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CDH版本大数据集群下搭建Hue(hadoop-2.6.0-cdh5.5.4.gz + hue-3.9.0-cdh5.5.4.tar.gz)(博主推荐)

 

 

 

  不多说,直接上干货!

  我的集群机器情况是 bigdatamaster(192.168.80.10)、bigdataslave1(192.168.80.11)和bigdataslave2(192.168.80.12)

  然后,安装目录是在/home/hadoop/app下。

 

  官方建议在master机器上安装Hue,我这里也不例外。安装在bigdatamaster机器上。

 

 Hue版本:hue-3.9.0-cdh5.5.4
 需要编译才能使用(联网)


 说给大家的话:大家电脑的配置好的话,一定要安装cloudera manager。毕竟是一家人的。废话不多说,因为我目前读研,自己笔记本电脑最大8G,只能玩手动来练手。
纯粹是为了给身边没高配且条件有限的学生党看的! 但我已经在实验室机器群里搭建好cloudera manager 以及 ambari都有。

大数据领域两大最主流集群管理工具Ambari和Cloudera Manger

CentOS6.5下Cloudera安装搭建部署大数据集群(图文分五大步详解)(博主强烈推荐)

CentOS6.5下Ambari安装搭建部署大数据集群(图文分五大步详解)(博主强烈推荐)

Ubuntu14.04下Ambari安装搭建部署大数据集群(图文分五大步详解)(博主强烈推荐)

Ubuntu14.04下Cloudera安装搭建部署大数据集群(图文分五大步详解)(博主强烈推荐)(在线或离线)

 

 

 

 

 




  因为,这篇博客,我是以CentOS为例的。
http://archive.cloudera.com/cdh5/cdh/5/hue-3.9.0-cdh5.5.4/manual.html#_install_hue

    其实,其他系统如Ubuntu而言,就是这些依赖安装有些区别而已。这里,大家自行去看官网吧!









  

 一、hue-3.9.0-cdh5.5.4.tar.gz的下载地址

http://archive.cloudera.com/cdh5/cdh/5/hue-3.9.0-cdh5.5.4.tar.gz 

 

 

 

二、在安装Hue之前,需要安装各种依赖包

   ant
       asciidoc
       cyrus-sasl-devel
       cyrus-sasl-gssapi
       gcc
       gcc-c++
       krb5-devel
       libtidy (for unit tests only)
       libxml2-devel
       libxslt-devel
       make
       mvn (from ``maven`` package or maven3 tarball)
       MySQL(可以不用安装)(当然,我在安装Hive时,已经在bigdatamaster这台机器就安装了MySQL)
       mysql-devel  (可以不用安装)(当然,我在安装Hive时,已经在bigdatamaster这台机器就安装了MySQL)
       openldap-devel
       Python-devel
       sqlite-devel
       openssl-devel (for version 7+)
       gmp-devel

 

 

  或者

ant
asciidoc
cyrus-sasl-devel
cyrus-sasl-gssapi
gcc
gcc-c++
krb5-devel
libtidy (for unit tests only)
libxml2-devel
libxslt-devel
make mvn (
from maven package or maven3 tarball) mysql (我这里不安装了,因为在hive那边已经安装了) mysql-devel (我这里不安装了,因为在hive那边已经安装了) openldap-devel python-devel sqlite-devel openssl-devel (for version 7+)
gmp-devel

 

 

 

  检查系统上有没有上述的那些包

rpm -qa | grep package_name

 

  注意,不是上述的用法,是具体的。

 

 

[hadoop@bigdatamaster app]$ rpm -qa | grep ant
wpa_supplicant-0.7.3-4.el6_3.x86_64
anthy-9100h-10.1.el6.x86_64
ibus-anthy-1.2.1-3.el6.x86_64
enchant-1.5.0-4.el6.x86_64
[hadoop@bigdatamaster app]$ rpm -qa | grep asciidoc
[hadoop@bigdatamaster app]$ rpm -qa | grep cyrus-sasl-devel
[hadoop@bigdatamaster app]$ rpm -qa | grep gcc
libgcc-4.4.7-4.el6.x86_64
[hadoop@bigdatamaster app]$ rpm -qa | grep gcc-c++
[hadoop@bigdatamaster app]$ rpm -qa | grep krb5-devel
krb5-devel-1.10.3-65.el6.x86_64
[hadoop@bigdatamaster app]$ rpm -qa | grep libtidy
[hadoop@bigdatamaster app]$ rpm -qa | grep libxml2-devel
[hadoop@bigdatamaster app]$ rpm -qa | grep libxslt-devel
[hadoop@bigdatamaster app]$ rpm -qa | grep make
make-3.81-20.el6.x86_64
[hadoop@bigdatamaster app]$ rpm -qa | grep mvn
[hadoop@bigdatamaster app]$ rpm -qa | grep mysql-devel
mysql-devel-5.1.73-8.el6_8.x86_64
[hadoop@bigdatamaster app]$ rpm -qa | grep openldap-devel
[hadoop@bigdatamaster app]$ rpm -qa | grep python-devel
[hadoop@bigdatamaster app]$ rpm -qa | grep sqlite-devel
[hadoop@bigdatamaster app]$ rpm -qa | grep openssl-devel
openssl-devel-1.0.1e-57.el6.x86_64
[hadoop@bigdatamaster app]$ rpm -qa | grep gmp-devel
[hadoop@bigdatamaster app]$ 

   这一步,我看到有些资料上说,需要先卸载掉,自带的这些。不然会对后续的安装,产生版本冲突的问题。

    直接用yum安装的,中间可能会报一些依赖的版本冲突问题,可以卸载已经安装的版本,然后再装。

 

 

 

卸载自带的包

rpm -e --nodeps   ***

  

 

   查阅和卸载自带的ant

[hadoop@bigdatamaster app]$ su root
Password: 
[root@bigdatamaster app]# rpm -qa | grep ant
wpa_supplicant-0.7.3-4.el6_3.x86_64
anthy-9100h-10.1.el6.x86_64
ibus-anthy-1.2.1-3.el6.x86_64
enchant-1.5.0-4.el6.x86_64
[root@bigdatamaster app]# rpm -e --nodeps wpa_supplicant-0.7.3-4.el6_3.x86_64
[root@bigdatamaster app]# rpm -e --nodeps anthy-9100h-10.1.el6.x86_64
[root@bigdatamaster app]# rpm -e --nodeps ibus-anthy-1.2.1-3.el6.x86_64
[root@bigdatamaster app]# rpm -e --nodeps enchant-1.5.0-4.el6.x86_64
[root@bigdatamaster app]# 

 

 

 

   查阅和卸载自带的asciidoc、cyrus-sasl-devel、gcc

 

