Hadoop 3.4.0+HBase2.5.8+ZooKeeper3.8.4+Hive4.0+Sqoop 分布式高可用集群部署安装 大数据系列二

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猴君
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创建服务器,参考

虚拟机创建服务器

节点名字节点IP系统版本
master11192.168.50.11centos 8.5
slave12192.168.50.12centos 8.5
slave13192.168.50.13centos 8.5

1 下载组件

Hadoop:官网地址

Hbase:官网地址

ZooKeeper:官网下载

Hive:官网下载

Sqoop:官网下载

为方便同学们下载,特整理到网盘

链接地址

2 通过xftp 上传软件到服务器,统一放到/data/soft/

3 配置ZooKeeper

tar zxvf apache-zookeeper-3.8.4-bin.tar.gz mv apache-zookeeper-3.8.4-bin/ /data/zookeeper #修改配置文件 cd /data/zookeeper/conf cp zoo_sample.cfg zoo.cfg #创建数据保存目录 mkdir  -p /data/zookeeper/zkdata mkdir -p /data/zookeeper/logs vim zoo.cfg dataDir=/tmp/zookeeper-->dataDir=/data/zookeeper/zkdata dataLogDir=/data/zookeeper/logs server.1=master11:2888:3888 server.2=slave12:2888:3888 server.3=slave13:2888:3888  #配置环境变量 vim /etc/profile export ZooKeeper_HOME=/data/zookeeper export PATH=$PATH:$ZooKeeper_HOME/bin source  /etc/profile

#新建myid并且写入对应的myid

[root@master11 zkdata]# cat myid  1 #对应修改 slave12 myid--2 slave13 myid--3

4  配置HBase

tar  zxvf  hbase-2.5.8-bin.tar.gz mv  hbase-2.5.8/ /data/hbase mkdir -p /data/hbase/logs #vim /etc/profile export HBASE_LOG_DIR=/data/hbase/logs export HBASE_MANAGES_ZK=false export HBASE_HOME=/data/hbase export PATH=$PATH:$ZooKeeper_HOME/bin #vim  /data/hbase/conf/regionservers slave12 slave13 #新建backup-masters vim  /data/hbase/conf/backup-masters slave12 #vim  /data/hbase/conf/hbase-site.xml  <property>     <name>hbase.cluster.distributed</name>     <value>true</value>   </property> <!--HBase端口-->  <property>  <name>hbase.master.info.port</name>  <value>16010</value> </property> <property>     <name>hbase.zookeeper.quorum</name>     <value>master11,slave12,slave13</value>   </property> <property>     <name>hbase.rootdir</name>     <value>hdfs://master11:9000/hbase</value>   </property> <property>   <name>hbase.wal.provider</name>   <value>filesystem</value> </property>

 5 配置hadoop

tar zxvf hadoop-3.4.0.tar.gz mv  hadoop-3.4.0/ /data/hadoop #配置环境变量 vim /etc/profile export HADOOP_HOME=/data/hadoop export PATH=$PATH:$HADOOP_HOME/bin:$PATH:$HADOOP_HOME/sbin source /etc/profile #查看版本 [root@master11 soft]# hadoop version Hadoop 3.4.0 Source code repository git@github.com:apache/hadoop.git -r bd8b77f398f626bb7791783192ee7a5dfaeec760 Compiled by root on 2024-03-04T06:35Z Compiled on platform linux-x86_64 Compiled with protoc 3.21.12 From source with checksum f7fe694a3613358b38812ae9c31114e This command was run using /data/hadoop/share/hadoop/common/hadoop-common-3.4.0.jar

6 修改hadoop配置文件

#core-site.xml

vim /data/hadoop/etc/hadoop/core-site.xml #增加如下 <configuration> <property>     <name>fs.defaultFS</name>     <value>hdfs://master11</value> </property> <!-- hadoop 本地数据存储目录 format 时自动生成 --> <property>     <name>hadoop.tmp.dir</name>     <value>/data/hadoop/data/tmp</value> </property> <!-- 在 WebUI访问 HDFS 使用的用户名。--> <property>     <name>hadoop.http.staticuser.user</name>     <value>root</value> </property> <property>     <name>hadoop.proxyuser.hadoop.hosts</name>     <value>*</value> </property> <property>   <name>hadoop.proxyuser.root.hosts</name>   <value>*</value> </property> <property>   <name>hadoop.proxyuser.root.groups</name>   <value>*</value> </property> <property>     <name>ha.zookeeper.quorum</name>     <value>master11:2181,slave12:2181,slave13:2181</value>  </property>  <property>     <name>ha.zookeeper.session-timeout.ms</name>     <value>10000</value>  </property> </configuration> 

