Hadoop3+Hive3安装记录（虚拟机搭建分布式环境，报错解决）

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Hadoop官方下载地址

Hive官方下载地址

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概述

工具：VMware 14

目的：创建三个虚拟机，网络以桥接模式，三台虚拟机在同一网段，保证三台机器能够相互ping通。

流程步骤：
① 下载 CentOS7 ISO镜像使用VM创建第一个虚拟机；
② 通过 VM 克隆创建剩下两个虚拟机；
③ 设置三个系统的主机名以及网络，并相互设置ssh免密登录；
④ 安装JDK；
⑤ 安装 Hadoop3.2 ；
⑥ 安装 Hive3.1 ；

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配置Linux主机信息

• 修改主机名称(CentOS7)

 # 使用这个命令会立即生效且重启也生效
[root@smallsuperman ~]# hostnamectl set-hostname outman00
[root@smallsuperman ~]# hostname
outman00

 # 编辑下hosts文件， 给127.0.0.1添加hostname
[root@smallsuperman ~]# vi /etc/hosts  
[root@smallsuperman ~]# cat /etc/hosts 
127.0.0.1   localhost smallsuperman.centos localhost4 localhost4.localdomain4 outman00
::1         localhost smallsuperman.centos localhost6 localhost6.localdomain6

• 内网映射

# 主机名代替ip访问
[root@smallsuperman ~]# sed -i '$a\192.168.233.132 outman00' /etc/hosts
[root@smallsuperman ~]# sed -i '$a\192.168.233.130 outman01' /etc/hosts
[root@smallsuperman ~]# sed -i '$a\192.168.233.131 outman02' /etc/hosts
[root@smallsuperman ~]# ping outman00 # 测试通否
PING localhost (127.0.0.1) 56(84) bytes of data

• 关闭防火墙

# 检查防火墙状态
# 看到绿色字样标注的“active（running）”，说明防火墙是开启状态
# disavtive（dead）的字样，说明防火墙已经关闭
[root@smallsuperman ~]# systemctl status firewalld.service

# 关闭运行的防火墙
[root@smallsuperman ~]# systemctl stop firewalld.service

# 禁止防火墙服务器，系统重启不会开启防火墙
[root@smallsuperman ~]# systemctl disable firewalld.service

• 创建Hadoop用户，并赋权

# 增加一个用户
[root@smallsuperman ~]# adduser hadoop

# 赋权
以root用户身份为hadoop用户赋权，在 root 账号下，命令终端输入：vi /etc/sudoers
找到
root ALL=(ALL) ALL
添加一行内容
hadoop ALL=(ALL) ALL

• 设置SSH免密登录

# 每个主机都生成密钥（一直回车） 
[hadoop@outman02 ~]$ ssh-keygen

Generating public/private rsa key pair.
Enter file in which to save the key (/home/hadoop/.ssh/id_rsa): 
Created directory '/home/hadoop/.ssh'.
Enter passphrase (empty for no passphrase): 
Enter same passphrase again: 
Your identification has been saved in /home/hadoop/.ssh/id_rsa.
Your public key has been saved in /home/hadoop/.ssh/id_rsa.pub.
The key fingerprint is:
SHA256:rKWn0xjk+J3ZShFMO3pYx6sBxCpl1YkUojNsG4HQ1iE hadoop@outman02
The key's randomart image is:
+---[RSA 2048]----+
|ooE.o==+..       |
|..o++ooooo       |
| .Bo .. * o      |
| ..=. .* + .     |
|  .. +o S .      |
|    . o= +       |
|     .o=++       |
|      ++= .      |
|      ....       |
+----[SHA256]-----+

# 与其他主机建立免密连接，将自己的公钥拷贝至其他主机的authorized_keys文件中。
[hadoop@outman02 ~]$ ssh-copy-id outman01
[hadoop@outman02 ~]$ ssh-copy-id outman00
[hadoop@outman01 ~]$ ssh-copy-id outman00
[hadoop@outman01 ~]$ ssh-copy-id outman02
[hadoop@outman00 ~]$ ssh-copy-id outman01
[hadoop@outman00 ~]$ ssh-copy-id outman02

