdir hadoop2.2.0/tmp
  • 配置环境
➜  ~ vi .zshrc 
export JAVA_HOME=$HOME/java/jdk
export CLASSPATH=$JAVA_HOME/lib/tool.jar:$JAVA_HOME/lib/dt.jar
export PATH=$JAVA_HOME/bin:$PATH
➜  ~ source .zshrc 
➜  ~ echo $CLASSPATH
/home/zhangbc/java/jdk/lib/tool.jar:/home/zhangbc/java/jdk/lib/dt.jar
➜  ~ vi .zshrc 
export HADOOP_HOME=$HOME/hadoop2.2.0
export PATH=$HADOOP_HOME/sbin:$HADOOP_HOME/bin:$JAVA_HOME/bin:$PATH
export HADOOP_LOG_DIR=$HADOOP_HOME/logs
export YARN_LOG_DIR=$HADOOP_LOG_DIR
➜  ~ source .zshrc 
➜  ~ hadoop version
Hadoop 2.2.0
Subversion Unknown -r Unknown
Compiled by root on 2014-09-21T22:41Z
Compiled with protoc 2.5.0
From source with checksum 79e53ce7994d1628b240f09af91e1af4
This command was run using /home/zhangbc/hadoop2.2.0/share/hadoop/common/hadoop-common-2.2.0.jar

Hadoop

  • 修改Hadoop2.2.0配置文件
# 检查并修改以下三个文件中JAVA_HOME的值
➜  ~ vi hadoop2.2.0/etc/hadoop/hadoop-env.sh 
➜  ~ vi hadoop2.2.0/etc/hadoop/yarn-env.sh 
➜  ~ vi hadoop2.2.0/etc/hadoop/mapred-env.sh # 只需要去掉注释加以修改
export JAVA_HOME=${JAVA_HOME} # 错误
export JAVA_HOME=/home/zhangbc/java/jdk # 正确

# 添加集群的slave节点
➜  ~ vi hadoop2.2.0/etc/hadoop/slaves 
# localhost
slave_1
slave_2
slave_3

➜  ~ vi hadoop2.2.0/etc/hadoop/core-site.xml 

    
        fs.defaultFS
        hdfs://master:9000/
        设定namenode的主机名及其端口
    
    
        hadoop.tmp.dir
        /home/zhangbc/hadoop2.2.0/tmp/hadoop-${user.name}
        存储临时文件
    
    
        hadoop.proxyuser.hadoop.hosts
        *
    
    
        hadoop.proxyuser.hadoop.groups
        *
    



➜  ~ vi hadoop2.2.0/etc/hadoop/hdfs-site.xml

    
        dfs.namenode.http-address
        master:50070
        设定NameNode地址及其端口
    
    
        dfs.namenode.secondary.http-address
        slave_1:50090
        设定SecondNameNode地址及其端口
    
    
        dfs.replication
        3
        设定HDFS存储文件的副本个数，默认为3
    
    
        dfs.namenode.name.dir
        file:///home/zhangbc/hadoop2.2.0/hdfs/name
        设置NameNode用来持续存储命名空间和交换日志的本地文件系统路径
    
    
        dfs.datanode.data.dir
        file:///home/zhangbc/hadoop2.2.0/hdfs/data
        设置DataNode在本地存储文件的目录列表
    
    
        dfs.namenode.checkpoint.dir
        file:///home/zhangbc/hadoop2.2.0/hdfs/namesecondary
        设置SecondaryNameNode存储临时镜像的本地文件系统路径，
            若这是一个用逗号分隔的列表，则镜像会冗余复制到所有目录
    
    
        dfs.WEBhdfs.enable
        true
        是否允许网页浏览HDFS文件
    
    
        dfs.stream-buffer-size
        131072
        默认为4KB,作为Hadoop的缓冲区，用于Hapdoop读写HDFS的文件，
        还有map的输出都用到了这个缓冲区容量，131072=128KB
    



