hadoop-2.7.3.tar.gz + spark-2.0.2-bin-hadoop2.7.tgz + zeppelin-0.6.2-incubating-bin-all.tgz（master、slave1和slave2）（博主推荐）（图文详解）

　　我这里，采取的是ubuntu 16.04系统，当然大家也可以在CentOS6.5里，这些都是小事

CentOS 6.5的安装详解

hadoop-2.6.0.tar.gz + spark-1.5.2-bin-hadoop2.6.tgz的集群搭建（单节点）（Ubuntu系统）

 

大数据搭建各个子项目时配置文件技巧（适合CentOS和Ubuntu系统）（博主推荐）

新建用户组、用户、用户密码、删除用户组、用户（适合CentOS、Ubuntu系统）

VMware里Ubuntu-16.04-desktop的VMware Tools安装图文详解

Ubuntukylin-14.04-desktop（ 不带分区）安装步骤详解 

Ubuntu14.04安装之后的一些配置 

Ubuntu11.10 带图形安装步骤详解

Ubuntukylin-14.04-desktop（带分区）安装步骤详解

Ubuntu各版本的历史发行界面

Spark on YARN模式的安装（spark-1.6.1-bin-hadoop2.6.tgz + hadoop-2.6.0.tar.gz）（master、slave1和slave2）（博主推荐）

Spark standalone模式的安装（spark-1.6.1-bin-hadoop2.6.tgz）（master、slave1和slave2）

　　我这里，采取的是Ubuntu 16.04 ，而且Spark on YARN模式

Spark on YARN模式的安装（spark-1.6.1-bin-hadoop2.6.tgz + hadoop-2.6.0.tar.gz）（master、slave1和slave2）（博主推荐）

hadoop-2.6.0.tar.gz + spark-1.5.2-bin-hadoop2.6.tgz的集群搭建（单节点）（Ubuntu系统）

 

 

　　系统配置文件

#jdk
export JAVA_HOME=/home/spark/app/jdk
export JRE_HOME=$JAVA_HOME/jre
export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib
export PATH=$PATH:$JAVA_HOME/bin


#scala
export SCALA_HOME=/home/spark/app/scala
export PATH=$PATH:$SCALA_HOME/bin



#hadoop
export HADOOP_HOME=/home/spark/app/hadoop
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin


#spark
export SPARK_HOME=/home/spark/app/spark
export PATH=$PATH:$SPARK_HOME/bin:$SPARK_HOME/sbin


#zookeeper
export ZOOKEEPER_HOME=/home/spark/app/zookeeper
export PATH=$PATH:$ZOOKEEPER_HOME/bin


#zeppelin
export ZEPPELIN_HOME=/home/spark/app/zeppelin
export PATH=$PATH:$ZEPPELIN_HOME_HOME/bin

　　我的路径是在/home/spark/app下

Hadoop的配置文件

 core-site.xml

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License. See accompanying LICENSE file.
-->

<!-- Put site-specific property overrides in this file. -->

<configuration>
        <property>
                <name>fs.defaultFS</name>
                <value>hdfs://master:9000</value>
        </property>
        <property>
        　      <name>io.file.buffer.size</name>
        　      <value>131072</value>
        </property>
        <property>
        　      <name>hadoop.tmp.dir</name>
        　      <value>/usr/local/hadoop/hadoop-2.7.3/tmp</value>
        </property>
        <property>
        　　    <name>hadoop.proxyuser.hadoop.hosts</name>
                <value>*</value>
        </property>
        <property>
        　　    <name>hadoop.proxyuser.hadoop.groups</name>
        　      <value>*</value>
        </property>
</configuration>

hdfs-site.xml

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License. See accompanying LICENSE file.
-->

<!-- Put site-specific property overrides in this file. -->


<configuration>
        <property>
                <name>dfs.namenode.secondary.http-address</name>
        　　    <value>master:9001</value>
        </property>
        <property>
        　　    <name>dfs.replication</name>
        　　    <value>2</value>
        </property>
        <property>
        　　    <name>dfs.namenode.name.dir</name>
        　      <value>/usr/local/hadoop/hadoop-2.7.3/dfs/name</value>
        </property>
        <property>
        　　    <name>dfs.datanode.data.dir</name>
        　　    <value>/usr/local/hadoop/hadoop-2.7.3/dfs/data</value>
        </property>
        <property>
        　　    <name>dfs.webhdfs.enabled</name>
        　　    <value>true</value>
        </property>
</configuration>