# 测试一下免密登录
[hadoop@outman00 ~]$ ssh hadoop@outman01
Last failed login: Mon Jun  3 02:16:04 CST 2019 from outman00 on ssh:notty
There were 3 failed login attempts since the last successful login.
Last login: Mon Jun  3 02:13:15 2019
[hadoop@outman01 ~]$ pwd
/home/hadoop

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安装JDK

1、去官网下载软件的安装压缩包 ；
2、上传一份到主机临时目录下（我的是在/tmp/tar_gz），然后通过 scp 到另外两个服务器相同位置；

• 解压到指定目录下

[root@outman02 tar_gz]# tar -zxvf jdk-8u211-linux-x64.tar.gz -C /usr/local/my_app

• 配置环境变量

[root@outman00 jdk1.8.0_211]# sed  -i '$a\\nexport JAVA_HOME=/usr/local/my_app/jdk1.8.0_211\nexport PATH=$PATH:$JAVA_HOME/bin ' /etc/profile
# 更新加载环境变量 
[root@outman00 jdk1.8.0_211]# source /etc/profile
# 检查是否安装成功
[root@outman00 jdk1.8.0_211]# java -version
java version "1.8.0_211"
Java(TM) SE Runtime Environment (build 1.8.0_211-b12)
Java HotSpot(TM) 64-Bit Server VM (build 25.211-b12, mixed mode)

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安装Hadoop

主要目录
（1）bin目录：存放对Hadoop相关服务（HDFS,YARN）进行操作的脚本
（2）etc目录：Hadoop的配置文件目录，存放Hadoop的配置文件
（3）lib目录：存放Hadoop的本地库（对数据进行压缩解压缩功能）
（4）sbin目录：存放启动或停止Hadoop相关服务的脚本
（5）share目录：存放Hadoop的依赖jar包、文档、和官方案例

• 解压到指定目录下

[root@outman00 tar_gz]# tar -zxvf hadoop-3.2.0.tar.gz  -C /usr/local/my_app/hadoop

修改配置文件

• 进入解压路径

[root@outman00 hadoop-3.2.0]# cd /usr/local/my_app/hadoop/hadoop-3.2.0/etc/hadoop/

• 修改配置文件中JDK路径

[root@outman00 hadoop]# vi /usr/local/my_app/hadoop/hadoop-3.2.0/etc/hadoop/hadoop-env.sh

# 修改内容，添加JDK的路径信息
    52 # The java implementation to use. By default, this environment
    53 # variable is REQUIRED on ALL platforms except OS X!
    54 export JAVA_HOME=/usr/local/my_app/jdk1.8.0_211

• 修改 core-site.xml 文件

fs.defaultFS HDFS中NameNode的地址 端口。
hadoop.tmp.dir Hadoop运行时产生文件的存储目录。

 fs.defaultFS
 hdfs://outman00:9000


 hadoop.tmp.dir
 /usr/local/my_app/hadoop/hadoop_data

• 修改 hdfs-site.xml

  dfs.namenode.name.dir
  /usr/local/my_app/hadoop/hadoop_data/namenode_data
  元数据存储目录，安全起见可配置到其他目录



  dfs.datanode.data.dir
  /usr/local/my_app/hadoop/hadoop_data/datanode_data
  datanode 的数据存储目录



   dfs.replication
   2
   HDFS 的数据块的副本个数



   dfs.secondary.http.address
   outman01:50090
   secondarynamenode 节点信息，最好是和namenode 设置为不同节点
   