➜  ~ vi hadoop2.2.0/etc/hadoop/mapred-site.xml 

    
        mapReduce.framework.name
        yarn
    
    
        mapreduce.jobhistory.address
        master:10020
    
    
        mapreduce.jobhistory.webapp.address
        master:19888
    



➜  ~ vi hadoop2.2.0/etc/hadoop/yarn-site.xml

    
        yarn.resourcemanager.hostname
        master
    
    
        yarn.nodemanager.aux-services
        mapreduce_shuffle
    
    
        yarn.nodemanager.aux-services.mapreduce.shuffle.class
        org.apache.hadoop.mapred.ShuffleHandler
    
    
        yarn.resourcemanager.address
        master:8032
    
    
        yarn.resourcemanager.scheduler.address
        master:8030
    
    
        yarn.resourcemanager.resource-tracker.address
        master:8031
    
    
        yarn.resourcemanager.admin.address
        master:8033
    
    
        yarn.resourcemanager.webapp.address
        master:8088
  • 修改主机名称（千万不要含有下划线_）
➜  ~ sudo hostname master   # 只对当前状态生效
[sudo] passWord for zhangbc: 
➜  ~ hostname
master
➜  ~ sudo vi /etc/hostname # 永久修改


master
:wq
  • 关闭防火墙
➜  ~ service ufw status
ufw start/running
➜  ~ sudo service ufw stop
[sudo] password for zhangbc: 
ufw stop/waiting
➜  ~ service ufw status   
ufw stop/waiting

三，克隆VM

通过 VMware Workstation工具，关闭当前虚拟机，对其克隆三台虚拟机作为从机使用。

克隆方法选择“创建完整克隆(F)”，如图所示：
创建完整克隆

四，搭建集群

  • 修改三台从机slave的host，并再重启使之生效。
➜  ~ sudo vi /etc/hostname
➜  ~ sudo vi /etc/hosts
➜  ~ sudo reboot
  • 对所有集群中的服务器进行检查，关闭防火墙并禁止掉。
➜  ~ sudo service ufw status
[sudo] password for zhangbc: 
ufw start/running
➜  ~ sudo service ufw stop  
ufw stop/waiting
➜  ~ sudo service ufw status
ufw stop/waiting
➜  ~ sudo ufw disable 
Firewall stopped and disabled on system startup
  • 对所有集群中的服务器绑定hostname与IP
➜  ~ sudo vi /etc/hosts
 192.168.71.128  master
 192.168.71.129  slave_1
 192.168.71.130  slave_2
 192.168.71.131  slave_3
  • 对所有集群中的服务器创建SSH密钥，完成相关验证，注意保留原有的其他密钥，以备他用
➜  .ssh mv id_rsa id_rsa_git
➜  .ssh mv id_rsa.pub id_rsa_git.pub
➜  .ssh ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa
# 生成authorized_keys
➜  .ssh cat id_rsa.pub >> authorized_keys
# 设置权限
➜  .ssh sudo chmod 600 authorized_keys 
# ssh登录本机，并退出
➜  .ssh ssh localhost 
The authenticity of host 'localhost (127.0.0.1)' can't be established.
ECDSA key fingerprint is b6:fa:8d:2b:2d:0d:e4:fd:4f:44:ed:37:3f:79:b6:ce.
Are you sure you want to continue connecting (yes/no)? yes
Warning: Permanently added 'localhost' (ECDSA) to the list of known hosts.
Welcome to Ubuntu 14.04.6 LTS (GNU/Linux 4.4.0-142-generic x86_64)

 * Documentation:  https://help.ubuntu.com/

New release '16.04.6 LTS' available.
Run 'do-release-upgrade' to upgrade to it.

Your Hardware Enablement Stack (HWE) is supported until April 2019.
Last login: Wed Nov 13 20:17:41 2019 from 192.168.71.1
➜  ~ exit
Connection to localhost closed.
➜  .ssh
  • 配置各个节点之间免密登录
# 将slave_1节点rsa通过ssh-copy-id分别复制到master，slave_2，slave_3
➜  ~ ssh-copy-id -i ~/.ssh/id_rsa.pub master
➜  ~ ssh-copy-id -i ~/.ssh/id_rsa.pub slave_2
➜  ~ ssh-copy-id -i ~/.ssh/id_rsa.pub slave_3
# 验证登录
➜  ~ ssh master
➜  ~ ssh slave_2
➜  ~ ssh slave_3
# 其他节点同步骤

