大数据集群运维（1）Hadoop + Hive + HBase + Kylin伪分布式安装[通俗易懂]

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软件要求
Hadoop：2.7+，3.1 +（自v2.5起）
Hive：0.13-1.2.1+
HBase：1.1+，2.0（自v2.5起）
Spark（可选）2.3.0+
Kafka（可选）1.0.0+（自v2.5起）
JDK：1.8+（自v2.5起）
操作系统：仅Linux，CentOS 6.5+或Ubuntu 16.0.4+
安装要求知道了，但是hadoop这些东西不太熟悉，小白一个，看了网上一些资料边看边学边做，期间遇到了很多坑！很多人写的安装文档以是步骤东一块西一块，在经历了很多坑之后终于是把完全分散的hadoop + mysql + hive + hbase + zookeeper + kylin部署成功了，但是对于日常自己学习测试来说，开多台虚拟机电脑实在撑不住，于是写了现在这个伪分布式的部署文档给像我一样初学kylin的小白同学们
环境配置：
目前有两个测试环境，以Centsos 7系统的安装为示例介绍详细过程，Centos7系统规划配置清单如下，另外一个测试环境为RedHat 6 64位系统，安装过程都差不多，Mysql安装有些不一样，不一样的地方都分别写了各自的安装方法，安装过程中
遇到的坑很多并且都已经解决，不再一一分解，按照以下步骤是完全可以在Centos 7 / Redhat 6 64位系统安装成功的。

大数据集群运维（1）Hadoop + Hive + HBase + Kylin伪分布式安装[通俗易懂]

一，Centos7安装
打开vmware，创建新虚拟机安装Centos 774位系统：

完成后界面如下：

选择启动虚拟机，选择第一个选项回车：

选择继续
等待依赖包检查完成，点击日期和时间设置时间
接下来点击软件选择选择安装模式，这里选择最精简安装：
然后点击done出来之后，等待依赖包检查完成，然后设置磁盘分区

选择现在设置：
点击完成后，进入下面的界面，选择标准分区，然后设置点击+号设置分区

最后分好区如下：
然后点击done后点击确认

最后done点击安装就可以了：
二，Linux环境配置：1，linux网络配置：（1）因为Centos 7安装可以在这个界面设置下root密码，等待安装完成就可以了。的精简模式，先解决linux网络问题来让windows能够使用xshell连上，编辑/ etc / sysconfig / network-scripts / ifcfg-ens33内容如下：

TYPE=Ethernet
PROXY_METHOD=none
BROWSER_ONLY=no
BOOTPROTO=none
DEFROUTE=yes
IPV4_FAILURE_FATAL=no
IPV6INIT=yes
IPV6_AUTOCONF=yes
IPV6_DEFROUTE=yes
IPV6_FAILURE_FATAL=no
IPV6_ADDR_GEN_MODE=stable-privacy
NAME=ens33
UUID=e8df3ff3-cf86-42cd-b48a-0d43fe85d8a6
DEVICE=ens33
ONBOOT="yes"
IPADDR=192.168.1.66
PREFIX=24
IPV6_PRIVACY=no

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（2）重启网络

IT知识分享网[root@hadoop ~]# service network restart
Restarting network (via systemctl):                        [  OK  ]
重启后可以通过下面命令来检查网络
[root@hadoop ~]# ip addr
1: lo: <LOOPBACK,UP,LOWER_UP> mtu 65536 qdisc noqueue state UNKNOWN group default qlen 1000
    link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00
    inet 127.0.0.1/8 scope host lo
       valid_lft forever preferred_lft forever
    inet6 ::1/128 scope host 
       valid_lft forever preferred_lft forever
2: ens33: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc pfifo_fast state UP group default qlen 1000
    link/ether 00:0c:29:0d:f1:ca brd ff:ff:ff:ff:ff:ff
    inet 192.168.1.66/24 brd 192.168.1.255 scope global noprefixroute ens33
       valid_lft forever preferred_lft forever
    inet6 fe80::d458:8497:adb:7f01/64 scope link noprefixroute 
       valid_lft forever preferred_lft forever

（3）接下来关闭防火墙

[root@hadoop ~]# systemctl disable firewalld
[root@hadoop ~]# systemctl stop firewalld```

（4）进程守护，关闭selinux

IT知识分享网[root@hadoop ~]# setenforce 0
[root@hadoop ~]# vi /etc/selinux/config
[root@hadoop ~]# cat  /etc/selinux/config
 
# This file controls the state of SELinux on the system.
# SELINUX= can take one of these three values:
#     enforcing - SELinux security policy is enforced.
#     permissive - SELinux prints warnings instead of enforcing.
#     disabled - No SELinux policy is loaded.
SELINUX=disabled
# SELINUXTYPE= can take one of three values:
#     targeted - Targeted processes are protected,
#     minimum - Modification of targeted policy. Only selected processes are protected. 
#     mls - Multi Level Security protection.
SELINUXTYPE=targeted 
重启
[root@hadoop ~]# reboot
可以通过下面方式查看是否启用selinux
sestatus
getenforce

（5）编辑/ etc / hosts加入以下内容

[root@hadoop ~]# cat /etc/hosts
127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4
::1 localhost localhost.localdomain localhost6 localhost6.localdomain6
192.168.1.66 hadoop

2，安装java
（1）先看下当前Linux环境是否有自带的open jdk：

[root@hadoop ~]# rpm -qa | grep java
[root@hadoop ~]# rpm -qa | grep jdk
[root@hadoop ~]# rpm -qa | grep gcj
没有，如果有的话要卸载，卸载案例如下：
卸载linux自带open jdk，将前面三条命令检查出来的内容一一卸载：
[root@master ~]# rpm -e --nodeps java-1.7.0-openjdk-1.7.0.99-2.6.5.1.0.1.el6.x86_64
[root@master ~]# rpm -e --nodeps tzdata-java-2016c-1.el6.noarch
[root@master ~]# rpm -e java-1.6.0-openjdk-1.6.0.38-1.13.10.4.el6.x86_64
[root@master ~]# rpm -e java-1.7.0-openjdk-1.7.0.99-2.6.5.1.0.1.el6.x86_64
卸载完成后应该再检查一次

（2）接下来安装配置java

创建安装目录：
[root@hadoop ~]# mkdir -p /usr/java
上传并解压jdk到此目录
[root@hadoop ~]# cd /usr/java/
[root@hadoop java]# ls
jdk-8u151-linux-x64 (1).tar.gz
解压缩
[root@hadoop java]# tar -zxvf jdk-8u151-linux-x64\ \(1\).tar.gz
[root@hadoop java]# rm -rf jdk-8u151-linux-x64\ \(1\).tar.gz 
[root@hadoop java]# ls
jdk1.8.0_151
编辑/etc/profile
写入下面jdk环境变量，保存退出
export JAVA_HOME=/usr/java/jdk1.8.0_151
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
export PATH=$PATH:$JAVA_HOME/bin
使环境变量生效
[root@master java]# source /etc/profile
检查安装是否没问题
[root@hadoop java]# java -version
java version "1.8.0_151"
Java(TM) SE Runtime Environment (build 1.8.0_151-b12)
Java HotSpot(TM) 64-Bit Server VM (build 25.151-b12, mixed mode)

3，配置SSH免密码登录
（1）输入命令，ssh-keygen -t rsa，生成密钥，都不输入密码，一直回车，/ root就会生成.ssh文件夹

[root@hadoop ~]# ssh-keygen -t rsa
Generating public/private rsa key pair.
Enter file in which to save the key (/root/.ssh/id_rsa): 
Enter passphrase (empty for no passphrase): 
Enter same passphrase again: 
Your identification has been saved in /root/.ssh/id_rsa.
Your public key has been saved in /root/.ssh/id_rsa.pub.
The key fingerprint is:
SHA256:+Xxqh8qa2AguQPY4aNJci6YiUWS822NtcLRK/9Kopp8 root@hadoop1
The key's randomart image is:
+---[RSA 2048]----+
| . |
| + . |
| o . . . |
| oo + o . |
|++o* B S |
|=+*.* + o |
|++o. o + o.. |
|=. ..=ooo oo. |
|o.o+E.+ooo.. |
+----[SHA256]-----+     
[root@hadoop ~]# cd .ssh/
[root@hadoop .ssh]# ls
id_rsa id_rsa.pub known_hosts
 