• 修改 yarn-site.xml

yarn.nodemanager.aux-services YARN 集群为 MapReduce 程序提供的 shuffle 服务
yarn.resourcemanager.hostname ResourceManager的信息

    yarn.nodemanager.aux-services
    mapreduce_shuffle




    yarn.resourcemanager.hostname
    outman00

• 修改 mapred-site.xml

配置采用yarn作为资源调度框架（指定MR运行在YARN上）

    mapreduce.framework.name
    yarn

• 修改workers （3.0之前是slaves文件 ）

outman00
outman01
outman02

• 把安装的Hadoop目录文件分发给另外两个节点（scp过去）

[hadoop@outman00 hadoop]$ scp -r hadoop-3.2.0/ hadoop@outman02:/usr/local/my_app/hadoop
[hadoop@outman00 hadoop]$ scp -r hadoop-3.2.0/ hadoop@outman01:/usr/local/my_app/hadoop

• 配置环境变量（三个节点 /etc/profile）

[root@outman00 hadoop]# sed -i '$a\export HADOOP_HOME=/usr/local/my_app/hadoop/hadoop-3.2.0\nexport PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin' /etc/profile

# 更新环境变量配置
[root@outman00 hadoop]# source /etc/profile

# 验证
[root@outman02 hadoop]# hadoop --help

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• 初始化namenode

在HDFS 主节点(core-site.xml中配置的fs.defaultFS),执行初始化命令，成功后会根据配置的信息创建对应的data目录如果需要重新初始化，删除后重新执行即可！

[root@outman00 hadoop]# hadoop namenode -format

# 判断成功关键信息
2019-06-05 01:58:12,198 INFO common.Storage: Storage directory /usr/local/my_app/hadoop/hadoop_data/namenode_data has been successfully formatted.

• 启动hdfs（执行启动脚本任意节点）

[hadoop@outman00 ~]$ start-dfs.sh

[hadoop@outman00 ~]$ jps
8949 DataNode
8840 NameNode
9229 Jps
[hadoop@outman01 hadoop_data]$ jps
8071 SecondaryNameNode
8137 Jps
7997 DataNode
[hadoop@outman02 hadoop_data]$ jps
7973 Jps
7817 DataNode

• 出现问题

  • NameDode 主节点可以访问hdfs，但是另外两个节点无法访问
• 报错信息

# 主节点正常访问
[hadoop@outman00 ~]$ hadoop fs -ls /
Found 1 items
drwxr-xr-x   - hadoop supergroup          0 2019-06-06 00:34 /dyp

# 次节点无法访问
[hadoop@outman01 ~]$ hadoop fs -ls /
ls: Call From outman01/192.168.233.130 to outman00:9000 failed on connection exception: java.net.ConnectException: 拒绝连接; For more details see:  http://wiki.apache.org/hadoop/ConnectionRefused

# 次节点无法访问
[hadoop@outman02 ~]$ hadoop fs -ls /
ls: Call From localhost/127.0.0.1 to outman00:9000 failed on connection exception: java.net.ConnectException: 拒绝连接; For more details see:  http://wiki.apache.org/hadoop/ConnectionRefused

• 根据配置信息 core-site.xml 检查是否可以访问主节点的9000端口

# 主节点可以
[root@outman00 datanode_data]# telnet  outman00 9000
Trying 127.0.0.1...
Connected to outman00.
Escape character is '^]'.

# 次节点不可以
[root@outman01 ~]# telnet  outman00 9000
Trying 192.168.233.132...
telnet: connect to address 192.168.233.132: Connection refused
[root@outman02 xinetd.d]# telnet  outman00 9000
Trying 192.168.233.132...
telnet: connect to address 192.168.233.132: Connection refused

• 检查主节点9000端口占用情况

发现9000端口被 127.0.0.1:本地占用，也就是只有本地才能访问 （HDFS监听的9000端口默认绑定127.0.0.1地址）

[root@outman00 datanode_data]# lsof -i:9000
COMMAND  PID   USER   FD   TYPE DEVICE SIZE/OFF NODE NAME
java    7339 hadoop  269u  IPv4  42236      0t0  TCP localhost:cslistener (LISTEN)
java    7339 hadoop  279u  IPv4  44037      0t0  TCP localhost:cslistener->localhost:51560 (ESTABLISHED)
java    7413 hadoop  328u  IPv4  44036      0t0  TCP localhost:51560->localhost:cslistener (ESTABLISHED)
[root@outman00 datanode_data]# netstat -tunlp |grep 9000
tcp        0      0 127.0.0.1:9000          0.0.0.0:*               LISTEN      7339/java   