[root@bigdatamaster app]# rpm -qa | grep asciidoc
[root@bigdatamaster app]# rpm -qa | grep cyrus-sasl-devel
[root@bigdatamaster app]# rpm -qa | grep gcc 
libgcc-4.4.7-4.el6.x86_64
[root@bigdatamaster app]# rpm -e --nodeps libgcc-4.4.7-4.el6.x86_64 (删除完这个命令,我就后悔了)
[root@bigdatamaster app]# 

 

 

   其他的,我都不多赘述了,也可以大家在中间,删除的时候,会出现如下的问题。

[root@bigdatamaster app]# rpm -qa | grep krb5-devel
rpm: error while loading shared libraries: libgcc_s.so.1: cannot open shared object file: No such file or directory
[root@bigdatamaster app]# rpm -qa | grep libtidy
rpm: error while loading shared libraries: libgcc_s.so.1: cannot open shared object file: No such file or directory

乱删rpm导致再次安装包时出现 error while loading shared libraries: libgcc_s.so.1问题

 

   解决办法

   说先搜下有没有这个libgcc_s.so.1共享库,果然是有的。

[root@bigdatamaster app]# locate libgcc_s.so.1

  在/lib64/libgcc_s.so.1。

  然后,我的还在/lib64下,则

 error while loading shared libraries: xxx.so.x"错误的原因和解决办法 

  即上面的这篇博客,里的1) 如果共享库文件安装到了/lib或/usr/lib目录下, 那么需执行一下ldconfig命令。

   其实吧,我感觉,这些资料都不好。

  

 最简单的办法就是,我们不是做大数据的么,直接,把另外一台机器的libgcc_s-4.4.6-20110824.so.1到/lib64下恢复正常。

 

 

 

   添加maven源

wget http://repos.fedorapeople.org/repos/dchen/apache-maven/epel-apache-maven.repo -O /etc/yum.repos.d/epel-apache-maven.repo

[root@bigdatamaster app]# wget http://repos.fedorapeople.org/repos/dchen/apache-maven/epel-apache-maven.repo -O /etc/yum.repos.d/epel-apache-maven.repo
--2017-05-05 19:52:01--  http://repos.fedorapeople.org/repos/dchen/apache-maven/epel-apache-maven.repo
Resolving repos.fedorapeople.org... 152.19.134.199, 2610:28:3090:3001:5054:ff:fea7:9474
Connecting to repos.fedorapeople.org|152.19.134.199|:80... connected.
HTTP request sent, awaiting response... 302 Found
Location: https://repos.fedorapeople.org/repos/dchen/apache-maven/epel-apache-maven.repo [following]
--2017-05-05 19:52:02--  https://repos.fedorapeople.org/repos/dchen/apache-maven/epel-apache-maven.repo
Connecting to repos.fedorapeople.org|152.19.134.199|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 445
Saving to: “/etc/yum.repos.d/epel-apache-maven.repo”

100%[=====================================================================================================================================================>] 445         --.-K/s   in 0s      

2017-05-05 19:52:04 (11.8 MB/s) - “/etc/yum.repos.d/epel-apache-maven.repo” saved [445/445]

[root@bigdatamaster app]# 

 

 

 

 

  

 

 安装依赖 (注意mysql 和 mysql - dever 不需要安装了,因为我在hive那边已经安装好了)(别怪我没提醒你)(你这里若再安装,版本不兼容,会出问题的)

yum install -y ant asciidoc cyrus-sasl-devel cyrus-sasl-gssapi gcc gcc-c++ krb5-devel libtidy libxml2-devel libxslt-devel make mvn openldap-devel python-devel sqlite-devel  openssl-devel gmp-devel

  

  或者

下载需要的系统包

yum install ant asciidoc cyrus-sasl-devel cyrus-sasl-gssapi gcc gcc-c++ krb5-devel ibtidy libxml2-devel libxslt-devel openldap-devel python-devel 
sqlite-devel openssl-devel mysql-devel gmp-devel

 

 

 

 

  Verifying  : python-libs-2.6.6-51.el6.x86_64                                                                                                                                           75/79 
  Verifying  : gmp-4.3.1-7.el6_2.2.x86_64                                                                                                                                                76/79 
  Verifying  : python-2.6.6-51.el6.x86_64                                                                                                                                                77/79 
  Verifying  : libxml2-python-2.7.6-14.el6.x86_64                                                                                                                                        78/79 
  Verifying  : sqlite-3.6.20-1.el6.x86_64                                                                                                                                                79/79 

Installed:
  ant.x86_64 0:1.7.1-15.el6                      asciidoc.noarch 0:8.4.5-4.1.el6              cyrus-sasl-devel.x86_64 0:2.1.23-15.el6_6.2        gcc.x86_64 0:4.4.7-18.el6                     
  gcc-c++.x86_64 0:4.4.7-18.el6                  gmp-devel.x86_64 0:4.3.1-12.el6              libtidy.x86_64 0:0.99.0-19.20070615.1.el6          libxml2-devel.x86_64 0:2.7.6-21.el6_8.1       
  libxslt-devel.x86_64 0:1.1.26-2.el6_3.1        openldap-devel.x86_64 0:2.4.40-16.el6        python-devel.x86_64 0:2.6.6-66.el6_8               sqlite-devel.x86_64 0:3.6.20-1.el6_7.2        

Dependency Installed:
  cloog-ppl.x86_64 0:0.15.7-1.2.el6                     cpp.x86_64 0:4.4.7-18.el6                                        docbook-style-xsl.noarch 0:1.75.2-6.el6                               
  java-1.5.0-gcj.x86_64 0:1.5.0.0-29.1.el6              java-1.7.0-openjdk.x86_64 1:1.7.0.131-2.6.9.0.el6_8              java-1.7.0-openjdk-devel.x86_64 1:1.7.0.131-2.6.9.0.el6_8             
  java_cup.x86_64 1:0.10k-5.el6                         libgcc.x86_64 0:4.4.7-18.el6                                     libgcj.x86_64 0:4.4.7-18.el6                                          
  libgcrypt-devel.x86_64 0:1.4.5-12.el6_8               libgpg-error-devel.x86_64 0:1.7-4.el6                            libstdc++-devel.x86_64 0:4.4.7-18.el6                                 
  lksctp-tools.x86_64 0:1.0.10-7.el6                    mpfr.x86_64 0:2.4.1-6.el6                                        pcsc-lite-libs.x86_64 0:1.5.2-16.el6                                  
  ppl.x86_64 0:0.10.2-11.el6                            sinjdoc.x86_64 0:0.5-9.1.el6                                     tzdata-java.noarch 0:2017b-1.el6                                      
  xerces-j2.x86_64 0:2.7.1-12.7.el6_5                   xml-commons-apis.x86_64 0:1.3.04-3.6.el6                         xml-commons-resolver.x86_64 0:1.1-4.18.el6                            

Updated:
  cyrus-sasl-gssapi.x86_64 0:2.1.23-15.el6_6.2                                                            make.x86_64 1:3.81-23.el6                                                           

