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

创建服务器,参考

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 &
#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。