• 尝试修改host配置

#127.0.0.1   localhost smallsuperman.centos localhost4 localhost4.localdomain4 outman00
#::1         localhost smallsuperman.centos localhost6 localhost6.localdomain6
192.168.233.132 outman00
192.168.233.130 outman01
192.168.233.131 outman02

• 重启hadoop

[hadoop@outman00 ~]$ stop-all.sh
[hadoop@outman00 ~]$ start-all.sh

• 检查主节点NameNode上9000占用（占用的ip变成了主节点其他节点可以访问了）

[root@outman00 datanode_data]# netstat -tunlp | grep 9000
tcp        0      0 192.168.233.132:9000    0.0.0.0:*               LISTEN      10843/java 

• 其他节点访问hdfs

[hadoop@outman01 ~]$ hadoop fs -ls /
Found 1 items
drwxr-xr-x   - hadoop supergroup          0 2019-06-06 00:34 /dyp
[hadoop@outman02 ~]$ hadoop fs -ls /
Found 1 items
drwxr-xr-x   - hadoop supergroup          0 2019-06-06 00:34 /dyp

• 访问 HDFS 前台页面

http://192.168.233.132:9870

特别注意

hadoop3.0之前web访问端口是50070
hadoop3.0之后web访问端口为9870

---

• 启动yarn（要在yarn的主节点启动）

[hadoop@outman00 hadoop_data]$ start-yarn.sh
Starting resourcemanager
Starting nodemanagers

# 查看进程（主节点增加 ResourceManager 、NodeManager 其他节点增加 NodeManager）
[hadoop@outman00 hadoop_data]$ jps
9811 Jps
8949 DataNode
9463 NodeManager
8840 NameNode
9353 ResourceManager
[hadoop@outman01 hadoop_data]$ jps
8227 NodeManager
8071 SecondaryNameNode
8327 Jps
7997 DataNode

• 测试yarn

[hadoop@outman00 mapreduce]$ hadoop jar hadoop-mapreduce-examples-3.2.0.jar wordcount  /dyp/test/test  /dyp/test/test_out

# 报错
[2019-06-06 02:01:09.415]Container exited with a non-zero exit code 1. Error file: prelaunch.err.
Last 4096 bytes of prelaunch.err :
Last 4096 bytes of stderr :
错误: 找不到或无法加载主类 org.apache.hadoop.mapreduce.v2.app.MRAppMaster
# 解决方法  ：  在配置文件 mapred-site.xml 文件中添加 mapreduce 程序所用到的 classpath 如下
# /usr/local/my_app/hadoop/hadoop-3.2.0/ 就是hadoop安装路径


    mapreduce.framework.name
    yarn



    mapreduce.application.classpath
    /usr/local/my_app/hadoop/hadoop-3.2.0/share/hadoop/mapreduce/*, /usr/local/my_app/hadoop/hadoop-3.2.0/share/hadoop/mapreduce/lib/*

• 再次测试

[hadoop@outman00 mapreduce]$ hadoop jar hadoop-mapreduce-examples-3.2.0.jar wordcount  /dyp/test/test  /dyp/test/test_out

[hadoop@outman00 mapreduce]$ hadoop fs -ls  /dyp/test/test_out
Found 2 items
-rw-r--r--   2 hadoop supergroup          0 2019-06-06 02:16 /dyp/test/test_out/_SUCCESS
-rw-r--r--   2 hadoop supergroup         29 2019-06-06 02:16 /dyp/test/test_out/part-r-00000
[hadoop@outman00 mapreduce]$ hadoop fs -cat  /dyp/test/test_out/part-r-00000
1|2|3   1
A|B|C   1
A|B|C1|2|3  1

