Java教程
HA高可用集群部署
本文主要是介绍HA高可用集群部署，对大家解决编程问题具有一定的参考价值，需要的程序猿们随着小编来一起学习吧！
HA高可用集群部署
高可用 ZooKeeper 集群部署
zookeeper安装部署
注意：需要安装jdk，但jdk已经在第4章装过，这里直接装zookeeper
#解压并安装zookeeper [root@master ~]# ls anaconda-ks.cfg apache-hive-2.0.0-bin.tar.gz hadoop-2.7.1.tar.gz jdk-8u152-linux-x64.tar.gz mysql-community-client-5.7.18-1.el7.x86_64.rpm mysql-community-common-5.7.18-1.el7.x86_64.rpm mysql-community-devel-5.7.18-1.el7.x86_64.rpm mysql-community-libs-5.7.18-1.el7.x86_64.rpm mysql-community-server-5.7.18-1.el7.x86_64.rpm mysql-connector-java-5.1.46.jar sqoop-1.4.7.bin__hadoop-2.6.0.tar.gz zookeeper-3.4.8.tar.gz [root@master ~]# tar xf zookeeper-3.4.8.tar.gz -C /usr/local/src/ [root@master ~]# cd /usr/local/src/ [root@master src]# ls hadoop hive jdk sqoop zookeeper-3.4.8 [root@master src]# mv zookeeper-3.4.8 zookeeper [root@master src]# ls hadoop hive jdk sqoop zookeeper
创建zookeeper数据目录
[root@master src]# mkdir /usr/local/src/zookeeper/data [root@master src]# mkdir /usr/local/src/zookeeper/logs
配置环境变量
[root@master src]# vi /etc/profile.d/zookeeper.sh export ZK_HOME=/usr/local/src/zookeeper export PATH=$PATH:$ZK_HOME/bin
修改zoo.cfg配置文件
[root@master src]# cd /usr/local/src/zookeeper/conf/ [root@master conf]# ls configuration.xsl log4j.properties zoo_sample.cfg [root@master conf]# cp zoo_sample.cfg zoo.cfg [root@master conf]# vi zoo.cfg #修改 dataDir=/usr/local/src/zookeeper/data #增加 dataLogDir=/usr/local/src/zookeeper/logs server.1=master:2888:3888 server.2=slave1:2888:3888 server.3=slave2:2888:3888
创建myid配置文件
[root@master conf]# cd .. [root@master zookeeper]# cd data/ [root@master data]# echo "1" > myid
分发Zookeeper集群配置文件
#发送环境变量文件到slave1,slave2 [root@master data]# scp -r /etc/profile.d/zookeeper.sh slave1:/etc/profile.d/ [root@master data]# scp -r /etc/profile.d/zookeeper.sh slave2:/etc/profile.d/ #发送zookeeper配置文件到slave1,slave2 [root@master ~]# scp -r /usr/local/src/zookeeper/ slave1:/usr/local/src/ [root@master ~]# scp -r /usr/local/src/zookeeper/ slave2:/usr/local/src/
修改myid配置
#slave1 [root@slave1 ~]# echo "2" > /usr/local/src/zookeeper/data/myid #slave2 [root@slave2 ~]# echo "3" > /usr/local/src/zookeeper/data/myid #查看3个节点 [root@master ~]# cat /usr/local/src/zookeeper/data/myid 1 [root@slave1 ~]# cat /usr/local/src/zookeeper/data/myid 2 [root@slave2 ~]# cat /usr/local/src/zookeeper/data/myid 3
修改文件所属权限
[root@master ~]# chown -R hadoop.hadoop /usr/local/src/ [root@slave1 ~]# chown -R hadoop.hadoop /usr/local/src/ [root@slave2 ~]# chown -R hadoop.hadoop /usr/local/src/
查看防火墙和selinux，如果没关就关掉
#以master为例,slave1,slave2同样要做
[root@master ~]# systemctl disable --now firewalld
[root@master ~]# systemctl status firewalld
● firewalld.service - firewalld - dynamic firewall daemon
Loaded: loaded (/usr/lib/systemd/system/firewalld.service; disabled; ve>
Active: inactive (dead)
Docs: man:firewalld(1)
[root@master ~]# vi /etc/selinux/config
SELINUX=disabled
切换hadoop用户，启动zookeeper
[root@master ~]# su - hadoop [root@slave1 ~]# su - hadoop [root@slave2 ~]# su - hadoop #启动zookeeper [hadoop@master ~]$ zkServer.sh start ZooKeeper JMX enabled by default Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg Starting zookeeper ... STARTED [hadoop@master ~]$ zkServer.sh status ZooKeeper JMX enabled by default Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg Mode: follower [hadoop@slave1 ~]$ zkServer.sh start ZooKeeper JMX enabled by default Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg Starting zookeeper ... STARTED [hadoop@slave1 ~]$ zkServer.sh status ZooKeeper JMX enabled by default Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg Mode: leader [hadoop@slave2 ~]$ zkServer.sh start ZooKeeper JMX enabled by default Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg Starting zookeeper ... STARTED [hadoop@slave2 ~]$ zkServer.sh status ZooKeeper JMX enabled by default Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg Mode: follower