Dependency Updated:
  cyrus-sasl.x86_64 0:2.1.23-15.el6_6.2      cyrus-sasl-lib.x86_64 0:2.1.23-15.el6_6.2         cyrus-sasl-md5.x86_64 0:2.1.23-15.el6_6.2     cyrus-sasl-plain.x86_64 0:2.1.23-15.el6_6.2    
  gmp.x86_64 0:4.3.1-12.el6                  libgcrypt.x86_64 0:1.4.5-12.el6_8                 libgomp.x86_64 0:4.4.7-18.el6                 libstdc++.x86_64 0:4.4.7-18.el6                
  libxml2.x86_64 0:2.7.6-21.el6_8.1          libxml2-python.x86_64 0:2.7.6-21.el6_8.1          nspr.x86_64 0:4.13.1-1.el6                    nss.x86_64 0:3.28.4-1.el6_9                    
  nss-softokn.x86_64 0:3.14.3-23.3.el6_8     nss-softokn-freebl.x86_64 0:3.14.3-23.3.el6_8     nss-sysinit.x86_64 0:3.28.4-1.el6_9           nss-tools.x86_64 0:3.28.4-1.el6_9              
  nss-util.x86_64 0:3.28.4-1.el6_9           openldap.x86_64 0:2.4.40-16.el6                   python.x86_64 0:2.6.6-66.el6_8                python-libs.x86_64 0:2.6.6-66.el6_8            
  sqlite.x86_64 0:3.6.20-1.el6_7.2          

Complete!
[root@bigdatamaster app]# 

 

 

 

 

上传hue-3.9.0-cdh5.5.4.tar.gz(我这里选择先下载好,再上传)

    当然,这一步,大家也是可以下载,编译源码(hue 3.9),编译时间较长

git clone https://github.com/cloudera/hue.git branch-3.9
cd branch-3.9
make apps

 

  编译完后也可以选择安装

make install

 

 

   我这里选择上传

[hadoop@bigdatamaster app]$ pwd
/home/hadoop/app
[hadoop@bigdatamaster app]$ ll
total 60
drwxr-xr-x   8 hadoop hadoop 4096 Apr 26  2016 apache-flume-1.6.0-cdh5.5.4-bin
lrwxrwxrwx   1 hadoop hadoop   19 May  5 11:15 elasticsearch -> elasticsearch-2.4.3
drwxrwxr-x   7 hadoop hadoop 4096 May  5 11:35 elasticsearch-2.4.3
lrwxrwxrwx   1 hadoop hadoop   22 May  5 12:44 filebeat -> filebeat-1.3.1-x86_64/
drwxr-xr-x   2 hadoop hadoop 4096 May  5 12:47 filebeat-1.3.1-x86_64
lrwxrwxrwx   1 hadoop hadoop   32 May  5 09:31 flume -> apache-flume-1.6.0-cdh5.5.4-bin/
lrwxrwxrwx.  1 hadoop hadoop   21 May  4 20:59 hadoop -> hadoop-2.6.0-cdh5.5.4
drwxr-xr-x. 15 hadoop hadoop 4096 May  4 21:14 hadoop-2.6.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   20 May  4 21:48 hbase -> hbase-1.0.0-cdh5.5.4
drwxr-xr-x. 27 hadoop hadoop 4096 May  4 22:05 hbase-1.0.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   20 May  4 22:37 hive -> hive-1.1.0-cdh5.5.4/
drwxr-xr-x. 10 hadoop hadoop 4096 Apr 26  2016 hive-1.1.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   11 May  4 20:34 jdk -> jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop 4096 Apr 11  2015 jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop 4096 Aug  5  2015 jdk1.8.0_60
lrwxrwxrwx.  1 hadoop hadoop   19 May  4 22:49 kafka -> kafka_2.11-0.8.2.2/
drwxr-xr-x.  6 hadoop hadoop 4096 May  4 22:57 kafka_2.11-0.8.2.2
lrwxrwxrwx   1 hadoop hadoop   26 May  5 19:03 kibana -> kibana-4.6.3-linux-x86_64/
drwxrwxr-x  11 hadoop hadoop 4096 Nov  4 23:24 kibana-4.6.3-linux-x86_64
lrwxrwxrwx   1 hadoop hadoop   15 May  5 14:44 logstash -> logstash-2.4.1/
drwxrwxr-x   5 hadoop hadoop 4096 May  5 14:44 logstash-2.4.1
lrwxrwxrwx   1 hadoop hadoop   12 May  5 09:05 scala -> scala-2.11.8
drwxrwxr-x   6 hadoop hadoop 4096 Mar  4  2016 scala-2.11.8
lrwxrwxrwx   1 hadoop hadoop   25 May  5 09:05 spark -> spark-2.1.0-bin-hadoop2.6
drwxr-xr-x  14 hadoop hadoop 4096 May  5 09:20 spark-2.1.0-bin-hadoop2.6
lrwxrwxrwx   1 hadoop hadoop   21 May  5 09:49 sqoop -> sqoop-1.4.6-cdh5.5.4/
drwxr-xr-x  10 hadoop hadoop 4096 Apr 26  2016 sqoop-1.4.6-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   25 May  4 20:44 zookeeper -> zookeeper-3.4.5-cdh5.5.4/
drwxr-xr-x. 16 hadoop hadoop 4096 May  4 20:52 zookeeper-3.4.5-cdh5.5.4
[hadoop@bigdatamaster app]$ rz