---

安装 MySQL

我这里使用腾讯云服务器上安装在 Docker 中的 MySQL，所以在虚拟上只需要安装MySQL的客户端就可以了，只用于访问

• 安装mysql-client

[root@outman00 ~]# yum  install mysql

# 连接腾讯云MySQL
[root@outman00 ~]# mysql -h 腾讯云MySQL的IP -u root -p

---

安装Hive3

• 解压到指定目录下

[root@outman00 tar_gz]# tar -zxvf apache-hive-3.1.1-bin.tar.gz -C /usr/local/my_app/hive

• 下载 MySQL 的 Java 驱动并上传到 Hive 的lib路径下
  官网下载地址

-rw-r--r--. 1 root root  2293144 6月   7 02:07 mysql-connector-java-8.0.16.jar
[root@outman00 lib]# pwd
/usr/local/my_app/hive/hive-3.1.1/lib

• 配置Hive环境变量

[root@outman00 lib]# sed -i '$a\export HIVE_HOME=/usr/local/my_app/hive/hive-3.1.1\nexport PATH=$PATH:$HIVE_HOME/bin' /etc/profile

# 更新生效
[root@outman00 lib]# source /etc/profile

• 修改配置文件

[root@outman00 conf]# cd /usr/local/my_app/hive/hive-3.1.1/conf
[root@outman00 conf]# cp hive-env.sh.template hive-env.sh
[root@outman00 conf]# cp hive-default.xml.template hive-site.xml

• hive-env.sh 添加以下内容

export JAVA_HOME=/usr/local/my_app/jdk1.8.0_211

export HADOOP_HOME=/usr/local/my_app/hadoop/hadoop-3.2.0

export HIVE_HOME=/usr/local/my_app/hive/hive-3.1.1

• 更新生效

[root@outman00 conf]# source hive-env.sh

• 修改 hive-site.xml

• 先创建目录

[root@outman00 conf]# mkdir -p /usr/local/my_app/hive/hive_data/warehouse
[root@outman00 conf]# mkdir -p /usr/local/my_app/hive/hive_data/tmp
[root@outman00 conf]# mkdir -p /usr/local/my_app/hive/hive_data/log

• 修改 hive-site.xml

    javax.jdo.option.ConnectionDriverName
    com.mysql.jdbc.Driver
    Driver class name for a JDBC metastore


    javax.jdo.option.ConnectionUserName
    用户名
    username to use against metastore database
 

    javax.jdo.option.ConnectionPassword
    密码
    password to use against metastore database


    hive.metastore.warehouse.dir
    /usr/local/my_app/hive/hive_datawarehouse
    location of default database for the warehouse


    hive.exec.scratchdir
    /usr/local/my_app/hive/hive_data/tmp
    HDFS root scratch dir for Hive jobs which gets created with write all (733) permission. For each connecting user, an HDFS scratch dir: ${hive.exec.scratchdir}/<username> is created, with ${hive.scratch.dir.permission}.


    hive.querylog.location
    /usr/local/my_app/hive/hive_data/log
    Location of Hive run time structured log file


# 我们把变量  $system:java.io.tmpdir 替换成我们的临时数据存放目录 /usr/local/my_app/hive/hive_data/tmp

• 修改 hive-log4j.proprties 文件

• hive启动报错如下

Caused by: com.ctc.wstx.exc.WstxParsingException: Illegal character entity: expansion character (code 0x8
at [row,col,system-id]: [3186,96,"file:/usr/local/my_app/hive/hive-3.1.1/conf/hive-site.xml"