合并公钥到authorized_keys文件，在hadoop服务器，进入/root/.ssh目录，通过SSH命令合并
[root@hadoop .ssh]# cat id_rsa.pub>> authorized_keys
通过下面命令测试
ssh localhost
ssh hadoop
ssh 192.168.1.66

4，安装Hadoop2.7
（1）下载连接： http :
//archive.apache.org/dist/hadoop/core/hadoop-2.7.6/
<ignore_js_op>

（2）解压：

[root@hadoop ~]# cd /hadoop/
[root@hadoop hadoop]# ls
hadoop-2.7.6 (1).tar.gz
[root@hadoop hadoop]# tar -zxvf hadoop-2.7.6\ \(1\).tar.gz ^C
[root@hadoop hadoop]# ls
hadoop-2.7.6  hadoop-2.7.6 (1).tar.gz
[root@hadoop hadoop]# rm -rf *gz
[root@hadoop hadoop]# mv hadoop-2.7.6/* .

（3）在/ hadoop目录下创建数据存放的文件夹，tmp，hdfs，hdfs / data，hdfs / name

[root@hadoop hadoop]# pwd
/hadoop
[root@hadoop hadoop]# mkdir tmp
[root@hadoop hadoop]# mkdir hdfs
[root@hadoop hadoop]# mkdir hdfs/data
[root@hadoop hadoop]# mkdir hdfs/name

（4）配置/ hadoop / etc / hadoop目录下的core-site.xml

[root@hadoop hadoop]# vi etc/hadoop/core-site.xml 
<configuration>
  <property>
        <name>fs.defaultFS</name>
        <value>hdfs://192.168.1.66:9000</value>
    </property>
    <property>
        <name>hadoop.tmp.dir</name>
        <value>file:/hadoop/tmp</value>
    </property>
    <property>
        <name>io.file.buffer.size</name>
        <value>131702</value>
    </property>
 </configuration>

（5）配置/hadoop/etc/hadoop/hdfs-site.xml

[root@hadoop hadoop]# vi etc/hadoop/hdfs-site.xml
<configuration>
<property>
        <name>dfs.namenode.name.dir</name>
        <value>file:/hadoop/hdfs/name</value>
    </property>
    <property>
        <name>dfs.datanode.data.dir</name>
        <value>file:/hadoop/hdfs/data</value>
    </property>
    <property>
        <name>dfs.replication</name>
        <value>1</value>
    </property>
    <property>
        <name>dfs.namenode.secondary.http-address</name>
        <value>192.168.1.66:9001</value>
    </property>
    <property>
    <name>dfs.webhdfs.enabled</name>
    <value>true</value>
    </property>
 </configuration>

（6）复制etc / hadoop / mapred-site.xml.template为etc / hadoop / mapred-site.xml，再编辑：

[root@hadoop hadoop]# cd etc/hadoop/
[root@hadoop hadoop]# cp mapred-site.xml.template  mapred-site.xml
[root@hadoop hadoop]# vi mapred-site.xml
<configuration>
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
    <property>
        <name>mapreduce.jobhistory.address</name>
        <value>192.168.1.66:10020</value>
    </property>
    <property>
        <name>mapreduce.jobhistory.webapp.address</name>
        <value>192.168.1.66:19888</value>
    </property>
 
</configuration>

（7）配置etc / hadoop / yarn-site.xml

root@hadoop1 hadoop]# vi yarn-site.xml
<configuration>
 
 
<!-- Site specific YARN configuration properties -->
  <property>
    <name>yarn.nodemanager.aux-services</name>
    <value>mapreduce_shuffle</value>
    </property>
<property>
    <name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name>
    <value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
  <property>
    <name>yarn.resourcemanager.hostname</name>
    <value>hadoop</value>
  </property>
 
</configuration>

（8）配置/ hadoop / etc / hadoop /目录下hadoop-env.sh，yarn-env.sh的JAVA_HOME，不设置的话，启动不了

[root@hadoop hadoop]# pwd
/hadoop/etc/hadoop
[root@hadoop hadoop]# vi hadoop-env.sh 
将 export JAVA_HOME 改为：export JAVA_HOME=/usr/java/jdk1.8.0_151
加入
export HADOOP_CONF_DIR=${HADOOP_CONF_DIR:-"/etc/hadoop"}
export HADOOP_COMMON_LIB_NATIVE_DIR=${HADOOP_HOME}/lib/native
 
[root@hadoop hadoop]# vi yarn-env.sh 
将 export JAVA_HOME 改为：export JAVA_HOME=/usr/java/jdk1.8.0_151

配置slaves文件

[root@hadoop hadoop]# cat slaves 
localhost

（9）配置hadoop环境变量

[root@hadoop ~]# vim /etc/profile  
写入下面内容
export HADOOP_HOME=/hadoop/
export HADOOP_CONF_DIR=${HADOOP_HOME}/etc/hadoop
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib:$HADOOP_COMMON_LIB_NATIVE_DIR"
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
 
[root@hadoop ~]# source /etc/profile

（10）启动hadoop

[root@hadoop hadoop]# pwd
/hadoop
[root@hadoop hadoop]#  bin/hdfs namenode -format
.。。。。。。。。。。。。。。。。。。。。。
19/03/04 17:18:00 INFO namenode.FSImage: Allocated new BlockPoolId: BP-774693564-192.168.1.66-1551691079972
19/03/04 17:18:00 INFO common.Storage: Storage directory /hadoop/hdfs/name has been successfully formatted.
19/03/04 17:18:00 INFO namenode.FSImageFormatProtobuf: Saving image file /hadoop/hdfs/name/current/fsimage.ckpt_0000000000000000000 using no compression
19/03/04 17:18:00 INFO namenode.FSImageFormatProtobuf: Image file /hadoop/hdfs/name/current/fsimage.ckpt_0000000000000000000 of size 321 bytes saved in 0 seconds.
19/03/04 17:18:00 INFO namenode.NNStorageRetentionManager: Going to retain 1 images with txid >= 0
19/03/04 17:18:00 INFO util.ExitUtil: Exiting with status 0
19/03/04 17:18:00 INFO namenode.NameNode: SHUTDOWN_MSG: 
/************************************************************
SHUTDOWN_MSG: Shutting down NameNode at hadoop/192.168.1.66
************************************************************/
全部启动sbin/start-all.sh，也可以分开sbin/start-dfs.sh、sbin/start-yarn.sh
[root@hadoop hadoop]# sbin/start-dfs.sh
[root@hadoop hadoop]# sbin/start-yarn.sh
停止的话，输入命令，sbin/stop-all.sh
输入命令jps，可以看到相关信息:
[root@hadoop hadoop]# jps
10581 ResourceManager
10102 NameNode
10376 SecondaryNameNode
10201 DataNode
10683 NodeManager
11007 Jps

（11）启动工作历史

# kylin需要连接jobhistory
 mr-jobhistory-daemon.sh start historyserver
 [root@hadoop hadoop]# jps
33376 NameNode
33857 ResourceManager
33506 DataNode
33682 SecondaryNameNode
33960 NodeManager
34319 JobHistoryServer
34367 Jps

（12）验证
1）浏览器打开http://192.168.1.66:8088/
2）浏览器打开http://192.168.1.66:50070/
5，安装Mysql
需要根据自己的系统版本去下载，下载连接：
https://dev.mysql.com/downloads/mysql/5.7.html#downloads
我在这里下载的是适用我当前本人测试环境Centos 7 64位的系统，而另一个测试环境10.1.197.241是Redhat 6，两一个测试环境如果安装时要下载对应的系统的rpm包，不然不兼容的rpm包安装时会报下面的错误（例如在Redhat6安装适用centos7的mysql）：