查看集群
[hadoop@master ~]$ jps 1522 QuorumPeerMain 1579 Jps [hadoop@slave1 ~]$ jps 1368 Jps 1309 QuorumPeerMain [hadoop@slave2 ~]$ jps 1330 QuorumPeerMain 1387 Jps
Hadoop HA集群部署
注意：ssh免密登录在第4章已经配过，这里直接配HA
配置密钥加几条：
-
将masterr创建的公钥发给slave1
[hadoop@master ~]$ scp ~/.ssh/authorized_keys root@slave1:~/.ssh/ root@slave1's password: authorized_keys 100% 567 672.2KB/s 00:00
-
将slave1的私钥加到公钥里
[hadoop@slave1 ~]$ cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
-
将公钥发给slave2，master
[hadoop@slave1 ~]$ ssh-copy-id slave2 [hadoop@slave1 ~]$ ssh-copy-id master
删除第4章安装的hadoop
#删除环境变量，三个节点都要做 [root@master ~]# rm -rf /etc/profile.d/hadoop.sh [root@slave1 ~]# rm -rf /etc/profile.d/hadoop.sh [root@slave2 ~]# rm -rf /etc/profile.d/hadoop.sh #删除hadoop [root@master ~]# rm -rf /usr/local/src/hadoop/ [root@slave1 ~]# rm -rf /usr/local/src/hadoop/ [root@slave2 ~]# rm -rf /usr/local/src/hadoop/
配置hadoop环境变量
[root@master ~]# vi /etc/profile.d/hadoop.sh export HADOOP_HOME=/usr/local/src/hadoop export HADOOP_PREFIX=$HADOOP_HOME export HADOOP_MAPRED_HOME=$HADOOP_HOME export HADOOP_COMMON_HOME=$HADOOP_HOME export HADOOP_HDFS_HOME=$HADOOP_HOME export YARN_HOME=$HADOOP_HOME export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native export HADOOP_INSTALL=$HADOOP_HOME export HADOOP_OPTS="Djava.library.path=$HADOOP_INSTALL/lib:$HADOOP_COMMON_LIB_NATIVE_DIR" export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin export JAVA_HOME=/usr/local/src/jdk export PATH=$PATH:$JAVA_HOME/bin export ZK_HOME=/usr/local/src/zookeeper export PATH=$PATH:$ZK_HOME/bin
配置 hadoop-env.sh 配置文件
[root@master ~]# tar -xf hadoop-2.7.1.tar.gz -C /usr/local/src/ [root@master ~]# mv /usr/local/src/hadoop-2.7.1/ /usr/local/src/hadoop [root@master ~]# cd /usr/local/src/hadoop/etc/hadoop/ [root@master hadoop]# vi hadoop-env.sh #在最下面添加如下配置： export JAVA_HOME=/usr/local/src/jdk
配置 core-site.xml 配置文件
[root@master hadoop]# vi core-site.xml
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://mycluster</value>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>file:/usr/local/src/hadoop/tmp</value>
</property>
<property>
<name>ha.zookeeper.quorum</name>
<value>master:2181,slave1:2181,slave2:2181</value>
</property>
<property>
<name>ha.zookeeper.session-timeout.ms</name>
<value>30000</value>
<description>ms</description>
</property>
<property>
<name>fs.trash.interval</name>
<value>1440</value>
</property>
</configuration>
配置 hdfs-site.xml 配置文件
[root@master hadoop]# vi hdfs-site.xml
<configuration>
<property>
<name>dfs.qjournal.start-segment.timeout.ms</name>
<value>60000</value>
</property>
<property>
<name>dfs.nameservices</name>
<value>mycluster</value>
</property>
<property>
<name>dfs.ha.namenodes.mycluster</name>
<value>master,slave1</value>
</property>
<property>
<name>dfs.namenode.rpc-address.mycluster.master</name>
<value>master:8020</value>
</property>
<property>
<name>dfs.namenode.rpc-address.mycluster.slave1</name>
<value>slave1:8020</value>
</property>
<property>
<name>dfs.namenode.http-address.mycluster.master</name>
<value>master:50070</value>
</property>
<property>
<name>dfs.namenode.http-address.mycluster.slave1</name>
<value>slave1:50070</value>
</property>
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://master:8485;slave1:8485;slave2:8485/mycluster</value>
</property>
<property>
<name>dfs.client.failover.proxy.provider.mycluster</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
<name>dfs.ha.fencing.methods</name>
<value>
sshfence
shell(/bin/true)
</value>
</property>
<property>
<name>dfs.permissions.enabled</name>
<value>false</value>
</property>
<property>
<name>dfs.support.append</name>
<value>true</value>
</property>
<property>
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/root/.ssh/id_rsa</value>
</property>