#hdfs-site.xml

vim  /data/hadoop/etc/hadoop/hdfs-site.xml 
<configuration>      <!-- 副本数dfs.replication默认值3,可不配置 -->     <property>         <name>dfs.replication</name>         <value>3</value>     </property>      <!-- 节点数据存储地址 -->     <property>         <name>dfs.namenode.name.dir</name>         <value>/data/hadoop/data/dfs/name</value>     </property>     <property>         <name>dfs.datanode.data.dir</name>         <value>/data/hadoop/data/dfs/data</value>     </property>      <!-- 主备配置 -->     <!-- 为namenode集群定义一个services name -->     <property>         <name>dfs.nameservices</name>         <value>mycluster</value>     </property>     <!-- 声明集群有几个namenode节点 -->     <property>         <name>dfs.ha.namenodes.mycluster</name>         <value>nn1,nn2</value>     </property>     <!-- 指定 RPC通信地址 的地址 -->     <property>         <name>dfs.namenode.rpc-address.mycluster.nn1</name>         <value>master11:8020</value>     </property>     <!-- 指定 RPC通信地址 的地址 -->     <property>         <name>dfs.namenode.rpc-address.mycluster.nn2</name>         <value>slave12:8020</value>     </property>     <!-- http通信地址 web端访问地址 -->     <property>             <name>dfs.namenode.http-address.mycluster.nn1</name>             <value>master11:50070</value>     </property>     <!-- http通信地址 web 端访问地址 -->     <property>             <name>dfs.namenode.http-address.mycluster.nn2</name>             <value>slave12:50070</value>      </property>       <!-- 声明journalnode集群服务器 -->      <property>             <name>dfs.namenode.shared.edits.dir</name>             <value>qjournal://master11:8485;slave12:8485;slave13:8485/mycluster</value>          </property>      <!-- 声明journalnode服务器数据存储目录 -->      <property>             <name>dfs.journalnode.edits.dir</name>             <value>/data/hadoop/data/dfs/jn</value>      </property>      <!-- 开启NameNode失败自动切换 -->      <property>             <name>dfs.ha.automatic-failover.enabled</name>             <value>true</value>      </property>      <!-- 隔离:同一时刻只能有一台服务器对外响应 -->         <property>         <name>dfs.ha.fencing.methods</name>         <value>             sshfence             shell(/bin/true)         </value>     </property>     <!-- 配置失败自动切换实现方式,通过ConfiguredFailoverProxyProvider这个类实现自动切换 -->      <property>             <name>dfs.client.failover.proxy.provider.mycluster</name>             <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>      </property>       <!-- 指定上述选项ssh通讯使用的密钥文件在系统中的位置。 -->      <property>             <name>dfs.ha.fencing.ssh.private-key-files</name>             <value>/root/.ssh/id_rsa</value>       </property>       <!-- 配置sshfence隔离机制超时时间(active异常,standby如果没有在30秒之内未连接上,那么standby将变成active) -->       <property>             <name>dfs.ha.fencing.ssh.connect-timeout</name>             <value>30000</value>      </property>      <property>        <name>dfs.ha.fencing.methods</name>        <value>sshfence</value>      </property> <!-- 开启hdfs允许创建目录的权限,配置hdfs-site.xml -->      <property>                 <name>dfs.permissions.enabled</name>                 <value>false</value>         </property>     <!-- 使用host+hostName的配置方式 -->         <property>                 <name>dfs.namenode.datanode.registration.ip-hostname-check</name>                 <value>false</value>         </property> <property>    <name>dfs.webhdfs.enabled</name>     <value>true</value> </property> <!-- 开启自动化: 启动zkfc --> <property>    <name>dfs.ha.automatic-failover.enabled</name>    <value>true</value> </property> <property>     <name>ipc.client.connect.max.retries</name>     <value>100</value>     <description>Indicates the number of retries a client will make to establish a server connection.</description> </property> <property>     <name>ipc.client.connect.retry.interval</name>     <value>10000</value>     <description>Indicates the number of milliseconds a client will wait for before retrying to establish a server connection.</description> </property>  </configuration> 