 

mapred-site.xml

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License. See accompanying LICENSE file.
-->

<!-- Put site-specific property overrides in this file. -->



<configuration>
        <property>
                <name>mapreduce.framework.name</name>
　　            <value>yarn</value>
        </property>
        <property>
　　            <name>mapreduce.jobhistory.address</name>
　　            <value>master:10020</value>
        </property>
        <property>
　　            <name>mapreduce.jobhistory.webapp.address</name>
　　            <value>master:19888</value>
        </property>
</configuration>

yarn-site.xml

<?xml version="1.0"?>
<!--
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License. See accompanying LICENSE file.
-->

<configuration>

    <property>
          <name>yarn.resourcemanager.hostname</name>
            <value>master</value>
    </property>
    <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.address</name>
    　　    <value>master:8032</value>
    </property>
    <property>
　　        <name>yarn.resourcemanager.scheduler.address</name>
　　        <value>master:8030</value>
    </property>
    <property>
　　        <name>yarn.resourcemanager.resource-tracker.address</name>
　　        <value>master:8031</value>
    </property>
    <property>
　　        <name>yarn.resourcemanager.admin.address</name>
　　        <value>master:8033</value>
    </property>
    <property>
　　        <name>yarn.resourcemanager.webapp.address</name>
　　        <value>master:8088</value>
    </property>

</configuration>

slaves

slave1
slave2

hadoop-env.sh

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# Set Hadoop-specific environment variables here.

# The only required environment variable is JAVA_HOME.  All others are
# optional.  When running a distributed configuration it is best to
# set JAVA_HOME in this file, so that it is correctly defined on
# remote nodes.

# The java implementation to use.
export JAVA_HOME=/home/spark/app/jdk


# The jsvc implementation to use. Jsvc is required to run secure datanodes
# that bind to privileged ports to provide authentication of data transfer
# protocol.  Jsvc is not required if SASL is configured for authentication of
# data transfer protocol using non-privileged ports.
#export JSVC_HOME=${JSVC_HOME}

export HADOOP_CONF_DIR=${HADOOP_CONF_DIR:-"/etc/hadoop"}

# Extra Java CLASSPATH elements.  Automatically insert capacity-scheduler.
for f in $HADOOP_HOME/contrib/capacity-scheduler/*.jar; do
  if [ "$HADOOP_CLASSPATH" ]; then
    export HADOOP_CLASSPATH=$HADOOP_CLASSPATH:$f
  else
    export HADOOP_CLASSPATH=$f
  fi
done

# The maximum amount of heap to use, in MB. Default is 1000.
#export HADOOP_HEAPSIZE=
#export HADOOP_NAMENODE_INIT_HEAPSIZE=""

# Extra Java runtime options.  Empty by default.
export HADOOP_OPTS="$HADOOP_OPTS -Djava.net.preferIPv4Stack=true"

# Command specific options appended to HADOOP_OPTS when specified
export HADOOP_NAMENODE_OPTS="-Dhadoop.security.logger=${HADOOP_SECURITY_LOGGER:-INFO,RFAS} -Dhdfs.audit.logger=${HDFS_AUDIT_LOGGER:-INFO,NullAppender} $HADOOP_NAMENODE_OPTS"
export HADOOP_DATANODE_OPTS="-Dhadoop.security.logger=ERROR,RFAS $HADOOP_DATANODE_OPTS"

export HADOOP_SECONDARYNAMENODE_OPTS="-Dhadoop.security.logger=${HADOOP_SECURITY_LOGGER:-INFO,RFAS} -Dhdfs.audit.logger=${HDFS_AUDIT_LOGGER:-INFO,NullAppender} $HADOOP_SECONDARYNAMENODE_OPTS"

export HADOOP_NFS3_OPTS="$HADOOP_NFS3_OPTS"
export HADOOP_PORTMAP_OPTS="-Xmx512m $HADOOP_PORTMAP_OPTS"