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>/usr/local/src/hadoop/tmp/hdfs/nn</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>/usr/local/src/hadoop/tmp/hdfs/dn</value>
</property>
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/usr/local/src/hadoop/tmp/hdfs/jn</value>
</property>
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.ha.fencing.ssh.connect-timeout</name>
<value>30000</value>
</property>
<property>
<name>ha.failover-controller.cli-check.rpc-timeout.ms</name>
<value>60000</value>
</property>
</configuration>
配置mapred-site.xml配置文件
[root@master ~]# cd /usr/local/src/hadoop/etc/hadoop/
[root@master hadoop]# cp mapred-site.xml.template mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>master:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>master:19888</value>
</property>
</configuration>
配置yarn-site.xml配置文件
<configuration>
<!-- Site specific YARN configuration properties -->
<property>
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
<property>
<name>yarn.resourcemanager.cluster-id</name>
<value>yrc</value>
</property>
<property>
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm1</name>
<value>master</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm2</name>
<value>slave1</value>
</property>
<property>
<name>yarn.resourcemanager.zk-address</name>
<value>master:2181,slave1:2181,slave2:2181</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<name>yarn.log-aggregation.retain-seconds</name>
<value>86400</value>
</property>
<property>
<name>yarn.resourcemanager.recovery.enabled</name>
<value>true</value>
</property>
<property>
<name>yarn.resourcemanager.store.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>
</configuration>
配置slaves配置文件
[root@master hadoop]# vi slaves #删除localhost添加以下 master slave1 slave2
创建数据存放目录
#namenode、datanode、journalnode 等存放数据的公共目录为/usr/local/src/hadoop/tmp
[root@master hadoop]# mkdir -p /usr/local/src/hadoop//tmp/hdfs/{nn,dn,jn}
[root@master hadoop]# mkdir -p /usr/local/src/hadoop/tmp/logs
分发文件到其他节点
#分发环境变量文件 [root@master hadoop]# scp -r /etc/profile.d/hadoop.sh slave1:/etc/profile.d/ hadoop.sh 100% 601 496.6KB/s 00:00 [root@master hadoop]# scp -r /etc/profile.d/hadoop.sh slave2:/etc/profile.d/ hadoop.sh 100% 601 314.7KB/s 00:00 #分发hadoop配置目录 [root@master hadoop]# scp -r /usr/local/src/hadoop/ slave1:/usr/local/src/ [root@master hadoop]# scp -r /usr/local/src/hadoop/ slave2:/usr/local/src/
修改目录所有者和所有者组
[root@master ~]# chown -R hadoop.hadoop /usr/local/src/ [root@slave1 ~]# chown -R hadoop.hadoop /usr/local/src/ [root@slave2 ~]# chown -R hadoop.hadoop /usr/local/src/
生效环境变量
#在切换hadoop用户时会自动导入，为了以防万一，还是手动source一下 [root@master ~]# source /etc/profile.d/hadoop.sh [root@slave1 ~]# source /etc/profile.d/hadoop.sh [root@slave2 ~]# source /etc/profile.d/hadoop.sh
HA高可用集群启动
HA的启动
启动journalnode守护进程
#切换hadoop用户 [hadoop@master ~]$ hadoop-daemons.sh start journalnode master: starting journalnode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-journalnode-master.out slave1: starting journalnode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-journalnode-slave1.out slave2: starting journalnode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-journalnode-slave2.out
初始化namenode
[hadoop@master ~]$ hdfs namenode -format ............ 23/05/28 13:58:27 INFO namenode.FSImage: Allocated new BlockPoolId: BP-793703415-192.168.88.10-1685253507647 23/05/28 13:58:27 INFO common.Storage: Storage directory /usr/local/src/hadoop/tmp/hdfs/nn has been successfully formatted. 23/05/28 13:58:28 INFO namenode.NNStorageRetentionManager: Going to retain 1 images with txid >= 0 23/05/28 13:58:28 INFO util.ExitUtil: Exiting with status 0 23/05/28 13:58:28 INFO namenode.NameNode: SHUTDOWN_MSG: /************************************************************ SHUTDOWN_MSG: Shutting down NameNode at master/192.168.88.10 ************************************************************/
