大数据运维（37） Hadoop+Hive+HBase+Kylin +spark+Flink伪分布式安装

问题导读

1.Centos7如何安装配置？

2.linux网络配置如何进行？

3.linux环境下java如何安装？

4.linux环境下SSH免密码登录如何配置？

5.linux环境下Hadoop2.7如何安装？

6.linux环境下Mysql如何安装？

7.linux环境下Hive如何安装？

8.linux环境下Zookeeper如何安装？

9.linux环境下Kafka如何安装？

10.linux环境下Hbase如何安装？

11.linux环境下KYLIN如何安装？

12.linux环境下scala如何安装？

13.linux环境下spark如何安装？

最近学习Kylin，肯定需要一个已经安装好的环境，Kylin的依赖环境官方介绍如下：
依赖于 Hadoop 集群处理大量的数据集。您需要准备一个配置好 HDFS，YARN，MapReduce,，Hive， HBase，Zookeeper 和其他服务的 Hadoop 集群供 Kylin 运行。Kylin 可以在 Hadoop 集群的任意节点上启动。方便起见，您可以在 master 节点上运行 Kylin。但为了更好的稳定性，我们建议您将 Kylin 部署在一个干净的 Hadoop client 节点上，该节点上 Hive，HBase，HDFS 等命令行已安装好且 client 配置（如 core-site.xml，hive-site.xml，hbase-site.xml及其他）也已经合理的配置且其可以自动和其它节点同步。运行 Kylin 的 Linux 账户要有访问 Hadoop 集群的权限，包括创建/写入 HDFS 文件夹，Hive 表， HBase 表和提交 MapReduce 任务的权限。

软件要求
Hadoop: 2.7+, 3.1+ (since v2.5)
Hive: 0.13 - 1.2.1+
HBase: 1.1+, 2.0 (since v2.5)
Spark (可选) 2.3.0+
Kafka (可选) 1.0.0+ (since v2.5)
JDK: 1.8+ (since v2.5)
OS: Linux only, CentOS 6.5+ or 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！很多人写的安装部署文档要么是步骤东一块西一块，要么是省略，扔个连接或则说让自己去百度。在经历了很多坑之后终于是把完全分布式的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系统的安装为例子介绍详细过程，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，不再一一列举，按照下面步骤是完全可以在Centos 7/Redhat 6 64位系统安装成功的。



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date&time设置时间



接下来点击software selection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done后，进入下面所示界面，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



接下来选择网络设置



设置hostname,点击apply。然后选择configure设置网络ip





最后done点击安装就可以了：



可以在这个界面设置下root密码，等待安装完成就可以了。这是虚拟机的安装，接下来配置linux,安装软件。

1、linux网络配置：

（1）因为Centos 7安装的精简模式，先解决linux网络问题来让windows能够用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

（2）重启网络

[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

[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加入下面内容

[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key，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/



(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.xm

[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 ~]# vi /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 6，两个测试环境如果安装时要下载对应系统的rpm包，不然不兼容的rpm包安装时会报下面的错误(比如在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 server
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,这里配置好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common–>libs–>client–>server的顺序。若不按照此顺序，也会有一定“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默认安装在/var/lib下。

(5）更改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

[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

[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/user/hive/warehouse目录：

[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

将hive_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，并且赋予读写权限。

[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 system: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system: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,将该name对应的value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，将该name对应的value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value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value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value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

[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

[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 http://www.slf4j.org/codes.html#multiple_bindings 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hive：

启动metastore服务

nohup hive --service metastore >> ~/metastore.log 2>&1 &

启动hiveserver2，jdbc连接均需要

nohup  hive --service hiveserver2 >> ~/hiveserver2.log 2>&1 &

检测hive和hive2端口

[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  

测试hive

[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 http://www.slf4j.org/codes.html#multiple_bindings 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
!
!=
$sum0
%
。。。。。
hive> desc function sum;
OK
sum(x) - Returns the sum of a set of numbers
Time taken: 0.183 seconds, Fetched: 1 row(s)
hive> create database sbux;
OK
Time taken: 0.236 seconds
hive> use sbux;
OK
Time taken: 0.033 seconds
hive> create table student(id int, name string) row format delimited fields terminated by '	';
OK
Time taken: 0.909 seconds
hive> desc student;
OK
id                          int                                             
name                        string                                          
Time taken: 0.121 seconds, Fetched: 2 row(s)
在$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 style="overflow-wrap: break-word; color: rgb(68, 68, 68); font-family: "Microsoft Yahei", tahoma, arial, "Hiragino Sans GB", 宋体, sans-serif;">
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

