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【大数据开发运维解决方案】Hadoop+Hive+HBase+Kylin 伪分布式安装指南

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【大数据开发运维解决方案】Hadoop+Hive+HBase+Kylin 伪分布式安装指南Kylin 安装学习 Hadoop Mysql Hive Hbase Kylin 伪分布式安装最近学习 Kylin 肯定需要一个已经安装好的环境 Kylin 依赖于 Hadoop 集群处理大量的数据集

Hadoop2.7.6+Mysql5.7+Hive2.3.2+Hbase1.4.9+Kylin2.4单机伪分布式安装文档

注意：


本文档已经有了最新版本，主要改动地方为：
1、zookeeper改为使用安装的外置zookeeper而非hbase自带zookeeper ，新加zookeeper安装过程
2、hbase使用外置zookeeper，配置做相应改动
3、新加kafka相关实施配置来支持Kylin的steam cube的实验
新版本的文档连接在这：Hadoop2.7.6+Mysql5.7+Hive2.3.2+zookeeper3.4.6+kafka2.11+Hbase1.4.9+Kylin2.4单机伪分布式安装文档
下面的文档是原来老版的，适合不用kafka来做steam cube实验的读者使用。

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，后面的环境部署完关于如何将关系型数据库(我这里是用oracle）通过sqoop增量导入到hive的实验可以参考下面贴出的本人文章连接，至于其他相关知识请参考文人其他文章。
1、sqoop1.4.7的安装及使用(hadoop2.7环境)
2、Oracle通过sqoop同步数据到hive
3、Oracle通过sqoop增量同步数据到hive

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/Redhat6 64位系统安装成功的。
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一、Centos7安装

打开vmware，创建新虚拟机安装Centos 774位系统：
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完成后界面如下：
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选择启动虚拟机，选择第一个选项回车：
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选择继续在这里插入图片描述
等待依赖包检查完成，date&time设置时间
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接下来software selection选择安装模式，这里选择最精简安装：
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然后done出来之后，等待依赖包检查完成，然后设置磁盘分区
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选择现在设置：
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done后，进入下面所示界面，选择标准分区，然后设置+号设置分区
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最后分好区如下：
ran
然后done后确认
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接下来选择网络设置
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设置hostname,apply。然后选择configure设置网络ip
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最后done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。

二、Linux环境配置：

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

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(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></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--192.168.1.66-72 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

# 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

6、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@s 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 
[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 
[root@s hadoop]# rpm -qa |grep mysql mysql-community-common-5.7.18-1.el7.x86_64 通过此命令卸载： [root@s 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=

[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 
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 
[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.Z 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@s mysql]# /etc/rc.d/init.d/mysqld start Starting mysqld: [ OK ] [root@s 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@s mysql]# chkconfig mysqld on [root@s mysql]# chmod 755 /etc/rc.d/init.d/mysqld [root@s mysql]# service mysqld start Starting mysqld: [ OK ] [root@s 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

7、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/user/hive/warehouse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 H I V E H O M E / c o n f / h i v e − s i t e . x m l 中的临时目录将 h i v e − s i t e . x m l 文件中的 HIVE_HOME/conf/hive-site.xml中的临时目录 将hive-site.xml文件中的 HIVEH​OME/conf/hive−site.xml中的临时目录将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 s y s t e m : j a v a . i o . t m p d i r 替换成 / h a d o o p / h i v e / t m p 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 
<property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://localhost:3306/metastore?createDatabaseIfNotExist=true&amp;characterEncoding=UTF-8&amp;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

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 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 &         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 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
!
!=
$sum0
%
。。。。。
hive> desc function sum;
OK
sum(x) - Returns the sum of a set of numbers
Time taken: 0.183 seconds, Fetched: 1 row(s)
hive> create database sbux;
OK
Time taken: 0.236 seconds
hive> use sbux;
OK
Time taken: 0.033 seconds
hive> create table student(id int, name string) row format delimited fields terminated by '\t';
OK
Time taken: 0.909 seconds
hive> desc student;
OK
id                  	int                 	                    
name                	string              	                    
Time taken: 0.121 seconds, Fetched: 2 row(s)
 在$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：
在这里插入图片描述
在这里插入图片描述
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 |  | 6 | 0 | root | 0 | 1 | student | MANAGED_TABLE | NULL | NULL | | +--------+-------------+-------+------------------+-------+-----------+-------+----------+---------------+--------------------+--------------------+--------------------+ 1 row in set (0.00 sec)