注册ZNode
#要先启动zookeeper不然会报错 [hadoop@master ~]$ zkServer.sh start [hadoop@slave1 ~]$ zkServer.sh start [hadoop@slave2 ~]$ zkServer.sh start [hadoop@master ~]$ hdfs zkfc -formatZK ...... 23/05/28 14:01:08 INFO zookeeper.ClientCnxn: Opening socket connection to server slave2/192.168.88.30:2181. Will not attempt to authenticate using SASL (unknown error) 23/05/28 14:01:08 INFO zookeeper.ClientCnxn: Socket connection established to slave2/192.168.88.30:2181, initiating session 23/05/28 14:01:08 INFO zookeeper.ClientCnxn: Session establishment complete on server slave2/192.168.88.30:2181, sessionid = 0x38860f220b90000, negotiated timeout = 30000 23/05/28 14:01:08 INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/mycluster in ZK. 23/05/28 14:01:08 INFO ha.ActiveStandbyElector: Session connected. 23/05/28 14:01:08 INFO zookeeper.ZooKeeper: Session: 0x38860f220b90000 closed 23/05/28 14:01:08 INFO zookeeper.ClientCnxn: EventThread shut down
启动hdfs
[hadoop@master ~]$ start-all.sh
同步master数据
#复制 namenode 元数据到其它节点(在 master 节点执行) [hadoop@master ~]$ scp -r /usr/local/src/hadoop/tmp/hdfs/nn/* slave1:/usr/local/src/hadoop/tmp/hdfs/nn/ VERSION 100% 204 189.8KB/s 00:00 seen_txid 100% 2 1.3KB/s 00:00 fsimage_0000000000000000000.md5 100% 62 38.1KB/s 00:00 fsimage_0000000000000000000 100% 353 378.0KB/s 00:00 edits_inprogress_0000000000000000001 100% 1024KB 5.0MB/s 00:00 in_use.lock 100% 11 6.4KB/s 00:00 [hadoop@master ~]$ scp -r /usr/local/src/hadoop/tmp/hdfs/nn/* slave2:/usr/local/src/hadoop/tmp/hdfs/nn/ VERSION 100% 204 294.1KB/s 00:00 seen_txid 100% 2 2.2KB/s 00:00 fsimage_0000000000000000000.md5 100% 62 65.8KB/s 00:00 fsimage_0000000000000000000 100% 353 554.6KB/s 00:00 edits_inprogress_0000000000000000001 100% 1024KB 6.7MB/s 00:00 in_use.lock 100% 11 8.9KB/s 00:00
在slave1上启动resourcemanager和namenode进程
[hadoop@slave1 ~]$ yarn-daemons.sh start resourcemanager [hadoop@slave1 ~]$ hadoop-daemon.sh start namenode [hadoop@slave1 ~]$ jps 1489 JournalNode 1841 DFSZKFailoverController 1922 NodeManager 2658 NameNode 2738 Jps 1702 DataNode 2441 ResourceManager 1551 QuorumPeerMain
启动MapReduce任务历史服务器
[hadoop@master ~]$ yarn-daemon.sh start proxyserver starting proxyserver, logging to /usr/local/src/hadoop/logs/yarn-hadoop-proxyserver-master.out [hadoop@master ~]$ mr-jobhistory-daemon.sh start historyserver starting historyserver, logging to /usr/local/src/hadoop/logs/mapred-hadoop-historyserver-master.out
查看端口和进程
[hadoop@master ~]$ jps 3297 JobHistoryServer 2260 DataNode 2564 DFSZKFailoverController 2788 NodeManager 2678 ResourceManager 2122 NameNode 3371 Jps 1727 JournalNode 1919 QuorumPeerMain [hadoop@slave1 ~]$ jps 1489 JournalNode 1841 DFSZKFailoverController 1922 NodeManager 2658 NameNode 2738 Jps 1702 DataNode 2441 ResourceManager 1551 QuorumPeerMain [hadoop@slave2 ~]$ jps 1792 NodeManager 1577 QuorumPeerMain 2282 Jps 1515 JournalNode 1647 DataNode
查看网页显示
-
master:50070
-
slave1:50070
-
master:8088
HA的测试
创建一个测试文件
[hadoop@master ~]$ vi rainmom.txt Hello World Hello Hadoop
在hdfs创建文件夹
[hadoop@master ~]$ hadoop fs -mkdir /input
将rainmom.txt传输到input上
[hadoop@master ~]$ hadoop fs -put ~/rainmom.txt /input
进入到jar包测试文件目录下，测试mapreduce
[hadoop@master ~]$ cd /usr/local/src/hadoop/share/hadoop/mapreduce/ [hadoop@master mapreduce]$ hadoop jar hadoop-mapreduce-examples-2.7.1.jar wordcount /input/rainmom.txt /output ..... 23/05/28 14:35:37 INFO mapreduce.Job: Running job: job_1685253795384_0001 23/05/28 14:35:48 INFO mapreduce.Job: Job job_1685253795384_0001 running in uber mode : false 23/05/28 14:35:48 INFO mapreduce.Job: map 0% reduce 0% 23/05/28 14:35:57 INFO mapreduce.Job: map 100% reduce 0% 23/05/28 14:36:09 INFO mapreduce.Job: map 100% reduce 100% 23/05/28 14:36:10 INFO mapreduce.Job: Job job_1685253795384_0001 completed successfully ....