[root@s197240 hadoop]# rpm -ivh mysql-community-libs-5.7.18-1.el7.x86_64.rpm
warning: mysql-community-libs-5.7.18-1.el7.x86_64.rpm: Header V3 DSA/SHA1 Signature, key ID 5072e1f5: NOKEY
error: Failed dependencies:
libc.so.6(GLIBC_2.14)(64bit) is needed by mysql-community-libs-5.7.18-1.el7.x86_64

1）检查卸载mariadb-lib
Centos自带mariadb数据库，删除，安装mysql

[root@hadoop hadoop]# rpm -qa|grep mariadb
mariadb-libs-5.5.60-1.el7_5.x86_64
[root@hadoop hadoop]# rpm -e mariadb-libs-5.5.60-1.el7_5.x86_64 --nodeps
[root@hadoop hadoop]# rpm -qa|grep mariadb

如果时Redhat6安装时自带mysql库，卸载自带的包：
通过此命令查找已经安装的mysql包：

[root@s197240 hadoop]# rpm -qa |grep mysql
mysql-community-common-5.7.18-1.el7.x86_64
通过此命令卸载：
[root@s197240 hadoop]# rpm -e --allmatches --nodeps mysql-community-common-5.7.18-1.el7.x86_64

2）上传解压安装包
下载连接：https : //dev.mysql.com/downloads/file/?id=469456

[root@hadoop mysql]# pwd
/usr/local/mysql
[root@hadoop mysql]# ls
mysql-5.7.18-1.el7.x86_64.rpm-bundle.tar
[root@hadoop mysql]# tar -xvf  mysql-5.7.18-1.el7.x86_64.rpm-bundle.tar 
mysql-community-server-5.7.18-1.el7.x86_64.rpm
mysql-community-embedded-devel-5.7.18-1.el7.x86_64.rpm
mysql-community-devel-5.7.18-1.el7.x86_64.rpm
mysql-community-client-5.7.18-1.el7.x86_64.rpm
mysql-community-common-5.7.18-1.el7.x86_64.rpm
mysql-community-embedded-5.7.18-1.el7.x86_64.rpm
mysql-community-embedded-compat-5.7.18-1.el7.x86_64.rpm
mysql-community-libs-5.7.18-1.el7.x86_64.rpm
mysql-community-server-minimal-5.7.18-1.el7.x86_64.rpm
mysql-community-test-5.7.18-1.el7.x86_64.rpm
mysql-community-minimal-debuginfo-5.7.18-1.el7.x86_64.rpm
mysql-community-libs-compat-5.7.18-1.el7.x86_64.rpm

（3）安装mysql服务器，
其中安装mysql-server，需要以下几个必要的安装包：

mysql-community-client-5.7.17-1.el7.x86_64.rpm（依赖于libs）
mysql-community-common-5.7.17-1.el7.x86_64.rpm （依赖于common）
mysql-community-libs-5.7.17-1.el7.x86_64.rpm
mysql-community-server-5.7.17-1.el7.x86_64.rpm（依赖于common, client）

安装上面四个包需要libaio和net-tools的依赖项，此处配置好yum源，使用yum安装，通过以下命令安装：

yum -y install libaio
yum -y install net-tools

安装mysql-server：按照常用–> libs-> client-> server的顺序。若不按照此顺序，也会有一定的“依赖”关系的提醒。

[root@hadoop mysql]# rpm -ivh mysql-community-common-5.7.18-1.el7.x86_64.rpm 
warning: mysql-community-common-5.7.18-1.el7.x86_64.rpm: Header V3 DSA/SHA1 Signature, key ID 5072e1f5: NOKEY
Preparing...                          ################################# [100%]
Updating / installing...
   1:mysql-community-common-5.7.18-1.e################################# [100%]
[root@hadoop mysql]# rpm -ivh  mysql-community-libs-5.7.18-1.el7.x86_64.rpm 
warning: mysql-community-libs-5.7.18-1.el7.x86_64.rpm: Header V3 DSA/SHA1 Signature, key ID 5072e1f5: NOKEY
Preparing...                          ################################# [100%]
Updating / installing...
   1:mysql-community-libs-5.7.18-1.el7################################# [100%]
[root@hadoop mysql]# rpm -ivh mysql-community-client-5.7.18-1.el7.x86_64.rpm 
warning: mysql-community-client-5.7.18-1.el7.x86_64.rpm: Header V3 DSA/SHA1 Signature, key ID 5072e1f5: NOKEY
Preparing...                          ################################# [100%]
Updating / installing...
   1:mysql-community-client-5.7.18-1.e################################# [100%]
[root@hadoop mysql]# rpm -ivh mysql-community-server-5.7.18-1.el7.x86_64.rpm 
warning: mysql-community-server-5.7.18-1.el7.x86_64.rpm: Header V3 DSA/SHA1 Signature, key ID 5072e1f5: NOKEY
Preparing...                          ################################# [100%]
Updating / installing...
   1:mysql-community-server-5.7.18-1.e################################# [100%]

（4）初始化mysql

[root@hadoop mysql]#  mysqld --initialize

MySQL的默认安装在的/ var / lib中下。
（5）更改的MySQL数据库所属于用户及其所属于组

[root@hadoop mysql]# chown mysql:mysql /var/lib/mysql -R

（6）启动mysql数据库

启动mysql数据库
[root@hadoop mysql]# cd /var/lib/mysql
[root@hadoop mysql]# systemctl start mysqld.service
[root@hadoop ~]# cd /var/log/
[root@hadoop log]# grep 'password' mysqld.log 
2019-02-26T04:33:06.989818Z 1 [Note] A temporary password is generated for root@localhost: mxeV&htW-3VC
更改root用户密码，新版的mysql在第一次登录后更改密码前是不能执行任何命令的
[root@hadoop log]# mysql -u root -p
Enter password: 
Welcome to the MySQL monitor.  Commands end with ; or \g.
Your MySQL connection id is 4
Server version: 5.7.18
 
Copyright (c) 2000, 2017, Oracle and/or its affiliates. All rights reserved.
 
Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.
 
Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.
更改密码
mysql> set password=password('oracle');
Query OK, 0 rows affected, 1 warning (0.00 sec)
 
mysql> flush privileges;
Query OK, 0 rows affected (0.00 sec)
mysql> grant all privileges on *.* to root@'%' identified by 'oracle' with grant option;
Query OK, 0 rows affected, 1 warning (0.00 sec)
 
mysql> flush privileges;
Query OK, 0 rows affected (0.00 sec)

如果是Redhat6系统，启动mysql数据库过程如下：

[root@s197240 mysql]# /etc/rc.d/init.d/mysqld start
Starting mysqld:                                           [  OK  ]
[root@s197240 mysql]# ls /etc/rc.d/init.d/mysqld -l
-rwxr-xr-x 1 root root 7157 Dec 21 19:29 /etc/rc.d/init.d/mysqld
[root@s197240 mysql]# chkconfig mysqld on
[root@s197240 mysql]# chmod 755 /etc/rc.d/init.d/mysqld
[root@s197240 mysql]# service mysqld start
Starting mysqld:                                           [  OK  ]
[root@s197240 mysql]# service mysqld status
mysqld (pid  28861) is running...

mysql启动后，剩余后面的操作完全按照上面systemctl start mysqld.service步骤下面的过程来就可以了
6，Hive安装
下载连接：
http : //archive.apache.org/dist/hive/hive-2.3.2 /
（1）上载和解压缩

[root@hadoop ~]# mkdir /hadoop/hive
[root@hadoop ~]# cd /hadoop/hive/
[root@hadoop hive]# ls
apache-hive-2.3.3-bin.tar.gz
[root@hadoop hive]# tar -zxvf apache-hive-2.3.3-bin.tar.gz