[hadoop@bigdatamaster app]$ ll
total 70956
drwxr-xr-x   8 hadoop hadoop     4096 Apr 26  2016 apache-flume-1.6.0-cdh5.5.4-bin
lrwxrwxrwx   1 hadoop hadoop       19 May  5 11:15 elasticsearch -> elasticsearch-2.4.3
drwxrwxr-x   7 hadoop hadoop     4096 May  5 11:35 elasticsearch-2.4.3
lrwxrwxrwx   1 hadoop hadoop       22 May  5 12:44 filebeat -> filebeat-1.3.1-x86_64/
drwxr-xr-x   2 hadoop hadoop     4096 May  5 12:47 filebeat-1.3.1-x86_64
lrwxrwxrwx   1 hadoop hadoop       32 May  5 09:31 flume -> apache-flume-1.6.0-cdh5.5.4-bin/
lrwxrwxrwx.  1 hadoop hadoop       21 May  4 20:59 hadoop -> hadoop-2.6.0-cdh5.5.4
drwxr-xr-x. 15 hadoop hadoop     4096 May  4 21:14 hadoop-2.6.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop       20 May  4 21:48 hbase -> hbase-1.0.0-cdh5.5.4
drwxr-xr-x. 27 hadoop hadoop     4096 May  4 22:05 hbase-1.0.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop       20 May  4 22:37 hive -> hive-1.1.0-cdh5.5.4/
drwxr-xr-x. 10 hadoop hadoop     4096 Apr 26  2016 hive-1.1.0-cdh5.5.4
-rw-r--r--   1 hadoop hadoop 72594458 May  4 00:14 hue-3.9.0-cdh5.5.4.tar.gz
lrwxrwxrwx.  1 hadoop hadoop       11 May  4 20:34 jdk -> jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop     4096 Apr 11  2015 jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop     4096 Aug  5  2015 jdk1.8.0_60
lrwxrwxrwx.  1 hadoop hadoop       19 May  4 22:49 kafka -> kafka_2.11-0.8.2.2/
drwxr-xr-x.  6 hadoop hadoop     4096 May  4 22:57 kafka_2.11-0.8.2.2
lrwxrwxrwx   1 hadoop hadoop       26 May  5 19:03 kibana -> kibana-4.6.3-linux-x86_64/
drwxrwxr-x  11 hadoop hadoop     4096 Nov  4 23:24 kibana-4.6.3-linux-x86_64
lrwxrwxrwx   1 hadoop hadoop       15 May  5 14:44 logstash -> logstash-2.4.1/
drwxrwxr-x   5 hadoop hadoop     4096 May  5 14:44 logstash-2.4.1
lrwxrwxrwx   1 hadoop hadoop       12 May  5 09:05 scala -> scala-2.11.8
drwxrwxr-x   6 hadoop hadoop     4096 Mar  4  2016 scala-2.11.8
lrwxrwxrwx   1 hadoop hadoop       25 May  5 09:05 spark -> spark-2.1.0-bin-hadoop2.6
drwxr-xr-x  14 hadoop hadoop     4096 May  5 09:20 spark-2.1.0-bin-hadoop2.6
lrwxrwxrwx   1 hadoop hadoop       21 May  5 09:49 sqoop -> sqoop-1.4.6-cdh5.5.4/
drwxr-xr-x  10 hadoop hadoop     4096 Apr 26  2016 sqoop-1.4.6-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop       25 May  4 20:44 zookeeper -> zookeeper-3.4.5-cdh5.5.4/
drwxr-xr-x. 16 hadoop hadoop     4096 May  4 20:52 zookeeper-3.4.5-cdh5.5.4
[hadoop@bigdatamaster app]$ 

 

 

 

   解压

[hadoop@bigdatamaster app]$ ll
total 70956
drwxr-xr-x   8 hadoop hadoop     4096 Apr 26  2016 apache-flume-1.6.0-cdh5.5.4-bin
lrwxrwxrwx   1 hadoop hadoop       19 May  5 11:15 elasticsearch -> elasticsearch-2.4.3
drwxrwxr-x   7 hadoop hadoop     4096 May  5 11:35 elasticsearch-2.4.3
lrwxrwxrwx   1 hadoop hadoop       22 May  5 12:44 filebeat -> filebeat-1.3.1-x86_64/
drwxr-xr-x   2 hadoop hadoop     4096 May  5 12:47 filebeat-1.3.1-x86_64
lrwxrwxrwx   1 hadoop hadoop       32 May  5 09:31 flume -> apache-flume-1.6.0-cdh5.5.4-bin/
lrwxrwxrwx.  1 hadoop hadoop       21 May  4 20:59 hadoop -> hadoop-2.6.0-cdh5.5.4
drwxr-xr-x. 15 hadoop hadoop     4096 May  4 21:14 hadoop-2.6.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop       20 May  4 21:48 hbase -> hbase-1.0.0-cdh5.5.4
drwxr-xr-x. 27 hadoop hadoop     4096 May  4 22:05 hbase-1.0.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop       20 May  4 22:37 hive -> hive-1.1.0-cdh5.5.4/
drwxr-xr-x. 10 hadoop hadoop     4096 Apr 26  2016 hive-1.1.0-cdh5.5.4
-rw-r--r--   1 hadoop hadoop 72594458 May  4 00:14 hue-3.9.0-cdh5.5.4.tar.gz
lrwxrwxrwx.  1 hadoop hadoop       11 May  4 20:34 jdk -> jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop     4096 Apr 11  2015 jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop     4096 Aug  5  2015 jdk1.8.0_60
lrwxrwxrwx.  1 hadoop hadoop       19 May  4 22:49 kafka -> kafka_2.11-0.8.2.2/
drwxr-xr-x.  6 hadoop hadoop     4096 May  4 22:57 kafka_2.11-0.8.2.2
lrwxrwxrwx   1 hadoop hadoop       26 May  5 19:03 kibana -> kibana-4.6.3-linux-x86_64/
drwxrwxr-x  11 hadoop hadoop     4096 Nov  4 23:24 kibana-4.6.3-linux-x86_64
lrwxrwxrwx   1 hadoop hadoop       15 May  5 14:44 logstash -> logstash-2.4.1/
drwxrwxr-x   5 hadoop hadoop     4096 May  5 14:44 logstash-2.4.1
lrwxrwxrwx   1 hadoop hadoop       12 May  5 09:05 scala -> scala-2.11.8
drwxrwxr-x   6 hadoop hadoop     4096 Mar  4  2016 scala-2.11.8
lrwxrwxrwx   1 hadoop hadoop       25 May  5 09:05 spark -> spark-2.1.0-bin-hadoop2.6
drwxr-xr-x  14 hadoop hadoop     4096 May  5 09:20 spark-2.1.0-bin-hadoop2.6
lrwxrwxrwx   1 hadoop hadoop       21 May  5 09:49 sqoop -> sqoop-1.4.6-cdh5.5.4/
drwxr-xr-x  10 hadoop hadoop     4096 Apr 26  2016 sqoop-1.4.6-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop       25 May  4 20:44 zookeeper -> zookeeper-3.4.5-cdh5.5.4/
drwxr-xr-x. 16 hadoop hadoop     4096 May  4 20:52 zookeeper-3.4.5-cdh5.5.4
[hadoop@bigdatamaster app]$ tar -zxvf hue-3.9.0-cdh5.5.4.tar.gz 

 

 

 

 