【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，用来标识当前主机，conf/zoo.cfg文件中配置的server.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可用性：

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source使其生效。

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
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cube/steam cube案例文档
8）初步验证及使用：

测试创建项目从hive库取表：

打开网页：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，然后点击 Manage Projects。

点击 + Project 按钮添加一个新的项目。


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

输入表名并点击 Sync 按钮提交请求。

接下来就可以看到导入的表结构了：

(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  

看到上面最后两条信息就说明案例使用的hive表都创建好了，接下来重启kylin或则 reload metadata
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

然后切换到monitor界面：

等待cube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

[root@hadoop hadoop]# cat stop.sh
#!/bin/bash
echo -e "
========Start stop kylin========
"
$KYLIN_HOME/bin/kylin.sh stop
sleep 5
echo -e "
========Start stop hbase========
"
$HBASE_HOME/bin/stop-hbase.sh
sleep 5
echo -e "
========Start stop kafka========
"
$KAFKA_HOME/bin/kafka-server-stop.sh  $KAFKA_HOME/config/server.properties
sleep 3
echo -e "
========Start stop zookeeper========
"
$ZOOKEEPER_HOME/bin/zkServer.sh stop
sleep 3
echo -e "
========Start stop jobhistory========
"
mr-jobhistory-daemon.sh stop historyserver
sleep 3
echo -e "
========Start stop yarn========
"
stop-yarn.sh
sleep 5
echo -e "
========Start stop dfs========
"
stop-dfs.sh
sleep 5
echo -e "
========Start stop prot========
"
`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 "
========Check process========
"
jps

环境启动脚本

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

11.安装scala

解压scala安装包到任意目录

cd /home/tom
$ tar -xzvf scala-2.10.6.tgz

在/etc/profile文件的末尾添加环境变量：

export SCALA_HOME=/home/tom//scala-2.10.6
export PATH=$SCALA_HOME/bin:$PATH

保存并更新/etc/profile：

 source /etc/profile

查看是否成功：

scala -version

12.安装Spark

解压spark安装包到任意目录：

cd /home/tom
$ tar -xzvf spark-1.6.0-bin-hadoop2.6.tgz
$ mv spark-1.6.0-bin-hadoop2.6 spark-1.6.0
$ sudo vim /etc/profile[/mw_shl_code]

在/etc/profile文件的末尾添加环境变量：

export SPARK_HOME=/home/tom/spark-1.6.0
export PATH=$SPARK_HOME/bin:$PATH

保存并更新/etc/profile：

source /etc/profile

在conf目录下复制并重命名spark-env.sh.template为spark-env.sh：

cp spark-env.sh.template spark-env.sh
$ vi spark-env.sh

在spark-env.sh中添加：

export JAVA_HOME=/home/tom/jdk1.8.0_73/
export SCALA_HOME=/home/tom//scala-2.10.6
export SPARK_MASTER_IP=localhost
export SPARK_WORKER_MEMORY=4G

启动

$SPARK_HOME/sbin/start-all.sh

停止

$SPARK_HOME/sbin/stop-all.sh

测试Spark是否安装成功：

$SPARK_HOME/bin/run-example SparkPi

检查WebUI，浏览器打开端口：http://localhost:8080

查看集群环境
http://master:8080/  访问正常

进入spark-shell
$spark-shell   执行正常如下图


查看jobs等信息
http://master:4040/jobs/  访问正常。

 13、Flink安装

一：安装

Flink官网下载地址：https://flink.apache.org/downloads.html

选择1.6.3版本

 下载：

wget http://mirrors.hust.edu.cn/apache/flink/flink-1.7.1/flink-1.7.1-bin-hadoop26-scala_2.11.tgz

解压：

tar -zxvf flink-1.6.3-bin-hadoop26-scala_2.11.tgz
mv  flink-1.6.3 flink

查看本机host

进入flink目录，修改conf/flink-conf.yaml文件

vim  conf/flink-conf.yaml

修改conf/masters文件，修改后内容如下：

启动单机版flink：

bin/start-cluster.sh

启动界面如下：

查看启动是否成功：

 查看dashboard界面:http://192.168.186.129:808

 

二：官方案例演示

1.启动一个终端输入如下指令：

nc -lk 8000

2.启动第二个终端，执行flink自带的wordcount案例

bin/flink run examples/streaming/SocketWindowWordCount.jar --port 8000

3.在第一个终端发送数据：

4.测试结果保存在log/flink-root-taskexecutor-0-woniu.out文件中

5. Dashboard也可以看到任务信息