 #yarn-site.xml

vi /data/hadoop/etc/hadoop/yarn-site.xml <configuration>   <!-- 指定yarn占电脑资源,默认8核8g -->  <property>   <name>yarn.nodemanager.resource.cpu-vcores</name>   <value>2</value> </property> <property>   <name>yarn.nodemanager.resource.memory-mb</name>   <value>4096</value> </property>   <property>     <name>yarn.log.server.url</name>     <value>http://master11:19888/jobhistory/logs</value> </property>     <!-- 指定 MR 走 shuffle -->     <property>         <name>yarn.nodemanager.aux-services</name>         <value>mapreduce_shuffle</value>         </property>     <!-- 开启日志聚集功能 -->     <property>         <name>yarn.log-aggregation-enable</name>         <value>true</value>     </property>     <!-- 设置日志保留时间为 7 天 -->     <property>         <name>yarn.log-aggregation.retain-seconds</name>         <value>86400</value>     </property>      <!-- 主备配置 -->     <!-- 启用resourcemanager ha -->     <property>         <name>yarn.resourcemanager.ha.enabled</name>         <value>true</value>     </property>     <property>         <name>yarn.resourcemanager.cluster-id</name>         <value>my-yarn-cluster</value>     </property>     <!-- 声明两台resourcemanager的地址 -->     <property>         <name>yarn.resourcemanager.ha.rm-ids</name>         <value>rm1,rm2</value>     </property>     <property>         <name>yarn.resourcemanager.hostname.rm1</name>         <value>slave12</value>     </property>     <property>         <name>yarn.resourcemanager.hostname.rm2</name>         <value>slave13</value>     </property>     <property>         <name>yarn.resourcemanager.webapp.address.rm1</name>         <value>slave12:8088</value>     </property>     <property>         <name>yarn.resourcemanager.webapp.address.rm2</name>         <value>slave13:8088</value>     </property>     <!-- 指定zookeeper集群的地址 -->     <property>         <name>yarn.resourcemanager.zk-address</name>         <value>master11:2181,slave12:2181,slave13:2181</value>     </property>     <!-- 启用自动恢复 -->     <property>         <name>yarn.resourcemanager.recovery.enabled</name>         <value>true</value>     </property>    <!-- 指定resourcemanager的状态信息存储在zookeeper集群 -->     <property>         <name>yarn.resourcemanager.store.class</name>         <value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>     </property>       <property>         <name>yarn.scheduler.maximum-allocation-mb</name>         <value>2048</value>     </property>     <property>         <name>yarn.scheduler.minimum-allocation-mb</name>         <value>2048</value>     </property>     <property>         <name>yarn.nodemanager.vmem-pmem-ratio</name>         <value>2.1</value>     </property>     <property>         <name>mapred.child.java.opts</name>         <value>-Xmx1024m</value>     </property>    <property>     <name>yarn.resourcemanager.address.rm1</name>     <value>slave12:8032</value>   </property>   <property>     <name>yarn.resourcemanager.scheduler.address.rm1</name>     <value>slave12:8030</value>   </property>   <property>     <name>yarn.resourcemanager.resource-tracker.address.rm1</name>     <value>slave12:8031</value>   </property>   <property>     <name>yarn.resourcemanager.admin.address.rm1</name>     <value>slave12:8033</value>   </property>   <property>     <name>yarn.nodemanager.address.rm1</name>     <value>slave12:8041</value>   </property>   <property>     <name>yarn.resourcemanager.address.rm2</name>     <value>slave13:8032</value>   </property>   <property>     <name>yarn.resourcemanager.scheduler.address.rm2</name>     <value>slave13:8030</value>   </property>   <property>     <name>yarn.resourcemanager.resource-tracker.address.rm2</name>     <value>slave13:8031</value>   </property>   <property>     <name>yarn.resourcemanager.admin.address.rm2</name>     <value>slave13:8033</value>   </property>   <property>     <name>yarn.nodemanager.address.rm2</name>     <value>slave13:8041</value>   </property>   <property>     <name>yarn.nodemanager.localizer.address</name>     <value>0.0.0.0:8040</value>   </property>   <property>    <description>NM Webapp address.</description>     <name>yarn.nodemanager.webapp.address</name>     <value>0.0.0.0:8042</value>   </property> <property>     <name>yarn.nodemanager.address</name>     <value>${yarn.resourcemanager.hostname}:8041</value> </property> <property>  <name>yarn.application.classpath</name>  <value>/data/hadoop/etc/hadoop:/data/hadoop/share/hadoop/common/lib/*:/data/hadoop/share/hadoop/common/*:/data/hadoop/share/hadoop/hdfs:/data/hadoop/share/hadoop/hdfs/lib/*:/data/hadoop/share/hadoop/hdfs/*:/data/hadoop/share/hadoop/mapreduce/lib/*:/data/hadoop/share/hadoop/mapreduce/*:/data/hadoop/share/hadoop/yarn:/data/hadoop/share/hadoop/yarn/lib/* :/data/hadoop/share/hadoop/yarn/*</value>    </property> </configuration> 

