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Hadoop官方下载地址
Hive官方下载地址
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 ；
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
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:$JAVA_HOME/bin ' /etc/profile
# 更新加载环境变量
[root@outman00 jdk1.8.0_211]# source /etc/profile
# 检查是否安装成功
[root@outman00 jdk1.8.0_211]# java -version
java version "1.8.0_211"
Java(TM) SE Runtime Environment (build 1.8.0_211-b12)
Java HotSpot(TM) 64-Bit Server VM (build 25.211-b12, mixed mode)
安装Hadoop
主要目录
（1）bin目录：存放对Hadoop相关服务（HDFS,YARN）进行操作的脚本
（2）etc目录：Hadoop的配置文件目录，存放Hadoop的配置文件
（3）lib目录：存放Hadoop的本地库（对数据进行压缩解压缩功能）
（4）sbin目录：存放启动或停止Hadoop相关服务的脚本
（5）share目录：存放Hadoop的依赖jar包、文档、和官方案例
- 解压到指定目录下
[root@outman00 tar_gz]# tar -zxvf hadoop-3.2.0.tar.gz -C /usr/local/my_app/hadoop
修改配置文件
- 进入解压路径
[root@outman00 hadoop-3.2.0]# cd /usr/local/my_app/hadoop/hadoop-3.2.0/etc/hadoop/
- 修改配置文件中JDK路径
[root@outman00 hadoop]# vi /usr/local/my_app/hadoop/hadoop-3.2.0/etc/hadoop/hadoop-env.sh
# 修改内容，添加JDK的路径信息
52 # The java implementation to use. By default, this environment
53 # variable is REQUIRED on ALL platforms except OS X!
54 export JAVA_HOME=/usr/local/my_app/jdk1.8.0_211
- 修改 core-site.xml 文件
fs.defaultFSHDFS中NameNode的地址 端口。
hadoop.tmp.dirHadoop运行时产生文件的存储目录。
fs.defaultFS
hdfs://outman00:9000
hadoop.tmp.dir
/usr/local/my_app/hadoop/hadoop_data
- 修改 hdfs-site.xml
dfs.namenode.name.dir
/usr/local/my_app/hadoop/hadoop_data/namenode_data
元数据存储目录，安全起见可配置到其他目录
dfs.datanode.data.dir
/usr/local/my_app/hadoop/hadoop_data/datanode_data
datanode 的数据存储目录
dfs.replication
2
HDFS 的数据块的副本个数
dfs.secondary.http.address
outman01:50090
secondarynamenode 节点信息，最好是和namenode 设置为不同节点
- 修改 yarn-site.xml
yarn.nodemanager.aux-services YARN集群为 MapReduce 程序提供的 shuffle 服务
yarn.resourcemanager.hostnameResourceManager的信息
yarn.nodemanager.aux-services
mapreduce_shuffle
yarn.resourcemanager.hostname
outman00
- 修改 mapred-site.xml
配置采用yarn作为资源调度框架（指定MR运行在YARN上）
mapreduce.framework.name
yarn
- 修改workers （3.0之前是slaves文件 ）
outman00
outman01
outman02
- 把安装的Hadoop目录文件分发给另外两个节点（scp过去）
[hadoop@outman00 hadoop]$ 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
- 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。