total 70960
drwxr-xr-x   8 hadoop hadoop     4096 Apr 26  2016 apache-flume-1.6.0-cdh5.5.4-bin
lrwxrwxrwx   1 hadoop hadoop       19 May  5 11:15 elasticsearch -> elasticsearch-2.4.3
drwxrwxr-x   7 hadoop hadoop     4096 May  5 11:35 elasticsearch-2.4.3
lrwxrwxrwx   1 hadoop hadoop       22 May  5 12:44 filebeat -> filebeat-1.3.1-x86_64/
drwxr-xr-x   2 hadoop hadoop     4096 May  5 12:47 filebeat-1.3.1-x86_64
lrwxrwxrwx   1 hadoop hadoop       32 May  5 09:31 flume -> apache-flume-1.6.0-cdh5.5.4-bin/
lrwxrwxrwx.  1 hadoop hadoop       21 May  4 20:59 hadoop -> hadoop-2.6.0-cdh5.5.4
drwxr-xr-x. 15 hadoop hadoop     4096 May  4 21:14 hadoop-2.6.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop       20 May  4 21:48 hbase -> hbase-1.0.0-cdh5.5.4
drwxr-xr-x. 27 hadoop hadoop     4096 May  4 22:05 hbase-1.0.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop       20 May  4 22:37 hive -> hive-1.1.0-cdh5.5.4/
drwxr-xr-x. 10 hadoop hadoop     4096 Apr 26  2016 hive-1.1.0-cdh5.5.4
drwxr-xr-x   9 hadoop hadoop     4096 Apr 26  2016 hue-3.9.0-cdh5.5.4
-rw-r--r--   1 hadoop hadoop 72594458 May  4 00:14 hue-3.9.0-cdh5.5.4.tar.gz
lrwxrwxrwx.  1 hadoop hadoop       11 May  4 20:34 jdk -> jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop     4096 Apr 11  2015 jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop     4096 Aug  5  2015 jdk1.8.0_60
lrwxrwxrwx.  1 hadoop hadoop       19 May  4 22:49 kafka -> kafka_2.11-0.8.2.2/
drwxr-xr-x.  6 hadoop hadoop     4096 May  4 22:57 kafka_2.11-0.8.2.2
lrwxrwxrwx   1 hadoop hadoop       26 May  5 19:03 kibana -> kibana-4.6.3-linux-x86_64/
drwxrwxr-x  11 hadoop hadoop     4096 Nov  4 23:24 kibana-4.6.3-linux-x86_64
lrwxrwxrwx   1 hadoop hadoop       15 May  5 14:44 logstash -> logstash-2.4.1/
drwxrwxr-x   5 hadoop hadoop     4096 May  5 14:44 logstash-2.4.1
lrwxrwxrwx   1 hadoop hadoop       12 May  5 09:05 scala -> scala-2.11.8
drwxrwxr-x   6 hadoop hadoop     4096 Mar  4  2016 scala-2.11.8
lrwxrwxrwx   1 hadoop hadoop       25 May  5 09:05 spark -> spark-2.1.0-bin-hadoop2.6
drwxr-xr-x  14 hadoop hadoop     4096 May  5 09:20 spark-2.1.0-bin-hadoop2.6
lrwxrwxrwx   1 hadoop hadoop       21 May  5 09:49 sqoop -> sqoop-1.4.6-cdh5.5.4/
drwxr-xr-x  10 hadoop hadoop     4096 Apr 26  2016 sqoop-1.4.6-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop       25 May  4 20:44 zookeeper -> zookeeper-3.4.5-cdh5.5.4/
drwxr-xr-x. 16 hadoop hadoop     4096 May  4 20:52 zookeeper-3.4.5-cdh5.5.4
[hadoop@bigdatamaster app]$ rm hue-3.9.0-cdh5.5.4.tar.gz 

 

 

 

   创建软链接

[hadoop@bigdatamaster app]$ ll
total 64
drwxr-xr-x   8 hadoop hadoop 4096 Apr 26  2016 apache-flume-1.6.0-cdh5.5.4-bin
lrwxrwxrwx   1 hadoop hadoop   19 May  5 11:15 elasticsearch -> elasticsearch-2.4.3
drwxrwxr-x   7 hadoop hadoop 4096 May  5 11:35 elasticsearch-2.4.3
lrwxrwxrwx   1 hadoop hadoop   22 May  5 12:44 filebeat -> filebeat-1.3.1-x86_64/
drwxr-xr-x   2 hadoop hadoop 4096 May  5 12:47 filebeat-1.3.1-x86_64
lrwxrwxrwx   1 hadoop hadoop   32 May  5 09:31 flume -> apache-flume-1.6.0-cdh5.5.4-bin/
lrwxrwxrwx.  1 hadoop hadoop   21 May  4 20:59 hadoop -> hadoop-2.6.0-cdh5.5.4
drwxr-xr-x. 15 hadoop hadoop 4096 May  4 21:14 hadoop-2.6.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   20 May  4 21:48 hbase -> hbase-1.0.0-cdh5.5.4
drwxr-xr-x. 27 hadoop hadoop 4096 May  4 22:05 hbase-1.0.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   20 May  4 22:37 hive -> hive-1.1.0-cdh5.5.4/
drwxr-xr-x. 10 hadoop hadoop 4096 Apr 26  2016 hive-1.1.0-cdh5.5.4
drwxr-xr-x   9 hadoop hadoop 4096 Apr 26  2016 hue-3.9.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   11 May  4 20:34 jdk -> jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop 4096 Apr 11  2015 jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop 4096 Aug  5  2015 jdk1.8.0_60
lrwxrwxrwx.  1 hadoop hadoop   19 May  4 22:49 kafka -> kafka_2.11-0.8.2.2/
drwxr-xr-x.  6 hadoop hadoop 4096 May  4 22:57 kafka_2.11-0.8.2.2
lrwxrwxrwx   1 hadoop hadoop   26 May  5 19:03 kibana -> kibana-4.6.3-linux-x86_64/
drwxrwxr-x  11 hadoop hadoop 4096 Nov  4 23:24 kibana-4.6.3-linux-x86_64
lrwxrwxrwx   1 hadoop hadoop   15 May  5 14:44 logstash -> logstash-2.4.1/
drwxrwxr-x   5 hadoop hadoop 4096 May  5 14:44 logstash-2.4.1
lrwxrwxrwx   1 hadoop hadoop   12 May  5 09:05 scala -> scala-2.11.8
drwxrwxr-x   6 hadoop hadoop 4096 Mar  4  2016 scala-2.11.8
lrwxrwxrwx   1 hadoop hadoop   25 May  5 09:05 spark -> spark-2.1.0-bin-hadoop2.6
drwxr-xr-x  14 hadoop hadoop 4096 May  5 09:20 spark-2.1.0-bin-hadoop2.6
lrwxrwxrwx   1 hadoop hadoop   21 May  5 09:49 sqoop -> sqoop-1.4.6-cdh5.5.4/
drwxr-xr-x  10 hadoop hadoop 4096 Apr 26  2016 sqoop-1.4.6-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   25 May  4 20:44 zookeeper -> zookeeper-3.4.5-cdh5.5.4/
drwxr-xr-x. 16 hadoop hadoop 4096 May  4 20:52 zookeeper-3.4.5-cdh5.5.4
[hadoop@bigdatamaster app]$ ln -s hue-3.9.0-cdh5.5.4/ hue
[hadoop@bigdatamaster app]$ ll
total 64
drwxr-xr-x   8 hadoop hadoop 4096 Apr 26  2016 apache-flume-1.6.0-cdh5.5.4-bin
lrwxrwxrwx   1 hadoop hadoop   19 May  5 11:15 elasticsearch -> elasticsearch-2.4.3
drwxrwxr-x   7 hadoop hadoop 4096 May  5 11:35 elasticsearch-2.4.3
lrwxrwxrwx   1 hadoop hadoop   22 May  5 12:44 filebeat -> filebeat-1.3.1-x86_64/
drwxr-xr-x   2 hadoop hadoop 4096 May  5 12:47 filebeat-1.3.1-x86_64
lrwxrwxrwx   1 hadoop hadoop   32 May  5 09:31 flume -> apache-flume-1.6.0-cdh5.5.4-bin/
lrwxrwxrwx.  1 hadoop hadoop   21 May  4 20:59 hadoop -> hadoop-2.6.0-cdh5.5.4
drwxr-xr-x. 15 hadoop hadoop 4096 May  4 21:14 hadoop-2.6.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   20 May  4 21:48 hbase -> hbase-1.0.0-cdh5.5.4
drwxr-xr-x. 27 hadoop hadoop 4096 May  4 22:05 hbase-1.0.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   20 May  4 22:37 hive -> hive-1.1.0-cdh5.5.4/
drwxr-xr-x. 10 hadoop hadoop 4096 Apr 26  2016 hive-1.1.0-cdh5.5.4
lrwxrwxrwx   1 hadoop hadoop   19 May  5 20:44 hue -> hue-3.9.0-cdh5.5.4/
drwxr-xr-x   9 hadoop hadoop 4096 Apr 26  2016 hue-3.9.0-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   11 May  4 20:34 jdk -> jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop 4096 Apr 11  2015 jdk1.7.0_79
drwxr-xr-x.  8 hadoop hadoop 4096 Aug  5  2015 jdk1.8.0_60
lrwxrwxrwx.  1 hadoop hadoop   19 May  4 22:49 kafka -> kafka_2.11-0.8.2.2/
drwxr-xr-x.  6 hadoop hadoop 4096 May  4 22:57 kafka_2.11-0.8.2.2
lrwxrwxrwx   1 hadoop hadoop   26 May  5 19:03 kibana -> kibana-4.6.3-linux-x86_64/
drwxrwxr-x  11 hadoop hadoop 4096 Nov  4 23:24 kibana-4.6.3-linux-x86_64
lrwxrwxrwx   1 hadoop hadoop   15 May  5 14:44 logstash -> logstash-2.4.1/
drwxrwxr-x   5 hadoop hadoop 4096 May  5 14:44 logstash-2.4.1
lrwxrwxrwx   1 hadoop hadoop   12 May  5 09:05 scala -> scala-2.11.8
drwxrwxr-x   6 hadoop hadoop 4096 Mar  4  2016 scala-2.11.8
lrwxrwxrwx   1 hadoop hadoop   25 May  5 09:05 spark -> spark-2.1.0-bin-hadoop2.6
drwxr-xr-x  14 hadoop hadoop 4096 May  5 09:20 spark-2.1.0-bin-hadoop2.6
lrwxrwxrwx   1 hadoop hadoop   21 May  5 09:49 sqoop -> sqoop-1.4.6-cdh5.5.4/
drwxr-xr-x  10 hadoop hadoop 4096 Apr 26  2016 sqoop-1.4.6-cdh5.5.4
lrwxrwxrwx.  1 hadoop hadoop   25 May  4 20:44 zookeeper -> zookeeper-3.4.5-cdh5.5.4/
drwxr-xr-x. 16 hadoop hadoop 4096 May  4 20:52 zookeeper-3.4.5-cdh5.5.4
[hadoop@bigdatamaster app]$ 