#修改workers

vi /data/hadoop/etc/hadoop/workers master11 slave12 slave13

7  分发文件和配置

#master11 cd /data/   scp  -r   hadoop/  slave12:/data scp  -r   hadoop/  slave13:/data scp  -r  hbase/  slave13:/data scp  -r  hbase/  slave12:/data scp  -r   zookeeper/  slave12:/data scp  -r   zookeeper/  slave13:/data #3台服务器的/etc/profile 变量一致 export JAVA_HOME=/usr/local/jdk export PATH=$JAVA_HOME/bin:$PATH CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar export CLASSPATH  export HADOOP_HOME=/data/hadoop export PATH=$PATH:$HADOOP_HOME/bin:$PATH:$HADOOP_HOME/sbin export ZooKeeper_HOME=/data/zookeeper export PATH=$PATH:$ZooKeeper_HOME/bin # export HBASE_LOG_DIR=/data/hbase/logs export HBASE_MANAGES_ZK=false export HBASE_HOME=/data/hbase export PATH=$PATH:$HBASE_HOME/bin  export HIVE_HOME=/data/hive export PATH=$PATH:$HIVE_HOME/bin export HDFS_NAMENODE_USER=root export HDFS_DATANODE_USER=root export HDFS_SECONDARYNAMENODE_USER=root export YARN_RESOURCEMANAGER_USER=root export YARN_NODEMANAGER_USER=root export HDFS_ZKFC_USER=root export HDFS_DATANODE_SECURE_USER=root export HDFS_JOURNALNODE_USER=root 

8 集群启动

#HA模式第一次或删除在格式化版本

#第一次需要格式化,master11上面 start-dfs.sh hdfs  namenode -format ll /data/hadoop/data/dfs/name/current/ total 16 -rw-r--r--. 1 root root 399 May 13 20:21 fsimage_0000000000000000000 -rw-r--r--. 1 root root  62 May 13 20:21 fsimage_0000000000000000000.md5 -rw-r--r--. 1 root root   2 May 13 20:21 seen_txid -rw-r--r--. 1 root root 218 May 13 20:21 VERSION #同步数据到slave12节点(其余namenode节点) scp  -r  /data/hadoop/data/dfs/name/*  slave12:/data/hadoop/data/dfs/name/ #成功如图

#在任意一台 NameNode上初始化 ZooKeeper 中的 HA 状态 [root@master11 hadoop]# jps 2400 QuorumPeerMain 4897 Jps 3620 JournalNode 3383 DataNode # hdfs zkfc -formatZK #如下图

 

#集群正常启动顺序

#zookeeper,3台服务器都执行 zkServer.sh start #查看 [root@master11 ~]# zkServer.sh status ZooKeeper JMX enabled by default Using config: /data/zookeeper/bin/../conf/zoo.cfg Client port found: 2181. Client address: localhost. Client SSL: false. Mode: follower [root@slave12 data]# zkServer.sh status ZooKeeper JMX enabled by default Using config: /data/zookeeper/bin/../conf/zoo.cfg Client port found: 2181. Client address: localhost. Client SSL: false. Mode: leader [root@slave13 ~]# zkServer.sh  status ZooKeeper JMX enabled by default Using config: /data/zookeeper/bin/../conf/zoo.cfg Client port found: 2181. Client address: localhost. Client SSL: false. Mode: follower #master11 ,hadoop集群一键启动 start-all.sh start #一键停止 stop-all.sh #jps 查看如图