五，Hadoop启动与测试

  • 格式化文件系统
➜  ~ hdfs namenode -fORMat
19/11/13 21:57:48 INFO namenode.NameNode: STARTUP_MSG: 
/************************************************************
STARTUP_MSG: Starting NameNode
STARTUP_MSG:   host = master/192.168.71.128
STARTUP_MSG:   args = [-format]
STARTUP_MSG:   version = 2.2.0
.........
19/11/13 21:57:55 INFO util.ExitUtil: Exiting with status 0  # 表示成功
.........
  • 启动HDFS
zhangbc@master:~$ start-dfs.sh 
Starting namenodes on [master]
master: starting namenode, logging to /home/zhangbc/hadoop2.2.0/logs/hadoop-zhangbc-namenode-master.out
slave_1: starting datanode, logging to /home/zhangbc/hadoop2.2.0/logs/hadoop-zhangbc-datanode-slave_1.out
slave_3: starting datanode, logging to /home/zhangbc/hadoop2.2.0/logs/hadoop-zhangbc-datanode-slave_3.out
slave_2: starting datanode, logging to /home/zhangbc/hadoop2.2.0/logs/hadoop-zhangbc-datanode-slave_2.out


zhangbc@master:~$ jps
6524 Jps
5771 NameNode
zhangbc@slave_1:~$ jps
4919 Jps
4818 DataNode
zhangbc@slave_2:~$ jps
4919 Jps
4801 DataNode
zhangbc@slave_3:~$ jps
4705 DataNode
4800 Jps

WEB验证：http://192.168.71.128:50070
web_dfs

  • 启动Yarn
zhangbc@master:~$ start-yarn.sh 
starting yarn daemons
starting resourcemanager, logging to /home/zhangbc/hadoop2.2.0/logs/yarn-zhangbc-resourcemanager-master.out
slave_2: starting nodemanager, logging to /home/zhangbc/hadoop2.2.0/logs/yarn-zhangbc-nodemanager-slave_2.out
slave_1: starting nodemanager, logging to /home/zhangbc/hadoop2.2.0/logs/yarn-zhangbc-nodemanager-slave_1.out
slave_3: starting nodemanager, logging to /home/zhangbc/hadoop2.2.0/logs/yarn-zhangbc-nodemanager-slave_3.out

zhangbc@master:~$ jps
5771 NameNode
6642 Jps
zhangbc@slave_1:~$ jps
5099 Jps
4818 DataNode
5011 NodeManager
zhangbc@slave_2:~$ jps
5101 Jps
5016 NodeManager
4801 DataNode
zhangbc@slave_2:~$ jps
5101 Jps
5016 NodeManager
4801 DataNode

WEB验证：http://192.168.71.128:8088
web_yarn

  • 管理JobHistory Server
zhangbc@master:~$ mr-jobhistory-daemon.sh start historyserver
starting historyserver, logging to /home/zhangbc/hadoop2.2.0/logs/mapred-zhangbc-historyserver-master.out
zhangbc@master:~$ mr-jobhistory-daemon.sh stop historyserver

WEB验证：http://192.168.71.128:19888
web_job

  • 集群验证
# 创建目录
zhangbc@master:~$ hdfs dfs -mkdir -p /data/wordscount
zhangbc@master:~$ hdfs dfs -mkdir -p /output

# 查看数据目录
zhangbc@master:~$ hdfs dfs -ls /data

# 上传本地文件
zhangbc@master:~$ hdfs dfs -put hadoop2.2.0/etc/hadoop/core-site.xml /data/wordscount

# 执行
zhangbc@master:~$ hadoop jar hadoop2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar wordcount /data/wordscount /output/wordscount
...............................
19/11/14 13:04:45 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1573705994579_0001/
19/11/14 13:04:45 INFO mapreduce.Job: Running job: job_1573705994579_0001
19/11/14 13:04:59 INFO mapreduce.Job: Job job_1573705994579_0001 running in uber mode : false
19/11/14 13:04:59 INFO mapreduce.Job:  map 0% reduce 0%
19/11/14 13:05:14 INFO mapreduce.Job:  map 100% reduce 0%
19/11/14 13:05:27 INFO mapreduce.Job:  map 100% reduce 100%
19/11/14 13:05:27 INFO mapreduce.Job: Job job_1573705994579_0001 completed successfully
19/11/14 13:05:27 INFO mapreduce.Job: Counters: 43
............................................