（2）配置环境变量

#编辑/etc/profile，添加hive相关的环境变量配置
[root@hadoop hive]# vim /etc/profile
export JAVA_HOME=/usr/java/jdk1.8.0_151
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
export PATH=$PATH:$JAVA_HOME/bin
export HADOOP_HOME=/hadoop/
export HADOOP_CONF_DIR=${HADOOP_HOME}/etc/hadoop
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib:$HADOOP_COMMON_LIB_NATIVE_DIR"
export HIVE_HOME=/hadoop/hive/
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$HIVE_HOME/bin
#修改完文件后，执行如下命令，让配置生效：
[root@hadoop hive]# source /etc/profile

（3）Hive配置Hadoop HDFS
hive-site.xml配置
进入目录$ HIVE_HOME / conf，将hive-default.xml.template文件复制一份并改名为hive-site.xml

[root@hadoop hive]# cd $HIVE_HOME/conf 
[root@hadoop conf]# cp hive-default.xml.template hive-site.xml

使用hadoop新建hdfs目录，因为在hive-site.xml中有如下配置：

<property>
    <name>hive.metastore.warehouse.dir</name>
    <value>/user/hive/warehouse</value>
    <description>location of default database for the warehouse</description>
  </property>
  <property>

执行hadoop命令新建/用户/配置单元/仓库目录：

#新建目录/user/hive/warehouse
[root@hadoop1 ~]# $HADOOP_HOME/bin/hadoop dfs -mkdir -p /user/hive/warehouse
DEPRECATED: Use of this script to execute hdfs command is deprecated.
Instead use the hdfs command for it.
#给新建的目录赋予读写权限
[root@hadoop1 ~]# cd $HIVE_HOME
[root@hadoop1 hive]# cd conf/
[root@hadoop1 conf]# sh $HADOOP_HOME/bin/hdfs dfs -chmod 777 /user/hive/warehouse
#查看修改后的权限
[root@hadoop1 conf]# sh $HADOOP_HOME/bin/hdfs dfs -ls /user/hive
Found 1 items
drwxrwxrwx   - root supergroup          0 2019-02-26 14:15 /user/hive/warehouse
 
#运用hadoop命令新建/tmp/hive目录
[root@hadoop1 conf]# $HADOOP_HOME/bin/hdfs dfs -mkdir -p /tmp/hive
#给目录/tmp/hive赋予读写权限
[root@hadoop1 conf]# $HADOOP_HOME/bin/hdfs dfs -chmod 777 /tmp/hive
#检查创建好的目录
[root@hadoop1 conf]# $HADOOP_HOME/bin/hdfs dfs -ls /tmp
Found 1 items
drwxrwxrwx   - root supergroup          0 2019-02-26 14:17 /tmp/hive

修改HIVEHOME / conf / hive＆＃8722; site.xml中的临时目录将hive＆＃8722; site.xml文件中的HIVE_HOME / conf / hive-site.xml中的临时目录将为hive-site.xml文件中的HIVE
H
＆＃8203;
OME / conf / hive＆＃8722; site.xml中的临时目录将hive＆＃8722; site.xml文件中的{system：java.io.tmpdir}替换为hive的临时目录，例如我替换为$ HIVE_HOME / tmp ，该目录如果不存在则要自己手工创建，并具有识别权限。

[root@hadoop1 conf]# cd $HIVE_HOME
[root@hadoop1 hive]# mkdir tmp

配置文件hive-site.xml：
将文件中的所有系统：java.io.tmpdir替换成/ hadoop / hive / tmp将文件中所有的{system：java.io.tmpdir}替换成/ hadoop / hive / tmp将文件中所有的系统：java.io.tmpdir替换成/ hadoop / hive / tmp将文件中所有的{system：user.name}替换为root
（4）配置mysql
把MySQL的驱动包上传到Hive的lib目录下：

[root@hadoop lib]# pwd
/usr/local/hive/lib
[root@hadoop1 lib]# ls |grep mysql
mysql-connector-java-5.1.47.jar

（5）修改hive-site.xml数据库相关配置
搜索javax.jdo.option.connectionURL，将名称对应的值修改为MySQL的地址：

<property>
    <name>javax.jdo.option.ConnectionURL</name>
    <value>jdbc:mysql://localhost:3306/metastore?createDatabaseIfNotExist=true&characterEncoding=UTF-8&useSSL=false</value>
    <description>
      JDBC connect string for a JDBC metastore.
      To use SSL to encrypt/authenticate the connection, provide database-specific SSL flag in the connection URL.
      For example, jdbc:postgresql://myhost/db?ssl=true for postgres database.
    </description>
  </property>

搜索javax.jdo.option.ConnectionDriverName，将名称对应的值修改为MySQL驱动类路径：

<property>
    <name>javax.jdo.option.ConnectionDriverName</name>
    <value>com.mysql.jdbc.Driver</value>
    <description>Driver class name for a JDBC metastore</description>
  </property>

搜索javax.jdo.option.ConnectionUserName，将对应的值修改为MySQL数据库登录名：

<property>
    <name>javax.jdo.option.ConnectionUserName</name>
    <value>root</value>
    <description>Username to use against metastore database</description>
  </property>

搜索javax.jdo.option.ConnectionPassword，将对应的值修改为MySQL数据库的登录密码：

<property>
    <name>javax.jdo.option.ConnectionPassword</name>
    <value>oracle</value>
    <description>password to use against metastore database</description>
  </property>

搜索hive.metastore.schema.verification，将对应的值修改为false：

<property>
    <name>hive.metastore.schema.verification</name>
    <value>false</value>

在$ HIVE_HOME / conf目录下新建hive-env.sh

进入目录
[root@hadoop1 conf]# cd $HIVE_HOME/conf
[root@hadoop1 conf]# cp hive-env.sh.template hive-env.sh
#打开hive-env.sh并添加如下内容
[root@hadoop1 conf]# vim hive-env.sh
export HADOOP_HOME=/hadoop/
export HIVE_CONF_DIR=/hadoop/hive/conf
export HIVE_AUX_JARS_PATH=/hadoop/hive/lib

（6）MySQL数据库进行初始化

#进入$HIVE/bin
[root@apollo conf]# cd $HIVE_HOME/bin
#对数据库进行初始化：
[root@hadoop1 bin]# schematool -initSchema -dbType mysql
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/hadoop/hive/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/imp
l/StaticLoggerBinder.class]SLF4J: Found binding in [jar:file:/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/
org/slf4j/impl/StaticLoggerBinder.class]SLF4J: See [url=http://www.slf4j.org/codes.html#multiple_bindings]http://www.slf4j.org/codes.html#multiple_bindings[/url] for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Metastore connection URL:         jdbc:mysql://localhost:3306/metastore?createDatabaseIfNotEx
ist=true&characterEncoding=UTF-8&useSSL=falseMetastore Connection Driver :         com.mysql.jdbc.Driver
Metastore connection User:         root
Starting metastore schema initialization to 2.3.0
Initialization script hive-schema-2.3.0.mysql.sql
Initialization script completed
schemaTool completed
 
出现上面就是初始化成功，去mysql看下：
mysql> show databases;
+--------------------+
| Database           |
+--------------------+
| information_schema |
| metastore          |
| mysql              |
| performance_schema |
| sys                |
+--------------------+
5 rows in set (0.00 sec)
 
mysql> use metastore
Reading table information for completion of table and column names
You can turn off this feature to get a quicker startup with -A
 