 

 

 

 

   进入hue的安装目录,进行编译。

make apps

  看个人的网速吧,这个过程中,需要几分钟。

 

 

 

   为什么需要make apps,其实啊,是为了得到如下

 

 

 

 

 

 

 

 

 

 


    首先,大家一应要看清我的3个节点的集群机器情况!(不看清楚,自己去后悔吧)

 

 

 

 

        (这个配置文件表格,我是为了给大家方便看,制作出来展示,是根据大家的机器变动而走的)(动态的

Hue配置段 Hue配置项 Hue配置值 说明
desktop default_hdfs_superuser hadoop HDFS管理用户
desktop http_host 192.168.80.10 Hue Web Server所在主机/IP
desktop http_port 8000 Hue Web Server服务端口
desktop server_user hue 运行Hue Web Server的进程用户
desktop server_group hue 运行Hue Web Server的进程用户组
desktop default_user hue Hue管理员
desktop default_hdfs_superuser hadoop 

更改为你的hadoop用户,网上有些资料写为什么将

修改 文件desktop/libs/hadoop/src/hadoop/fs/webhdfs.py 中的  DEFAULT_HDFS_SUPERUSER = ‘hdfs’  更改为你的hadoop用户。

 

我的这里是hadoop

 

修改默认的hdfs访问用户

修改hue.ini中的配置

default_hdfs_superuser=hdfs

改为

default_hdfs_superuser=root (注意,这里别人的用户是root)

hadoop/hdfs_clusters fs_defaultfs hdfs://bigdatamaster:9000 对应core-site.xml配置项fs.defaultFS
hadoop/hdfs_clusters hadoop_conf_dir /home/hadoop/app/hadoop/etc/hadoop/conf Hadoop配置文件目录
hadoop/yarn_clusters resourcemanager_host bigdatamaster 对应yarn-site.xml配置项yarn.resourcemanager.hostname
hadoop/yarn_clusters resourcemanager_port 8032 ResourceManager服务端口号
hadoop/yarn_clusters resourcemanager_api_url http://bigdatamaster:23188 对应于yarn-site.xml配置项yarn.resourcemanager.webapp.address(我这里是为了避免跟spark那边的端口冲突,当然你也可以改为其他的端口)
hadoop/yarn_clusters proxy_api_url http://bigdatamaster:8888 对应yarn-site.xml配置项yarn.web-proxy.address
hadoop/yarn_clusters history_server_api_url http://bigdatamaster:19888

对应mapred-site.xml配置项mapreduce.jobhistory.webapp.address

zookeeper
host_ports
bigdatamaster:2181,bigdataslave1:2181,bigdataslave2:2181

zookeeper集群管理

beeswax hive_server_host bigdatamaster Hive所在节点主机名/IP
beeswax hive_server_port 10000 HiveServer2服务端口号

beeswax

hive_conf_dir
home/hadoop/app/hive/conf

Hive配置文件目录

 

     因为,我的Hue仅只安装在bigdatamaster(192.168.80.10)这台机器上即可!!!