配置文件 hive-site.xml 3186行96个字符不合法

# 详细报错
Exception in thread "main" java.lang.RuntimeException: com.ctc.wstx.exc.WstxParsingException: Illegal character entity: expansion character (code 0x8
 at [row,col,system-id]: [3186,96,"file:/usr/local/my_app/hive/hive-3.1.1/conf/hive-site.xml"]
    at org.apache.hadoop.conf.Configuration.loadResource(Configuration.java:2981)
    at org.apache.hadoop.conf.Configuration.loadResources(Configuration.java:2930)
    at org.apache.hadoop.conf.Configuration.getProps(Configuration.java:2805)
    at org.apache.hadoop.conf.Configuration.get(Configuration.java:1459)
    at org.apache.hadoop.hive.conf.HiveConf.getVar(HiveConf.java:4990)
    at org.apache.hadoop.hive.conf.HiveConf.getVar(HiveConf.java:5063)
    at org.apache.hadoop.hive.conf.HiveConf.initialize(HiveConf.java:5150)
    at org.apache.hadoop.hive.conf.HiveConf.(HiveConf.java:5093)
    at org.apache.hadoop.hive.common.LogUtils.initHiveLog4jCommon(LogUtils.java:97)
    at org.apache.hadoop.hive.common.LogUtils.initHiveLog4j(LogUtils.java:81)
    at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:699)
    at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:683)
    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:323)
    at org.apache.hadoop.util.RunJar.main(RunJar.java:236)
Caused by: com.ctc.wstx.exc.WstxParsingException: Illegal character entity: expansion character (code 0x8
 at [row,col,system-id]: [3186,96,"file:/usr/local/my_app/hive/hive-3.1.1/conf/hive-site.xml"]
    at com.ctc.wstx.sr.StreamScanner.constructWfcException(StreamScanner.java:621)
    at com.ctc.wstx.sr.StreamScanner.throwParseError(StreamScanner.java:491)
    at com.ctc.wstx.sr.StreamScanner.reportIllegalChar(StreamScanner.java:2456)
    at com.ctc.wstx.sr.StreamScanner.validateChar(StreamScanner.java:2403)
    at com.ctc.wstx.sr.StreamScanner.resolveCharEnt(StreamScanner.java:2369)
    at com.ctc.wstx.sr.StreamScanner.fullyResolveEntity(StreamScanner.java:1515)
    at com.ctc.wstx.sr.BasicStreamReader.nextFromTree(BasicStreamReader.java:2828)
    at com.ctc.wstx.sr.BasicStreamReader.next(BasicStreamReader.java:1123)
    at org.apache.hadoop.conf.Configuration$Parser.parseNext(Configuration.java:3277)
    at org.apache.hadoop.conf.Configuration$Parser.parse(Configuration.java:3071)
    at org.apache.hadoop.conf.Configuration.loadResource(Configuration.java:2964)
    ... 17 more

• 启动 metastore 报错

报错信息

hadoop@outman00 hive-3.1.1]$  hive --service metastore 

2019-06-07 23:25:27: Starting Hive Metastore Server
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/my_app/hive/hive-3.1.1/lib/log4j-slf4j-impl-2.10.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/my_app/hadoop/hadoop-3.2.0/share/hadoop/common/lib/slf4j-log4j12-1.7.25.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]
MetaException(message:Version information not found in metastore.)
    at org.apache.hadoop.hive.metastore.RetryingHMSHandler.(RetryingHMSHandler.java:84)
    at org.apache.hadoop.hive.metastore.RetryingHMSHandler.getProxy(RetryingHMSHandler.java:93)
    at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:8661)
    at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:8656)
    at org.apache.hadoop.hive.metastore.HiveMetaStore.startMetaStore(HiveMetaStore.java:8926)
    at org.apache.hadoop.hive.metastore.HiveMetaStore.main(HiveMetaStore.java:8843)
    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:323)
    at org.apache.hadoop.util.RunJar.main(RunJar.java:236)

分析报错

• jar包冲突，关键信息

[jar:file:/usr/local/my_app/hive/hive-3.1.1/lib/log4j-slf4j-impl-2.10.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/my_app/hadoop/hadoop-3.2.0/share/hadoop/common/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class