Database changed
mysql> show tables;
+---------------------------+
| Tables_in_metastore       |
+---------------------------+
| AUX_TABLE                 |
| BUCKETING_COLS            |
| CDS                       |
| COLUMNS_V2                |
| COMPACTION_QUEUE          |
| COMPLETED_COMPACTIONS     |
| COMPLETED_TXN_COMPONENTS  |
| DATABASE_PARAMS           |
| DBS                       |
| DB_PRIVS                  |
| DELEGATION_TOKENS         |
| FUNCS                     |
| FUNC_RU                   |
| GLOBAL_PRIVS              |
| HIVE_LOCKS                |
| IDXS                      |
| INDEX_PARAMS              |
| KEY_CONSTRAINTS           |
| MASTER_KEYS               |
| NEXT_COMPACTION_QUEUE_ID  |
| NEXT_LOCK_ID              |
| NEXT_TXN_ID               |
| NOTIFICATION_LOG          |
| NOTIFICATION_SEQUENCE     |
| NUCLEUS_TABLES            |
| PARTITIONS                |
| PARTITION_EVENTS          |
| PARTITION_KEYS            |
| PARTITION_KEY_VALS        |
| PARTITION_PARAMS          |
| PART_COL_PRIVS            |
| PART_COL_STATS            |
| PART_PRIVS                |
| ROLES                     |
| ROLE_MAP                  |
| SDS                       |
| SD_PARAMS                 |
| SEQUENCE_TABLE            |
| SERDES                    |
| SERDE_PARAMS              |
| SKEWED_COL_NAMES          |
| SKEWED_COL_VALUE_LOC_MAP  |
| SKEWED_STRING_LIST        |
| SKEWED_STRING_LIST_VALUES |
| SKEWED_VALUES             |
| SORT_COLS                 |
| TABLE_PARAMS              |
| TAB_COL_STATS             |
| TBLS                      |
| TBL_COL_PRIVS             |
| TBL_PRIVS                 |
| TXNS                      |
| TXN_COMPONENTS            |
| TYPES                     |
| TYPE_FIELDS               |
| VERSION                   |
| WRITE_SET                 |
+---------------------------+
57 rows in set (0.01 sec)

（7）启动配置单元：

启动metastore服务
nohup hive --service metastore >> ~/metastore.log 2>&1 &         ##hivemetastore
 启动hive服务
nohup  hive --service hiveserver2 >> ~/hiveserver2.log 2>&1 &    ##hiveserver2，jdbc连接均需要
[root@hadoop bin]# netstat  -lnp|grep 9083
tcp        0      0 0.0.0.0:9083            0.0.0.0:*               LISTEN      11918/java 
[root@hadoop bin]# netstat  -lnp|grep 10000
tcp        0      0 0.0.0.0:10000           0.0.0.0:*               LISTEN      12011/java  
[root@hadoop1 bin]# ./hive
which: no hbase in (/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/usr/java/jdk1.8.0_151
/bin:/usr/java/jdk1.8.0_151/bin:/hadoop//bin:/hadoop//sbin:/root/bin:/usr/java/jdk1.8.0_151/bin:/usr/java/jdk1.8.0_151/bin:/hadoop//bin:/hadoop//sbin:/hadoop/hive/bin)SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/hadoop/hive/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/imp
l/StaticLoggerBinder.class]SLF4J: Found binding in [jar:file:/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/
org/slf4j/impl/StaticLoggerBinder.class]SLF4J: See [url=http://www.slf4j.org/codes.html#multiple_bindings]http://www.slf4j.org/codes.html#multiple_bindings[/url] for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
 
Logging initialized using configuration in jar:file:/hadoop/hive/lib/hive-common-2.3.3.jar!/
hive-log4j2.properties Async: trueHive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider
 using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
hive> show functions;
OK
!
!=
$sum0
%
。。。。。
hive> desc function sum;
OK
sum(x) - Returns the sum of a set of numbers
Time taken: 0.183 seconds, Fetched: 1 row(s)
hive> create database sbux;
OK
Time taken: 0.236 seconds
hive> use sbux;
OK
Time taken: 0.033 seconds
hive> create table student(id int, name string) row format delimited fields terminated by '\t';
OK
Time taken: 0.909 seconds
hive> desc student;
OK
id                          int                                            
name                        string                                          
Time taken: 0.121 seconds, Fetched: 2 row(s)
 在$HIVE_HOME下新建一个文件
 #进入#HIVE_HOME目录
[root@apollo hive]# cd $HIVE_HOME
#新建文件student.dat
[root@apollo hive]# touch student.dat
#在文件中添加如下内容
[root@apollo hive]# vim student.dat
001        david
002        fab
003        kaishen
004        josen
005        arvin
006        wada
007        weda
008        banana
009        arnold
010        simon
011        scott
.导入数据
hive> load data local inpath '/hadoop/hive/student.dat' into table sbux.student;
Loading data to table sbux.student
OK
Time taken: 8.641 seconds
hive> use sbux;
OK
Time taken: 0.052 seconds
hive> select * from student;
OK
1        david
2        fab
3        kaishen
4        josen
5        arvin
6        wada
7        weda
8        banana
9        arnold
10        simon
11        scott
NULL        NULL
Time taken: 2.217 seconds, Fetched: 12 row(s)

（8）在界面上查看刚刚写入的hdfs数据
在hadoop的namenode上查看：
<ignore_js_op>

在mysql的hive数据里查看

[root@hadoop1 bin]# mysql -u root -p
Enter password: 
mysql> show databases;
+--------------------+
| Database |
+--------------------+
| information_schema |
| metastore |
| mysql |
| performance_schema |
| sys |
+--------------------+
5 rows in set (0.00 sec)
mysql> use metastore;
Database changed
mysql> select * from TBLS;
+--------+-------------+-------+------------------+-------+-----------+-------+----------+---------------+--------------------+--------------------+--------------------+
| TBL_ID | CREATE_TIME | DB_ID | LAST_ACCESS_TIME | OWNER | RETENTION | SD_ID | TBL_NAME | TBL_TYPE | VIEW_EXPANDED_TEXT | VIEW_ORIGINAL_TEXT | IS_REWRITE_ENABLED |
+--------+-------------+-------+------------------+-------+-----------+-------+----------+---------------+--------------------+--------------------+--------------------+
| 1 | 1551178545 | 6 | 0 | root | 0 | 1 | student | MANAGED_TABLE | NULL | NULL | |
+--------+-------------+-------+------------------+-------+-----------+-------+----------+---------------+--------------------+--------------------+--------------------+
1 row in set (0.00 sec)

7，Zookeeper安装
上传解压：

[root@hadoop ~]# cd /hadoop/
[root@hadoop hadoop]# pwd
/hadoop
[root@hadoop hadoop]# mkdir zookeeper
[root@hadoop hadoop]# cd zookeeper/
[root@hadoop zookeeper]# tar -zxvf zookeeper-3.4.6.tar.gz 
。。
[root@hadoop zookeeper]# ls
zookeeper-3.4.6 zookeeper-3.4.6.tar.gz
[root@hadoop zookeeper]# rm -rf *gz
[root@hadoop zookeeper]# mv zookeeper-3.4.6/* .
[root@hadoop zookeeper]# ls
bin CHANGES.txt contrib docs ivy.xml LICENSE.txt README_packaging.txt recipes zookeeper-3.4.6 zookeeper-3.4.6.jar.asc zookeeper-3.4.6.jar.sha1
build.xml conf dist-maven ivysettings.xml lib NOTICE.txt README.txt src zookeeper-3.4.6.jar zookeeper-3.4.6.jar.md5

配置配置文件

创建快照日志存放目录：
mkdir -p /hadoop/zookeeper/dataDir
创建事务日志存放目录：
mkdir -p /hadoop/zookeeper/dataLogDir
【注意】:如果不配置dataLogDir，那么事务日志也会写在dataDir目录中。这样会严重影响zk的性能。因为在zk吞吐量很高的时候，产生的事务日志和快照日志太多。
[root@hadoop zookeeper]# cd conf/
[root@hadoop conf]# mv zoo_sample.cfg zoo.cfg
[root@hadoop conf]# cat /hadoop/zookeeper/conf/zoo.cfg |grep -v ^#|grep -v ^$
tickTime=2000
initLimit=10
syncLimit=5
dataDir=/hadoop/zookeeper/dataDir
dataLogDir=/hadoop/zookeeper/dataLogDir
clientPort=2181
server.1=192.168.1.66:2887:3887

在我们配置的dataDir指定的目录下面，创建一个myid文件，里面内容为一个数字，用作标识当前主机，conf / zoo.cfg文件中配置的服务器。X中X为什么数字，则myid文件中就输入这个数字：