 

 

 

 

 

 

 

   配置hue文件(重点,一定要细心)

 $HUE_HOME/desktop/conf/hue.ini

[hadoop@bigdatamaster conf]$ pwd
/home/hadoop/app/hue/desktop/conf
[hadoop@bigdatamaster conf]$ ll
total 52
-rw-r--r-- 1 hadoop hadoop 41572 Apr 26  2016 hue.ini
-rw-r--r-- 1 hadoop hadoop  1843 Apr 26  2016 log4j.properties
-rw-r--r-- 1 hadoop hadoop  1721 Apr 26  2016 log.conf
[hadoop@bigdatamaster conf]$ vim hue.ini 

 

 

 

 

 

 

 

 

http://archive.cloudera.com/cdh5/cdh/5/hue-3.9.0-cdh5.5.4/manual.html#_install_hue
[desktop]这块,配置如下

 



[desktop]
   # hue webServer 地址和端口号
   secret_key= secret_key=jFE93j;2[290-eiw.KEiwN2s3['d;/.q[eIW^y#e=+Iei*@Mn<qW5o

   http_host=192.168.80.10
   http_port=8888

   time_zone=Asia/Shanghai


# Webserver runs
as this user server_user=hue server_group=hue # This should be the Hue admin and proxy user default_user=hue # This should be the hadoop cluster admin default_hdfs_superuser=hadoop

 

 

 

   注意,这里也可以不弄,保持默认的

 

 

 

 

 

 

 

 

 

http://archive.cloudera.com/cdh5/cdh/5/hue-3.9.0-cdh5.5.4/manual.html#_install_hue
[hadoop]这块,配置如下  (注意官网说,WebHdfs  或者  HttpFS)(一般用WebHdfs,那是因为非HA集群。如果是HA集群,则必须还要配置HttpFS


  下面这篇博客,我给了具体的配置和原因。

HUE配置文件hue.ini 的hdfs_clusters模块详解(图文详解)(分HA集群)

 

  好的,我们继续往下。因为本博客立足于是由bigdatamaster、bigdataslave1和bigdataslave2组成的非HA的3节点集群,所以选择WebHdfs。

  bigdataslave1 和 bigdataslave2都操作,不多赘述。

 

 

 

   然后,修改完三台机器的hdfs-site.xml之后,再修改core-site.xml 

  bigdataslave1和bigdataslave2都操作,不多赘述。

 

 

 

 

 

 

 

 

 

 hadoop模块

[hadoop]

  # Configuration for HDFS NameNode
  # ------------------------------------------------------------------------
  [[hdfs_clusters]]
    # HA support by using HttpFs

    [[[default]]]
      # Enter the filesystem uri
      fs_defaultfs=hdfs://bigdatamaster:9000

      # NameNode logical name.
      ## logical_name=

      # Use WebHdfs/HttpFs as the communication mechanism.
      # Domain should be the NameNode or HttpFs host.
      # Default port is 14000 for HttpFs.
      webhdfs_url=http://bigdatamaster:50070/webhdfs/v1

      # Change this if your HDFS cluster is Kerberos-secured
      ## security_enabled=false

      # In secure mode (HTTPS), if SSL certificates from YARN Rest APIs
      # have to be verified against certificate authority
      ## ssl_cert_ca_verify=True

      # Directory of the Hadoop configuration
      hadoop_conf_dir=/home/hadoop/app/hadoop/etc/hadoop/conf

 

  注意,我的 fs_defaultfs=hdfs://bigdatamaster:9000 ,大家要根据自己的机器来配置,思路一定要清晰,别一味地看别人博客怎么配置的

网上有些如, fs_defaultfs=hdfs://mycluster ,以及 fs_defaultfs=hdfs://master:8020。注意,这是别人的机器是这么配置的。

  总之,跟自己机器的core-site.xml的fs.defaultFS属性保持一致即可。

  其中,bigdatamaster,是我安装Hue这台机器的主机名,192.168.80.10是它对应的静态ip。

 

 

 

 

   那么,为什么是上面这样来配置的呢。大家要知道为什么

http://hadoop.apache.org/docs/r2.5.2/

 

 

 

 

 

 

 

 

 

 

[yarn_clusters]这块
 [[yarn_clusters]]

    [[[default]]]
      # Enter the host on which you are running the ResourceManager
      resourcemanager_host=192.168.80.10

      # The port where the ResourceManager IPC listens on
      resourcemanager_port=8032

      # Whether to submit jobs to this cluster
      submit_to=True

      # Resource Manager logical name (required for HA)
      ## logical_name=

      # Change this if your YARN cluster is Kerberos-secured
      ## security_enabled=false

      # URL of the ResourceManager API
      resourcemanager_api_url=http://192.168.80.10:8088

      # URL of the ProxyServer API
      proxy_api_url=http://192.168.80.10:8088

      # URL of the HistoryServer API
      history_server_api_url=http://192.168.80.10:19888

 

 

   进一步深入的话,请移步我的博客

HUE配置文件hue.ini 的yarn_clusters模块详解(图文详解)(分HA集群)

 

 

 

 

 

 

 

[zookeeper]这块
[zookeeper]
host_ports=bigdatamaster:2181,bigdataslave1:2181,bigdataslave2:2181

 

 

 

 

 

 

 

[beeswax] 和 hive 这块



[beeswax]

  # Host where HiveServer2 is running.
  # If Kerberos security is enabled, use fully-qualified domain name (FQDN).
  hive_server_host=bigdatamaster

  # Port where HiveServer2 Thrift server runs on.
  hive_server_port=10000

  # Hive configuration directory, where hive-site.xml is located
  hive_conf_dir=/home/hadoop/app/hive/conf

  因为,我的hive是安装在bigdatamaster这台机器上。大家一定要根据自己的机器情况来配置啊!

 

 

复制代码
        <property>
                <name>hive.server2.thrift.port</name>
                <value>10000</value>
        </property>
        <property>
                <name>hive.server2.thrift.bind.host</name>
                <value>bigdatamaster</value>
        </property>
复制代码

 

 

 

  同时,是还要将hive-site.xml里的hive.server2.thrift.port属性 和 hive.server2.thrift.bind.host属性。我这里的hive是安装在bigdatamaster机器上。

  更深入,想请请见

HUE配置文件hue.ini 的hive和beeswax模块详解(图文详解)(分HA集群)

 

 

 

 

 

 

 database模块

HUE配置文件hue.ini 的database模块详解(包含qlite、mysql、 psql、和oracle)(图文详解)(分HA集群)

###########################################################################
# Settings for the RDBMS application
###########################################################################

[librdbms]
  # The RDBMS app can have any number of databases configured in the databases
  # section. A database is known by its section name
  # (IE sqlite, mysql, psql, and oracle in the list below).