 

#查看集群状态

#NameNode [root@master11 ~]# hdfs  haadmin  -getServiceState nn1 active [root@master11 ~]# hdfs  haadmin  -getServiceState nn2 standby [root@master11 ~]# hdfs haadmin -ns mycluster -getAllServiceState master11:8020                                      active     slave12:8020                                       standby #yarn [root@master11 ~]# yarn rmadmin -getServiceState rm1 standby [root@master11 ~]# yarn rmadmin -getServiceState rm2 active 

#查看HDFS web ui

 

#查看 yarn集群

9 hadoop 测试使用

#创建目录 hdfs dfs  -mkdir  /testdata #查看 [root@master11 ~]# hdfs dfs  -ls / Found 2 items drwxr-xr-x   - root supergroup          0 2024-05-14 17:00 /hbase drwxr-xr-x   - root supergroup          0 2024-05-14 20:32 /testdata #上传文件 hdfs dfs  -put  jdk-8u191-linux-x64.tar.gz   /testdata #查看文件 [root@master11 soft]# hdfs dfs  -ls /testdata/ Found 1 items -rw-r--r--   3 root supergroup  191753373 2024-05-14 20:40 /testdata/jdk-8u191-linux-x64.tar.gz

 

 

 

10 启动Hbase,hadoop的active节点

[root@master11 ~]# hdfs  haadmin  -getServiceState nn1 active #启动 start-hbase.sh #查看 [root@master11 ~]# jps 16401 NodeManager 15491 NameNode 21543 HMaster 15848 JournalNode 1435 QuorumPeerMain 16029 DFSZKFailoverController 21902 Jps 15631 DataNode

 11 安装Hive

#解压和配置环境变量

tar zxvf apache-hive-4.0.0-bin.tar.gz mv  apache-hive-4.0.0-bin/  /data/hive #环境变量 vi /etc/profile export HIVE_HOME=/data/hive export PATH=$PATH:$HIVE_HOME/bin source /etc/profile

# 安装mysql ,可参考

mysql 8.3 二进制版本安装

#mysql驱动

mv mysql-connector-java-8.0.29.jar  /data/hive/lib/
schematool -dbType mysql -initSchema #报错 SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in [jar:file:/data/hive/lib/log4j-slf4j-impl-2.18.0.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/data/hadoop/share/hadoop/common/lib/slf4j-reload4j-1.7.36.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory] Exception in thread "main" [com.ctc.wstx.exc.WstxLazyException] com.ctc.wstx.exc.WstxUnexpectedCharException: Unexpected character '=' (code 61); expected a semi-colon after the reference for entity 'characterEncoding'  at [row,col,system-id]: [5,86,"file:/data/hive/conf/hive-site.xml"] 	at com.ctc.wstx.exc.WstxLazyException.throwLazily(WstxLazyException.java:40) 	at com.ctc.wstx.sr.StreamScanner.throwLazyError(StreamScanner.java:737) 	at com.ctc.wstx.sr.BasicStreamReader.safeFinishToken(BasicStreamReader.java:3745) 	at com.ctc.wstx.sr.BasicStreamReader.getTextCharacters(BasicStreamReader.java:914) 	at org.apache.hadoop.conf.Configuration$Parser.parseNext(Configuration.java:3434) 	at org.apache.hadoop.conf.Configuration$Parser.parse(Configuration.java:3213) 	at org.apache.hadoop.conf.Configuration.loadResource(Configuration.java:3106) 	at org.apache.hadoop.conf.Configuration.loadResources(Configuration.java:3072) 	at org.apache.hadoop.conf.Configuration.loadProps(Configuration.java:2945) 	at org.apache.hadoop.conf.Configuration.getProps(Configuration.java:2927) 	at org.apache.hadoop.conf.Configuration.set(Configuration.java:1431) 	at org.apache.hadoop.conf.Configuration.set(Configuration.java:1403) 	at org.apache.hadoop.hive.metastore.conf.MetastoreConf.newMetastoreConf(MetastoreConf.java:2120) 	at org.apache.hadoop.hive.metastore.conf.MetastoreConf.newMetastoreConf(MetastoreConf.java:2072) 	at org.apache.hive.beeline.schematool.HiveSchemaTool.main(HiveSchemaTool.java:144) 	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) 	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 	at java.lang.reflect.Method.invoke(Method.java:498) 	at org.apache.hadoop.util.RunJar.run(RunJar.java:330) 	at org.apache.hadoop.util.RunJar.main(RunJar.java:245) Caused by: com.ctc.wstx.exc.WstxUnexpectedCharException: Unexpected character '=' (code 61); expected a semi-colon after the reference for entity 'characterEncoding'  at [row,col,system-id]: [5,86,"file:/data/hive/conf/hive-site.xml"] 	at com.ctc.wstx.sr.StreamScanner.throwUnexpectedChar(StreamScanner.java:666) 	at com.ctc.wstx.sr.StreamScanner.parseEntityName(StreamScanner.java:2080) 	at com.ctc.wstx.sr.StreamScanner.fullyResolveEntity(StreamScanner.java:1538) 	at com.ctc.wstx.sr.BasicStreamReader.readTextSecondary(BasicStreamReader.java:4765) 	at com.ctc.wstx.sr.BasicStreamReader.finishToken(BasicStreamReader.java:3789) 	at com.ctc.wstx.sr.BasicStreamReader.safeFinishToken(BasicStreamReader.java:3743) 	... 18 more #解决 vi /data/hive/conf/hive-site.xml &字符 需要转义 改成 &amp; #成功提示 Initialization script completed 数据库如下图 