# 查看运行结果
zhangbc@master:~$ hdfs dfs -cat /output/wordscount/part-r-00000

六，安装过程中遇到的问题及其解决方案

  • 问题1：上传文件报错
zhangbc@master:~$ hdfs dfs -put hadoop2.2.0/etc/hadoop/core-site.xml /data/wordcount
19/11/14 10:13:24 WARN hdfs.DFSClient: DataStreamer Exception
org.apache.hadoop.ipc.RemoteException(java.io.IOExcept、ion): File /data/wordcount/core-site.xml._COPYING_ could only be replicated to 0 nodes instead of minReplication (=1).  There are 0 datanode(s) running and no node(s) are excluded in this operation.
    at org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget(BlockManager.java:1384)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:2477)
    at org.apache.hadoop.hdfs.server.namenode.NameNoderpcServer.addBlock(NameNodeRpcServer.java:555)
    at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:387)
    at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java:59582)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:585)
    at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:928)
    at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2048)
    at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2044)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:415)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1491)
    at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2042)

    at org.apache.hadoop.ipc.Client.call(Client.java:1347)
    at org.apache.hadoop.ipc.Client.call(Client.java:1300)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:206)
    at com.sun.proxy.$Proxy9.addBlock(Unknown Source)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:186)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
    at com.sun.proxy.$Proxy9.addBlock(Unknown Source)
    at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.addBlock(ClientNamenodeProtocolTranslatorPB.java:330)
    at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.locateFollowingBlock(DFSOutputStream.java:1226)
    at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1078)
    at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:514)
put: File /data/wordcount/core-site.xml._COPYING_ could only be replicated to 0 nodes instead of minReplication (=1).  There are 0 datanode(s) running and no node(s) are excluded in this operation.
19/11/14 10:13:24 ERROR hdfs.DFSClient: Failed to close file /data/wordcount/core-site.xml._COPYING_
org.apache.hadoop.ipc.RemoteException(java.io.IOException): File /data/wordcount/core-site.xml._COPYING_ could only be replicated to 0 nodes instead of minReplication (=1).  There are 0 datanode(s) running and no node(s) are excluded in this operation.
    at org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget(BlockManager.java:1384)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:2477)
    at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:555)
    at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:387)
    at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java:59582)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:585)
    at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:928)
    at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2048)
    at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2044)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:415)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1491)
    at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2042)

    at org.apache.hadoop.ipc.Client.call(Client.java:1347)
    at org.apache.hadoop.ipc.Client.call(Client.java:1300)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:206)
    at com.sun.proxy.$Proxy9.addBlock(Unknown Source)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:186)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
    at com.sun.proxy.$Proxy9.addBlock(Unknown Source)
    at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.addBlock(ClientNamenodeProtocolTranslatorPB.java:330)
    at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.locateFollowingBlock(DFSOutputStream.java:1226)
    at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1078)
    at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:514)

主要原因是重新格式化文件系统，导致master节点下的hadoop2.2.0/hdfs/name/current/VERSION中的clusterID和Slave节点下的hadoop2.2.0/hdfs/data/current/VERSION中的clusterID不一致。在浏览器输入master:50070可以发现Live Nodes为0。

解决方案是修改master节点下的clusterID使之与Slave节点下的clusterID一致，然后重启服务即可。

  • 问题2：执行JAR报错问题
Container launch failed for container_1573700741821_0001_01_000007 : java.lang.IllegalArgumentException: Does not contain a valid host:port authority: slave_1:33775

主要原因：Hadoop nodemanager结点主机名不能带下划线_。

解决方案：修改主机名称。

  • 问题3：绑定主机名引起的问题：sudo: unable to resolve host master

解决方案如下：

➜  ~ sudo vi /etc/hosts

  1 127.0.0.1       localhost
  2 127.0.1.1       ubuntu
  3 127.0.1.1       master
:wq!

通过本次实验，对集群概念有个基本的认识，在搭建过程中遇到问题不算太多，主要是对局域网组建缺乏认识深度，本集群环境可以进一步扩展，如动态增减节点，借助ZooKeeper技术加以融合等在企业中是比较常见的做法。

您可能感兴趣的文档:

--结束END--

本文标题: 分享一份关于Hadoop2.2.0集群环境搭建文档

本文链接: https://lsjlt.com/news/2173.html(转载时请注明来源链接)

有问题或投稿请发送至: 邮箱/279061341@qq.com    QQ/279061341

猜你喜欢
软考高级职称资格查询
热门wiki
近期文章
推荐阅读
热门问答
热门标签
编程网，编程工程师的家园，是目前国内优秀的开源技术社区之一，形成了由开源软件库、代码分享、资讯、协作翻译、讨论区和博客等几大频道内容，为IT开发者提供了一个发现、使用、并交流开源技术的平台。

  • 官方手机版

  • 微信公众号

  • 商务合作