  [[databases]]
    # sqlite configuration.
    [[[sqlite]]]
      # Name to show in the UI.
      nice_name=SQLite

      # For SQLite, name defines the path to the database.
      name=/home/hadoop/app/hue/desktop/desktop.db

      # Database backend to use.
      engine=sqlite

 

 

 

 

 

hive> show databases;
OK
default
hive
Time taken: 0.074 seconds, Fetched: 2 row(s)
hive> 

 

 

 

 

    # mysql, oracle, or postgresql configuration.
    [[[mysql]]]
      # Name to show in the UI.
      nice_name="My SQL DB"

      # For MySQL and PostgreSQL, name is the name of the database.
      # For Oracle, Name is instance of the Oracle server. For express edition
      # this is 'xe' by default.
      name=hive

      # Database backend to use. This can be:
      # 1. mysql
      # 2. postgresql
      # 3. oracle
      engine=mysql

      # IP or hostname of the database to connect to.
      host=bigdatamaster

      # Port the database server is listening to. Defaults are:
      # 1. MySQL: 3306
      # 2. PostgreSQL: 5432
      # 3. Oracle Express Edition: 1521
      port=3306

      # Username to authenticate with when connecting to the database.
      user=hive

      # Password matching the username to authenticate with when
      # connecting to the database.
      password=hive

      # Database options to send to the server when connecting.
      # https://docs.djangoproject.com/en/1.4/ref/databases/
      ## options={}

 

 

 

pig模块的配置

  具体,见

HUE配置文件hue.ini 的pig模块详解(图文详解)(分HA集群)

 

 

zookeeper模块的配置

  具体,见

HUE配置文件hue.ini 的zookeeper模块详解(图文详解)(分HA集群)

 

 

 

 

 

spark模块的配置

   具体,见

HUE配置文件hue.ini 的Spark模块详解(图文详解)(分HA集群)

 

 

 

impala模块的配置

   具体请见

HUE配置文件hue.ini 的impala模块详解(图文详解)(分HA集群)

 

 

 

liboozie和oozie模块的配置

  具体,见

HUE配置文件hue.ini 的liboozie和oozie模块详解(图文详解)(分HA集群)

 

 

sqoop模块的配置

  具体,见

HUE配置文件hue.ini 的sqoop模块详解(图文详解)(分HA集群)

 

 

hbase模块的配置(暂时这里遇到了点问题)

   1、配置HBase

  Hue需要读取HBase的数据是使用thrift的方式,默认HBase的thrift服务没有开启,所有需要手动额外开启thrift 服务。 
thrift service默认使用的是9090端口,使用如下命令查看端口是否被占用。

[hadoop@bigdatamaster conf]$ netstat -nl|grep 9090
[hadoop@bigdatamaster conf]$ 

  这里,最好保持默认端口。

 

     对于Hbase的配置,有点错误。

HUE配置文件hue.ini 的hbase模块详解(图文详解)(分HA集群)

 

 

 

 

 

 

 

 

 

Hue的启动

  也就是说,你Hue配置文件里面配置了什么,进程都要先提前启动。

build/env/bin/supervisor

 

[hadoop@bigdatamaster hue]$ pwd
/home/hadoop/app/hue
[hadoop@bigdatamaster hue]$ ll
total 92
-rw-rw-r--  1 hadoop hadoop  2782 May  5 21:03 app.reg
drwxr-xr-x 22 hadoop hadoop  4096 May  5 21:03 apps
drwxrwxr-x  4 hadoop hadoop  4096 May  5 21:03 build
drwxr-xr-x  3 hadoop hadoop  4096 Apr 26  2016 cloudera
drwxr-xr-x  6 hadoop hadoop  4096 May  7 10:13 desktop
drwxr-xr-x  6 hadoop hadoop  4096 Apr 26  2016 docs
drwxr-xr-x  3 hadoop hadoop  4096 Apr 26  2016 ext
-rw-r--r--  1 hadoop hadoop 11358 Apr 26  2016 LICENSE.txt
drwxrwxr-x  2 hadoop hadoop  4096 May  7 09:27 logs
-rw-r--r--  1 hadoop hadoop  4742 Apr 26  2016 Makefile
-rw-r--r--  1 hadoop hadoop  8505 Apr 26  2016 Makefile.sdk
-rw-r--r--  1 hadoop hadoop  3531 Apr 26  2016 Makefile.vars
-rw-r--r--  1 hadoop hadoop  2192 Apr 26  2016 Makefile.vars.priv
drwxr-xr-x  2 hadoop hadoop  4096 Apr 26  2016 maven
-rw-r--r--  1 hadoop hadoop   801 Apr 26  2016 NOTICE.txt
-rw-r--r--  1 hadoop hadoop  1305 Apr 26  2016 README
drwxr-xr-x  5 hadoop hadoop  4096 Apr 26  2016 tools
-rw-r--r--  1 hadoop hadoop   932 Apr 26  2016 VERSION
[hadoop@bigdatamaster hue]$ build/env/bin/supervisor

 

[hadoop@bigdatamaster hue]$ build/env/bin/supervisor
[INFO] Not running as root, skipping privilege drop
starting server with options:
{'daemonize': False,
 'host': '192.168.80.10',
 'pidfile': None,
 'port': 8888,
 'server_group': 'hue',
 'server_name': 'localhost',
 'server_user': 'hue',
 'ssl_certificate': None,
 'ssl_certificate_chain': None,
 'ssl_cipher_list': 'ECDHE-RSA-AES128-GCM-SHA256:ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES256-GCM-SHA384:ECDHE-ECDSA-AES256-GCM-SHA384:DHE-RSA-AES128-GCM-SHA256:DHE-DSS-AES128-GCM-SHA256:kEDH+AESGCM:ECDHE-RSA-AES128-SHA256:ECDHE-ECDSA-AES128-SHA256:ECDHE-RSA-AES128-SHA:ECDHE-ECDSA-AES128-SHA:ECDHE-RSA-AES256-SHA384:ECDHE-ECDSA-AES256-SHA384:ECDHE-RSA-AES256-SHA:ECDHE-ECDSA-AES256-SHA:DHE-RSA-AES128-SHA256:DHE-RSA-AES128-SHA:DHE-DSS-AES128-SHA256:DHE-RSA-AES256-SHA256:DHE-DSS-AES256-SHA:DHE-RSA-AES256-SHA:AES128-GCM-SHA256:AES256-GCM-SHA384:AES128-SHA256:AES256-SHA256:AES128-SHA:AES256-SHA:AES:CAMELLIA:DES-CBC3-SHA:!aNULL:!eNULL:!EXPORT:!DES:!RC4:!MD5:!PSK:!aECDH:!EDH-DSS-DES-CBC3-SHA:!EDH-RSA-DES-CBC3-SHA:!KRB5-DES-CBC3-SHA',
 'ssl_private_key': None,
 'threads': 40,
 'workdir': None}
/home/hadoop/app/hue-3.9.0-cdh5.5.4/build/env/lib/python2.6/site-packages/django_axes-1.4.0-py2.6.egg/axes/decorators.py:210: DeprecationWarning: The use of AUTH_PROFILE_MODULE to define user profiles has been deprecated.
  profile = user.get_profile()

 

 

 

 

 

 

http://bigdatamaster:8888

  这里,不多赘述了。

   

 

 

 

   如果大家,在启动Hue之后,遇到一些问题,相应可以去看我以下写的博客

安装Hue后的一些功能的问题解决干货总结(博主推荐)

 

 

 

 

 

 

 

 

 

 

 

 

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posted @ 2017-05-03 23:22  大数据和AI躺过的坑  阅读(5997)  评论(0编辑  收藏  举报