• 删除 HVIE_HOME/bin 下的jar
• 不要删除HADOOP_HOME/bin下的jar包否则start-all.sh远程启动hadoop时会报找不到log4j包的错误。

rm -rf /usr/local/my_app/hive/hive-3.1.1/lib/log4j-slf4j-impl-2.10.0.jar

• 启动metastore仍然报错内容如下

2019-06-07 23:41:43: Starting Hive Metastore Server
MetaException(message:Version information not found in metastore.)
    at org.apache.hadoop.hive.metastore.RetryingHMSHandler.(RetryingHMSHandler.java:84)
    at org.apache.hadoop.hive.metastore.RetryingHMSHandler.getProxy(RetryingHMSHandler.java:93)
    at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:8661)
    at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:8656)
    at org.apache.hadoop.hive.metastore.HiveMetaStore.startMetaStore(HiveMetaStore.java:8926)
    at org.apache.hadoop.hive.metastore.HiveMetaStore.main(HiveMetaStore.java:8843)
    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:323)
    at org.apache.hadoop.util.RunJar.main(RunJar.java:236)

• 尝试解决 在hvie-site.xml（继续报错）

# 关闭元数据验证
     
    datanucleus.metadata.validate    
    false    
 
# 关闭元数据存储模式验证
  
    hive.metastore.schema.verification 
    false 


    datanucleus.schema.autoCreateAll
    ture

# 其中hive.metastore.schema.verification防止架构版本不兼容时的 Metastore 操作。考虑将此设置为“True”，以减少 Metastore 操作期间发生架构损坏的可能性

• 如果是第一次需要执行初始化命令：schematool -dbType mysql -initSchema

[hadoop@outman00 hive-3.1.1]$ schematool -dbType mysql -initSchema

# 发现MySQL中创建了hive库
MySQL [(none)]> show databases;
+--------------------+
| Database           |
+--------------------+
| dyp                |
| hive               |
| information_schema |
| mysql              |
| performance_schema |
| sys                |
+--------------------+

---

正常启动 metastore 后 进入 hive 交互，报错如下

hive> show databases;
OK
Failed with exception java.io.IOException:java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: ${system:user.name%7D

• 修改配置

  
    hive.exec.local.scratchdir
    /usr/local/my_app/hive/hive_data/tmp/${user.name}
    Local scratch space for Hive jobs
  

---

启动后节点信息

启动后节点信息

outman00	outman01	outman02
DataNode NameNode NodeManager ResourceManager	DataNode NodeManager SecondaryNameNode	DataNode NodeManager

概念说明

• NameNode

负责管理整个 HDFS 文件系统的元数据:配置副本策略、管理我们存储数据块(Block)映射信息、管理HDFS名称空间、处理客户端读写请求

• SecondaryNameNode

是 NameNode 的辅助分担任务，定期合并fsimage和edits文件，可以辅助恢复NameNode；

• DataNode

负责管理用户的文件数据块:根据NameNode下发的任务命令，DataNode去执行对应的操作。（存储实际数据块、执行数据块的读写操作）
文件会按照固定大小（blocksize）来切分成块后分布式存储在若干台DataNode上
每一个文件快可以有多个副本，并存放在不同的 DataNode 上 DataNode 会定期向 NameNode 汇报自身所保存的文件block信息，而 NameNode 则会负责保持文件的副本数量（当减少DataNode的时候，NameNode才知道当前副本状态，从而进行副本维持）

• YARN 负责将系统资源分配给在 Hadoop 集群中运行的各种应用程序，并调度要在不同集群节点上执行的任务
• YARN 的组件 ResourceManager

ResourceManager 是在系统中的所有应用程序之间仲裁资源的最终权限。

• YARN 的组件 ResourceManager

NodeManager 是每台机器框架代理，负责 Containers，监视其资源使用情况（CPU，内存，磁盘，网络）并将其报告给 ResourceManager。