[root@hadoop conf]# echo "1" > /hadoop/zookeeper/dataDir/myid

启动zookeeper：

[root@hadoop zookeeper]# cd bin/
[root@hadoop bin]# ./zkServer.sh start
JMX enabled by default
Using config: /hadoop/zookeeper/bin/../conf/zoo.cfg
Starting zookeeper ... STARTED
[root@hadoop bin]# ./zkServer.sh status
JMX enabled by default
Using config: /hadoop/zookeeper/bin/../conf/zoo.cfg
Mode: standalone
[root@hadoop bin]# ./zkCli.sh -server localhost:2181
Connecting to localhost:2181
2019-03-12 11:47:29,355 [myid:] - INFO  [main:Environment@100] - Client environment:zookeeper.version=3.4.6-1569965, built on 02/20/2014 09:09 GMT
2019-03-12 11:47:29,360 [myid:] - INFO  [main:Environment@100] - Client environment:host.name=hadoop
2019-03-12 11:47:29,361 [myid:] - INFO  [main:Environment@100] - Client environment:java.version=1.8.0_151
2019-03-12 11:47:29,364 [myid:] - INFO  [main:Environment@100] - Client environment:java.vendor=Oracle Corporation
2019-03-12 11:47:29,364 [myid:] - INFO  [main:Environment@100] - Client environment:java.home=/usr/java/jdk1.8.0_151/jre
2019-03-12 11:47:29,364 [myid:] - INFO  [main:Environment@100] - Client environment:java.class.path=/hadoop/zookeeper/bin/../build/classes:/hadoop/zookeeper/bin/../build/lib/*.jar:/hadoop/z
ookeeper/bin/../lib/slf4j-log4j12-1.6.1.jar:/hadoop/zookeeper/bin/../lib/slf4j-api-1.6.1.jar:/hadoop/zookeeper/bin/../lib/netty-3.7.0.Final.jar:/hadoop/zookeeper/bin/../lib/log4j-1.2.16.jar:/hadoop/zookeeper/bin/../lib/jline-0.9.94.jar:/hadoop/zookeeper/bin/../zookeeper-3.4.6.jar:/hadoop/zookeeper/bin/../src/java/lib/*.jar:/hadoop/zookeeper/bin/../conf:.:/usr/java/jdk1.8.0_151/lib/dt.jar:/usr/java/jdk1.8.0_151/lib/tools.jar2019-03-12 11:47:29,364 [myid:] - INFO  [main:Environment@100] - Client environment:java.library.path=/usr/java/packages/lib/amd64:/usr/lib64:/lib64:/lib:/usr/lib
2019-03-12 11:47:29,364 [myid:] - INFO  [main:Environment@100] - Client environment:java.io.tmpdir=/tmp
2019-03-12 11:47:29,364 [myid:] - INFO  [main:Environment@100] - Client environment:java.compiler=<NA>
2019-03-12 11:47:29,364 [myid:] - INFO  [main:Environment@100] - Client environment:os.name=Linux
2019-03-12 11:47:29,364 [myid:] - INFO  [main:Environment@100] - Client environment:os.arch=amd64
2019-03-12 11:47:29,364 [myid:] - INFO  [main:Environment@100] - Client environment:os.version=3.10.0-957.el7.x86_64
2019-03-12 11:47:29,365 [myid:] - INFO  [main:Environment@100] - Client environment:user.name=root
2019-03-12 11:47:29,365 [myid:] - INFO  [main:Environment@100] - Client environment:user.home=/root
2019-03-12 11:47:29,365 [myid:] - INFO  [main:Environment@100] - Client environment:user.dir=/hadoop/zookeeper/bin
2019-03-12 11:47:29,366 [myid:] - INFO  [main:ZooKeeper@438] - Initiating client connection, connectString=localhost:2181 sessionTimeout=30000 watcher=org.apache.zookeeper.ZooKeeperMain$MyW
atcher@799f7e29Welcome to ZooKeeper!
2019-03-12 11:47:29,402 [myid:] - INFO  [main-SendThread(localhost:2181):ClientCnxn$SendThread@975] - Opening socket connection to server localhost/127.0.0.1:2181. Will not attempt to authe
nticate using SASL (unknown error)JLine support is enabled
2019-03-12 11:47:29,494 [myid:] - INFO  [main-SendThread(localhost:2181):ClientCnxn$SendThread@852] - Socket connection established to localhost/127.0.0.1:2181, initiating session
2019-03-12 11:47:29,519 [myid:] - INFO  [main-SendThread(localhost:2181):ClientCnxn$SendThread@1235] - Session establishment complete on server localhost/127.0.0.1:2181, sessionid = 0x1696f
feb12f0000, negotiated timeout = 30000
WATCHER::
 
WatchedEvent state:SyncConnected type:None path:null
[zk: localhost:2181(CONNECTED) 0] 
 
[root@hadoop bin]# jps
12467 QuorumPeerMain
11060 JobHistoryServer
10581 ResourceManager
12085 RunJar
10102 NameNode
12534 Jps
10376 SecondaryNameNode
10201 DataNode
11994 RunJar
10683 NodeManager

发现zookeeper正常起来了
8，Kafka安装
上传解压：

[root@hadoop bin]# cd /hadoop/
[root@hadoop hadoop]# mkdir kafka
[root@hadoop hadoop]# cd kafka/
[root@hadoop kafka]# ls
kafka_2.11-1.1.1.tgz
[root@hadoop kafka]# tar zxf kafka_2.11-1.1.1.tgz 
[root@hadoop kafka]# mv kafka_2.11-1.1.1/* .
[root@hadoop kafka]# ls
bin  config  kafka_2.11-1.1.1  kafka_2.11-1.1.1.tgz  libs  LICENSE  NOTICE  site-docs
[root@hadoop kafka]# rm -rf *tgz
[root@hadoop kafka]# ls
bin  config  kafka_2.11-1.1.1  libs  LICENSE  NOTICE  site-docs

修改配置文件：

[root@hadoop kafka]# cd config/
[root@hadoop config]# ls
connect-console-sink.properties    connect-file-sink.properties    connect-standalone.properties  producer.properties     zookeeper.properties
connect-console-source.properties  connect-file-source.properties  consumer.properties            server.properties
connect-distributed.properties     connect-log4j.properties        log4j.properties               tools-log4j.properties
[root@hadoop config]# vim server.properties 
配置如下：
[root@hadoop config]#  cat server.properties |grep -v ^#|grep -v ^$
broker.id=0
listeners=PLAINTEXT://192.168.1.66:9092
num.network.threads=3
num.io.threads=8
socket.send.buffer.bytes=102400
socket.receive.buffer.bytes=102400
socket.request.max.bytes=104857600
log.dirs=/hadoop/kafka/logs
num.partitions=1
num.recovery.threads.per.data.dir=1
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1
log.retention.hours=168
log.segment.bytes=1073741824
log.retention.check.interval.ms=300000
zookeeper.connect=192.168.1.66:2181
zookeeper.connection.timeout.ms=6000
group.initial.rebalance.delay.ms=0
delete.topic.enble=true -----如果不指定这个参数，执行删除操作只是标记删除

启动kafka

[root@hadoop kafka]# nohup bin/kafka-server-start.sh config/server.properties&
查看nohup文件有没有错误信息，没错就没问题。

验证kafka，为了日后操作方便，先来编辑几个常用脚本：

--消费者消费指定topic数据
[root@hadoop kafka]# cat console.sh 
#!/bin/bash
read -p "input topic:" name
 
bin/kafka-console-consumer.sh --zookeeper 192.168.1.66:2181 --topic $name --from-beginning
--列出当前所有topic
[root@hadoop kafka]# cat list.sh 
#!/bin/bash
bin/kafka-topics.sh -describe -zookeeper 192.168.1.66:2181
--生产者指定topic生产数据
[root@hadoop kafka]# cat productcmd.sh 
#!/bin/bash
read -p "input topic:" name
 
bin/kafka-console-producer.sh --broker-list 192.168.1.66:9092 --topic $name
--启动kafka
[root@hadoop kafka]# cat startkafka.sh 
#!/bin/bash
nohup bin/kafka-server-start.sh  config/server.properties&
关闭kafka
[root@hadoop kafka]# cat stopkafka.sh 
#!/bin/bash
bin/kafka-server-stop.sh
sleep 6
jps
--创建topic
[root@hadoop kafka]# cat create.sh 
read -p "input topic:" name
bin/kafka-topics.sh --create --zookeeper 192.168.1.66:2181 --replication-factor 1 --partitions 1 --topic $name