查看hdfs下的传输结果
[hadoop@master ~]$ hadoop fs -ls -R /output -rw-r--r-- 2 hadoop supergroup 0 2023-05-28 14:36 /output/_SUCCESS -rw-r--r-- 2 hadoop supergroup 25 2023-05-28 14:36 /output/part-r-00000
查看文件测试的结果
[hadoop@master ~]$ hadoop fs -cat /output/part-r-00000 Hadoop 1 Hello 2 World 1
高可用性验证
自动切换服务状态
#格式：hdfs haadmin -failover --forcefence --forceactive 主 备
[hadoop@master ~]$ hdfs haadmin -failover --forcefence --forceactive slave1 master
#这里注意一点，执行这条命令，会出现：forcefence and forceactive flags
not supported with auto-failover enabled.的提示，这句话表示，配置了自动切换之后，就不能进行手动切换了，
故此次切换失败， 该意思是在配置故障自动切换（dfs.ha.automatic-failover.enabled=true）之后，
无法手动进行，可将该参数更改为false(不需要重启进程)后，重新执行该命令即可。
# dfs.ha.automatic-failover.enabled参数需要在hdfs-site.xml或者core-site.xml中修改
[hadoop@master ~]$ vi /usr/local/src/hadoop/etc/hadoop/hdfs-site.xml
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
#查看状态
[hadoop@master ~]$ hdfs haadmin -getServiceState slave1
standby
[hadoop@master ~]$ hdfs haadmin -getServiceState master
active
手动切换服务状态
#在 maste 停止并启动 namenode [hadoop@master ~]$ hadoop-daemon.sh stop namenode stopping namenode #查看状态 [hadoop@master ~]$ hdfs haadmin -getServiceState master 23/05/28 14:53:55 INFO ipc.Client: Retrying connect to server: master/192.168.88.10:8020. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=1, sleepTime=1000 MILLISECONDS) Operation failed: Call From master/192.168.88.10 to master:8020 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused [hadoop@master ~]$ hdfs haadmin -getServiceState slave1 active #重新启动 [hadoop@master ~]$ hadoop-daemon.sh start namenode starting namenode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-namenode-master.out #再次查看状态 [hadoop@master ~]$ hdfs haadmin -getServiceState slave1 active [hadoop@master ~]$ hdfs haadmin -getServiceState master standby
查看web服务端
-
master:50070
-
slave1:50070
这篇关于HA高可用集群部署的文章就介绍到这儿，希望我们推荐的文章对大家有所帮助，也希望大家多多支持为之网！
您可能喜欢
-
Springboot应用的多环境打包入门11-23
-
Springboot应用的生产发布入门教程11-23
-
Python编程入门指南11-23
-
Java创业入门：从零开始的编程之旅11-23
-
Java创业入门：新手必读的Java编程与创业指南11-23
-
Java对接阿里云智能语音服务入门详解11-23
-
Java对接阿里云智能语音服务入门教程11-23
-
JAVA对接阿里云智能语音服务入门教程11-23
-
Java副业入门：初学者的简单教程11-23
-
JAVA副业入门：初学者的实战指南11-23
-
JAVA项目部署入门：新手必读指南11-23
-
Java项目部署入门：新手必看指南11-23
-
Java项目部署入门：新手必读指南11-23
-
Java项目开发入门：新手必读指南11-23
-
JAVA项目开发入门：从零开始的实用教程11-23
栏目导航