8、安装hbase

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]# 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 PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$HIVE_HOME/bin::$HCAT_HOME/bin:$HBASE_HOME/bin export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar:${HIVE_HOME}/lib:$HBASE_HOME/lib

（3）详细配置

[root@hadoop hbase]# cd /hadoop/hbase/ 创建zookeeper数据目录： [root@hadoop hbase]# mkdir data 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/ 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/hbase/data/zookeeper</value> </property> <property> <name>hbase.cluster.distributed</name> <value>true</value> </property> </configuration> [root@hadoop hbase]# cat conf/regionservers 192.168.1.66

（4）启动hbase并测试可用性：

[root@hadoop hbase]# bin/hbase-daemon.sh start zookeeper running zookeeper, logging to /hadoop/hbase//logs/hbase-root-zookeeper-hadoop.out [root@hadoop hbase]# bin/hbase-daemon.sh start master 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 [root@hadoop hbase]# bin/hbase-daemon.sh start regionserver 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 [root@hadoop hbase]# jps 13216 HMaster 10376 SecondaryNameNode 12011 RunJar 11918 RunJar 13070 HQuorumPeer 12623 RunJar 11060 JobHistoryServer 10581 ResourceManager 10102 NameNode 13462 HRegionServer 10201 DataNode 10683 NodeManager 13758 Jps 可以看出，新增了HQuorumPeer，HRegionServer和HMaster三个进程。

（5）访问web页面： http://192.168.1.66:16030/rs-status

在这里插入图片描述

9、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 
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 KYLIN_HOME=/hadoop/kylin/ export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$HIVE_HOME/bin:$HCAT_HOME/bin:$HBASE_HOME/bin:$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

（8）初步验证及使用：

1）、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
在这里插入图片描述
由顶部菜单栏进入 Model 页面，然后 Manage Projects。

在这里插入图片描述
+ Project 按钮添加一个新的项目。
在这里插入图片描述
在这里插入图片描述

在顶部菜单栏 Model，然后左边的 Data Source 标签，它会列出所有加载进 Kylin 的表， Load Table 按钮。
在这里插入图片描述
输入表名并 Sync 按钮提交请求。
在这里插入图片描述
接下来就可以看到导入的表结构了：
在这里插入图片描述
(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：
在这里插入图片描述
选择第二个kylin_sales_cube
在这里插入图片描述
选择bulid，随意选择一个12年以后的日期
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然后切换到monitor界面：
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等待cube创建完成。
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做sql查询

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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 "\n========Start stop kylin========\n" $KYLIN_HOME/bin/kylin.sh stop sleep 5 echo -e "\n========Start stop hbase-regionserver========\n" $HBASE_HOME/bin/hbase-daemon.sh stop regionserver sleep 5 echo -e "\n========Start stop hbase-master========\n" $HBASE_HOME/bin/hbase-daemon.sh stop master sleep 3 echo -e "\n========Start stop zookeeper========\n" $HBASE_HOME/bin/hbase-daemon.sh stop zookeeper 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" jps

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 2 echo -e "\n========Start run yarn========\n" start-yarn.sh sleep 2 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" $HBASE_HOME/bin/hbase-daemon.sh start zookeeper sleep 1 echo -e "\n========Start run hbase-master========\n" $HBASE_HOME/bin/hbase-daemon.sh start master sleep 1 echo -e "\n========Start run hbase-regionserver========\n" $HBASE_HOME/bin/hbase-daemon.sh start regionserver sleep 1 echo -e "\n========Check process========\n" jps sleep 1 echo -e "\n========Start run kylin========\n" $KYLIN_HOME/bin/kylin.sh start
今天的文章 【大数据开发运维解决方案】Hadoop+Hive+HBase+Kylin 伪分布式安装指南分享到此就结束了，感谢您的阅读。
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