接下来验证kafka可用：

会话1创建topic
[root@hadoop kafka]# ./create.sh 
input topic:test
Created topic "test".
查看创建的topic
[root@hadoop kafka]# ./list.sh 
Topic:test        PartitionCount:1        ReplicationFactor:1        Configs:
        Topic: test        Partition: 0        Leader: 0        Replicas: 0        Isr: 0
会话1指定test生产数据：
[root@hadoop kafka]# ./productcmd.sh 
input topic:test
>test  
>
会话2指定test消费数据：
[root@hadoop kafka]# ./console.sh 
input topic:test
Using the ConsoleConsumer with old consumer is deprecated and will be removed in a future major release. Consider using the new consumer by passing [bootstrap-server] instead of [zookeeper]
.test
测试可以正常生产和消费。

将kafka和zookeeper相关环境变量加到/ etc / profile，并进行源代码合并。

export ZOOKEEPER_HOME=/hadoop/zookeeper
export KAFKA_HOME=/hadoop/kafka

9，Hbase安装
下载连接：
http : //archive.apache.org/dist/hbase/
（1）创建安装目录并上传解压：

[root@hadoop hbase]# tar -zxvf hbase-1.4.9-bin.tar.gz 
[root@hadoop hbase]# ls
hbase-1.4.9  hbase-1.4.9-bin.tar.gz
[root@hadoop hbase]# rm -rf *gz
mv [root@hadoop hbase]# mv hbase-1.4.9/* .
 
[root@hadoop hbase]# pwd
/hadoop/hbase
[root@hadoop hbase]# ls
bin          conf  hbase-1.4.9    LEGAL  LICENSE.txt  README.txt
CHANGES.txt  docs  hbase-webapps  lib    NOTICE.txt

（2）环境变量配置，我的环境变量如下：

export JAVA_HOME=/usr/java/jdk1.8.0_151
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
export PATH=$PATH:$JAVA_HOME/bin
export HADOOP_HOME=/hadoop/
export HADOOP_CONF_DIR=${HADOOP_HOME}/etc/hadoop
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib:$HADOOP_COMMON_LIB_NATIVE_DIR"
export HIVE_HOME=/hadoop/hive
export HIVE_CONF_DIR=${HIVE_HOME}/conf
export HCAT_HOME=$HIVE_HOME/hcatalog
export HIVE_DEPENDENCY=/hadoop/hive/conf:/hadoop/hive/lib/*:/hadoop/hive/hcatalog/share/hcatalog/hive-hcatalog-pig-adapter-2.3.3.jar:/hadoop/hive/hcatalog/share/hcatalog/hive-hcatalog-core-2.3.3.jar:/hadoop/hive/hcatalog/share/hcatalog/hive-hcatalog-server-extensions-2.3.3.jar:/hadoop/hive/hcatalog/share/hcatalog/hive-hcatalog-streaming-2.3.3.jar:/hadoop/hive/lib/hive-exec-2.3.3.jar
export HBASE_HOME=/hadoop/hbase/
export ZOOKEEPER_HOME=/hadoop/zookeeper
export KAFKA_HOME=/hadoop/kafka
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$HIVE_HOME/bin:$HCAT_HOME/bin:$HBASE_HOME/bin:$ZOOKEEPER_HOME:$KAFKA_HOME
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar:${HIVE_HOME}/lib:$HBASE_HOME/lib

详细配置

修改conf/hbase-env.sh中的HBASE_MANAGES_ZK为false：
[root@hadoop kafka]# cd /hadoop/hbase/
[root@hadoop hbase]# ls
bin          conf  hbase-1.4.9    LEGAL  LICENSE.txt  README.txt
CHANGES.txt  docs  hbase-webapps  lib    NOTICE.txt
修改hbase-env.sh文件加入下面内容
[root@hadoop hbase]# vim conf/hbase-env.sh
export JAVA_HOME=/usr/java/jdk1.8.0_151
export HADOOP_HOME=/hadoop/
export HBASE_HOME=/hadoop/hbase/
export HBASE_MANAGES_ZK=false
修改配置文件hbase-site.xml
在该配置文件中可以给hbase配置一个临时目录，这里指定为mkdir /root/hbase/tmp，先执行命令创建文件夹。
mkdir  /root/hbase
mkdir  /root/hbase/tmp
mkdir  /root/hbase/pids
在<configuration>节点内增加以下配置：
<configuration>
  <property>
    <name>hbase.rootdir</name>
    <value>hdfs://192.168.1.66:9000/hbase</value>
  </property>
  <property>
    <name>hbase.zookeeper.property.dataDir</name>
    <value>/hadoop/zookeeper/dataDir</value>
  </property>
  <property>
                <name>hbase.zookeeper.quorum</name>
                <value>192.168.1.66</value>
                <description>the pos of zk</description>
        </property>
        <!-- 此处必须为true，不然hbase仍用自带的zk，若启动了外部的zookeeper，会导致冲突，hbase启动不起来 -->
        <property>
                <name>hbase.cluster.distributed</name>
                <value>true</value>
        </property>
        <!-- hbase主节点的位置 -->
        <property>
                <name>hbase.master</name>
                <value>192.168.1.66:60000</value>
        </property>
</configuration>
[root@hadoop hbase]# cat conf/regionservers
192.168.1.66
[root@hadoop hbase]# cp /hadoop/zookeeper/conf/zoo.cfg  /hadoop/hbase/conf/

启动hbase

[root@hadoop bin]# ./start-hbase.sh 
running master, logging to /hadoop/hbase//logs/hbase-root-master-hadoop.out
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option PermSize=128m; support was removed in 8.0
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0
: running regionserver, logging to /hadoop/hbase//logs/hbase-root-regionserver-hadoop.out
: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option PermSize=128m; support was removed in 8.0
: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0
--查看hbase相关进程HMaster、HRegionServer 已经起来了
[root@hadoop bin]# jps
12449 QuorumPeerMain
13094 Kafka
10376 SecondaryNameNode
12046 RunJar
11952 RunJar
11060 JobHistoryServer
10581 ResourceManager
10102 NameNode
10201 DataNode
10683 NodeManager
15263 HMaster
15391 HRegionServer
15679 Jps

10，安装KYLIN

下载连接
http://kylin.apache.org/cn/download/

(1）上传解压

[root@hadoop kylin]# pwd
/hadoop/kylin
[root@hadoop kylin]# ls
apache-kylin-2.4.0-bin-hbase1x.tar.gz
[root@hadoop kylin]# tar -zxvf apache-kylin-2.4.0-bin-hbase1x.tar.gz
[root@hadoop kylin]# rm -rf  apache-kylin-2.4.0-bin-hbase1x.tar.gz
[root@hadoop kylin]# 
[root@hadoop kylin]# mv apache-kylin-2.4.0-bin-hbase1x/* .
[root@hadoop kylin]# ls
apache-kylin-2.4.0-bin-hbase1x  bin  commit_SHA1  conf  lib  sample_cube  spark  tomcat  tool