 

#启动,hive 在master11,mysql 安装在slave12 

cd /data/hive/ nohup hive --service metastore & (启动hive元数据服务) nohup ./bin/hiveserver2 & (启动jdbc连接服务) #直接hive,提示“No current connection” hive [root@master11 hive]# hive SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in [jar:file:/data/hive/lib/log4j-slf4j-impl-2.18.0.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/data/hadoop/share/hadoop/common/lib/slf4j-reload4j-1.7.36.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory] SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in [jar:file:/data/hive/lib/log4j-slf4j-impl-2.18.0.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/data/hadoop/share/hadoop/common/lib/slf4j-reload4j-1.7.36.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory] Beeline version 4.0.0 by Apache Hive beeline> show  databases; No current connection beeline>  #在提示符 输入!connect jdbc:hive2://master11:10000,之后输入mysql用户和密码 beeline> !connect jdbc:hive2://master11:10000 Connecting to jdbc:hive2://master11:10000 Enter username for jdbc:hive2://master11:10000: root Enter password for jdbc:hive2://master11:10000: ********* Connected to: Apache Hive (version 4.0.0) Driver: Hive JDBC (version 4.0.0) Transaction isolation: TRANSACTION_REPEATABLE_READ 0: jdbc:hive2://master11:10000> show  databases; INFO  : Compiling command(queryId=root_20240514222349_ac19af6a-3c43-49fd-bcd0-25fc0e5b76c6): show  databases INFO  : Semantic Analysis Completed (retrial = false) INFO  : Created Hive schema: Schema(fieldSchemas:[FieldSchema(name:database_name, type:string, comment:from deserializer)], properties:null) INFO  : Completed compiling command(queryId=root_20240514222349_ac19af6a-3c43-49fd-bcd0-25fc0e5b76c6); Time taken: 0.021 seconds INFO  : Concurrency mode is disabled, not creating a lock manager INFO  : Executing command(queryId=root_20240514222349_ac19af6a-3c43-49fd-bcd0-25fc0e5b76c6): show  databases INFO  : Starting task [Stage-0:DDL] in serial mode INFO  : Completed executing command(queryId=root_20240514222349_ac19af6a-3c43-49fd-bcd0-25fc0e5b76c6); Time taken: 0.017 seconds +----------------+ | database_name  | +----------------+ | default        | +----------------+ 1 row selected (0.124 seconds) 0: jdbc:hive2://master11:10000>

Hadoop3.4.0+HBase2.5.8+ZooKeeper3.8.4+Hive4.0+Sqoop 分布式高可用集群部署安装,已完成。欢迎大家一起交流哦。下一篇,项目实战。

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