（2）配置环境变量
/ etc / profile内容如下

export JAVA_HOME=/usr/java/jdk1.8.0_151
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
export PATH=$PATH:$JAVA_HOME/bin
export HADOOP_HOME=/hadoop/
export HADOOP_CONF_DIR=${HADOOP_HOME}/etc/hadoop
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib:$HADOOP_COMMON_LIB_NATIVE_DIR"
export HIVE_HOME=/hadoop/hive
export HIVE_CONF_DIR=${HIVE_HOME}/conf
export HCAT_HOME=$HIVE_HOME/hcatalog
export HIVE_DEPENDENCY=/hadoop/hive/conf:/hadoop/hive/lib/*:/hadoop/hive/hcatalog/share/hcatalog/hive-hcatalog-pig-adapter-2.3.3.jar:/hadoop/hive/hcatalog/share/hcatalog/hive-hcatalog-core-2.3.3.jar:/hadoop/hive/hcatalog/share/hcatalog/hive-hcatalog-server-extensions-2.3.3.jar:/hadoop/hive/hcatalog/share/hcatalog/hive-hcatalog-streaming-2.3.3.jar:/hadoop/hive/lib/hive-exec-2.3.3.jar
export HBASE_HOME=/hadoop/hbase/
export ZOOKEEPER_HOME=/hadoop/zookeeper
export KAFKA_HOME=/hadoop/kafka
export KYLIN_HOME=/hadoop/kylin/
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$HIVE_HOME/bin:$HCAT_HOME/bin:$HBASE_HOME/bin:$ZOOKEEPER_HOME:$KAFKA_HOME:$KYLIN_HOME/bin
export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar:${HIVE_HOME}/lib:$HBASE_HOME/lib:$KYLIN_HOME/lib
   [root@hadoop kylin]# source /etc/profile

（3）修改kylin.properties内容

[root@hadoop kylin]# vim conf/kylin.properties 
加入下面内容
kylin.rest.timezone=GMT+8
kylin.rest.servers=192.168.1.66:7070
kylin.job.jar=/hadoop/kylin/lib/kylin-job-2.4.0.jar
kylin.coprocessor.local.jar=/hadoop/kylin/lib/kylin-coprocessor-2.4.0.jar
kyin.server.mode=all 
kylin.rest.servers=192.168.1.66:7070

（4）编辑kylin_hive_conf.xml

[root@hadoop kylin]# vim conf/kylin_hive_conf.xml
<property>
        <name>hive.exec.compress.output</name>
        <value>false</value>
        <description>Enable compress</description>
    </property>

（5）编辑server.xml

[root@hadoop kylin]# vim tomcat/conf/server.xml
注释掉下面这点代码：
 <!-- Connector port="7443" protocol="org.apache.coyote.http11.Http11Protocol"
                   maxThreads="150" SSLEnabled="true" scheme="https" secure="true"
                   keystoreFile="conf/.keystore" keystorePass="changeit"
                   clientAuth="false" sslProtocol="TLS" /> -->

（6）编辑kylin.sh

#additionally add tomcat libs to HBASE_CLASSPATH_PREFIX
  export HBASE_CLASSPATH_PREFIX=${tomcat_root}/bin/bootstrap.jar:${tomcat_root}/bin/tomcat-juli.jar:${tomcat_root}/lib/*:$hive_dependency:${HBASE_CLASSPATH_PREFIX}

（7）启动kylin

[root@hadoop kylin]# cd bin/
[root@hadoop bin]# pwd
/hadoop/kylin/bin
[root@hadoop bin]# ./check-env.sh 
Retrieving hadoop conf dir...
KYLIN_HOME is set to /hadoop/kylin
[root@hadoop bin]# ./kylin.sh start
Retrieving hadoop conf dir...
KYLIN_HOME is set to /hadoop/kylin
Retrieving hive dependency...
。。。。。。。。。。。
A new Kylin instance is started by root. To stop it, run 'kylin.sh stop'
Check the log at /hadoop/kylin/logs/kylin.log
Web UI is at http://<hostname>:7070/kylin
[root@hadoop bin]# jps
13216 HMaster
10376 SecondaryNameNode
12011 RunJar
11918 RunJar
13070 HQuorumPeer
11060 JobHistoryServer
10581 ResourceManager
31381 RunJar
10102 NameNode
13462 HRegionServer
10201 DataNode
10683 NodeManager
31677 Jps

至此，安装已经完成，大家可以通过http：//：7070 / kylin去访问kylin了，至于cube及steam cube的官方案例，因为文章长度原因，笔者写到了这篇文章供参考：
hadoop + kylin安装及官方多维数据集/蒸汽多维数据集案例文档
8）初步验证及使用：

1）、测试创建项目从hive库取表：

：网页：http : //192.168.1.66 :
7070/kylin/login初始密码：ADMIN / KYLIN

由顶部菜单栏进入Model页面，然后单击Manage Projects。

点击+ Project按钮添加一个新的项目。

在顶部菜单栏上单击Model，然后单击左边的Data Source标签，它会列出所有加载进Kylin的表，单击Load Table按钮。

输入表名并点击同步按钮提交请求。

接下来就可以看到介绍的表结构了：

（2），运行官方案例：

[root@hadoop bin]# pwd
/hadoop/kylin/bin
[root@hadoop bin]# ./sample.sh 
Retrieving hadoop conf dir...
。。。。。。。。。
Sample cube is created successfully in project 'learn_kylin'.
Restart Kylin Server or click Web UI => System Tab => Reload Metadata to take effect

看到上面最后两个信息就说明案例使用的hive表都创建好了，然后重启kylin或则reload元数据
再次刷新页面：

选择第二个kylin_sales_cube
选择bulid，随意选择一个12年以后的日期

等待多维数据集创建完成。

做sql查询

编辑整个环境重启脚本方便日常启停：
环境停止脚本

cat stop.sh
#!/bin/bash
echo -e "\n========Start stop kylin========\n"
$KYLIN_HOME/bin/kylin.sh stop
sleep 5
echo -e "\n========Start stop hbase========\n"
$HBASE_HOME/bin/stop-hbase.sh
sleep 5
echo -e "\n========Start stop kafka========\n"
$KAFKA_HOME/bin/kafka-server-stop.sh $KAFKA_HOME/config/server.properties
sleep 3
echo -e "\n========Start stop zookeeper========\n"
$ZOOKEEPER_HOME/bin/zkServer.sh stop
sleep 3
echo -e "\n========Start stop jobhistory========\n"
mr-jobhistory-daemon.sh stop historyserver
sleep 3
echo -e "\n========Start stop yarn========\n"
stop-yarn.sh
sleep 5
echo -e "\n========Start stop dfs========\n"
stop-dfs.sh
sleep 5
echo -e "\n========Start stop prot========\n"
`lsof -i:9083|awk 'NR>=2{print "kill -9 "$2}'|sh`
`lsof -i:10000|awk 'NR>=2{print "kill -9 "$2}'|sh`
sleep 2
echo -e "\n========Check process========\n"

　　环境启动脚本

[root@hadoop hadoop]# cat start.sh 
#!/bin/bash
echo -e "\n========Start run dfs========\n"
start-dfs.sh
sleep 5
echo -e "\n========Start run yarn========\n"
start-yarn.sh
sleep 3
echo -e "\n========Start run jobhistory========\n"
mr-jobhistory-daemon.sh start historyserver
sleep 2
echo -e "\n========Start run metastore========\n"
nohup hive --service metastore >> ~/metastore.log 2>&1 &  
sleep 10
echo -e "\n========Start run hiveserver2========\n"
nohup  hive --service hiveserver2 >> ~/hiveserver2.log 2>&1 &
sleep 10
echo -e "\n========Check Port========\n"
netstat  -lnp|grep 9083
sleep 5
netstat  -lnp|grep 10000
sleep 2
echo -e "\n========Start run zookeeper========\n"
$ZOOKEEPER_HOME/bin/zkServer.sh start
sleep 5
echo -e "\n========Start run kafka========\n"
$KAFKA_HOME/bin/kafka-server-start.sh  $KAFKA_HOME/config/server.properties
sleep 5
echo -e "\n========Start run hbase========\n"
$HBASE_HOME/bin/start-hbase.sh
sleep 5
echo -e "\n========Check process========\n"
jps
sleep 1
echo -e "\n========Start run kylin========\n"
$KYLIN_HOME/bin/kylin.sh start

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大数据集群运维（1）Hadoop + Hive + HBase + Kylin伪分布式安装[通俗易懂]

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