# The following applies to multiple commands (fs, dfs, fsck, distcp etc)
export HADOOP_CLIENT_OPTS="-Xmx512m $HADOOP_CLIENT_OPTS"
#HADOOP_JAVA_PLATFORM_OPTS="-XX:-UsePerfData $HADOOP_JAVA_PLATFORM_OPTS"

# On secure datanodes, user to run the datanode as after dropping privileges.
# This **MUST** be uncommented to enable secure HDFS if using privileged ports
# to provide authentication of data transfer protocol.  This **MUST NOT** be
# defined if SASL is configured for authentication of data transfer protocol
# using non-privileged ports.
export HADOOP_SECURE_DN_USER=${HADOOP_SECURE_DN_USER}

# Where log files are stored.  $HADOOP_HOME/logs by default.
#export HADOOP_LOG_DIR=${HADOOP_LOG_DIR}/$USER

# Where log files are stored in the secure data environment.
export HADOOP_SECURE_DN_LOG_DIR=${HADOOP_LOG_DIR}/${HADOOP_HDFS_USER}

###
# HDFS Mover specific parameters
###
# Specify the JVM options to be used when starting the HDFS Mover.
# These options will be appended to the options specified as HADOOP_OPTS
# and therefore may override any similar flags set in HADOOP_OPTS
#
# export HADOOP_MOVER_OPTS=""

###
# Advanced Users Only!
###

# The directory where pid files are stored. /tmp by default.
# NOTE: this should be set to a directory that can only be written to by 
#       the user that will run the hadoop daemons.  Otherwise there is the
#       potential for a symlink attack.
export HADOOP_PID_DIR=${HADOOP_PID_DIR}
export HADOOP_SECURE_DN_PID_DIR=${HADOOP_PID_DIR}

# A string representing this instance of hadoop. $USER by default.
export HADOOP_IDENT_STRING=$USER

Spark的配置文件

spark-env.sh

#!/usr/bin/env bash

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

# This file is sourced when running various Spark programs.
# Copy it as spark-env.sh and edit that to configure Spark for your site.

# Options read when launching programs locally with
# ./bin/run-example or ./bin/spark-submit
# - HADOOP_CONF_DIR, to point Spark towards Hadoop configuration files
# - SPARK_LOCAL_IP, to set the IP address Spark binds to on this node
# - SPARK_PUBLIC_DNS, to set the public dns name of the driver program
# - SPARK_CLASSPATH, default classpath entries to append

# Options read by executors and drivers running inside the cluster
# - SPARK_LOCAL_IP, to set the IP address Spark binds to on this node
# - SPARK_PUBLIC_DNS, to set the public DNS name of the driver program
# - SPARK_CLASSPATH, default classpath entries to append
# - SPARK_LOCAL_DIRS, storage directories to use on this node for shuffle and RDD data
# - MESOS_NATIVE_JAVA_LIBRARY, to point to your libmesos.so if you use Mesos

# Options read in YARN client mode
# - HADOOP_CONF_DIR, to point Spark towards Hadoop configuration files
# - SPARK_EXECUTOR_INSTANCES, Number of executors to start (Default: 2)
# - SPARK_EXECUTOR_CORES, Number of cores for the executors (Default: 1).
# - SPARK_EXECUTOR_MEMORY, Memory per Executor (e.g. 1000M, 2G) (Default: 1G)
# - SPARK_DRIVER_MEMORY, Memory for Driver (e.g. 1000M, 2G) (Default: 1G)

# Options for the daemons used in the standalone deploy mode
# - SPARK_MASTER_HOST, to bind the master to a different IP address or hostname
# - SPARK_MASTER_PORT / SPARK_MASTER_WEBUI_PORT, to use non-default ports for the master
# - SPARK_MASTER_OPTS, to set config properties only for the master (e.g. "-Dx=y")
# - SPARK_WORKER_CORES, to set the number of cores to use on this machine
# - SPARK_WORKER_MEMORY, to set how much total memory workers have to give executors (e.g. 1000m, 2g)
# - SPARK_WORKER_PORT / SPARK_WORKER_WEBUI_PORT, to use non-default ports for the worker
# - SPARK_WORKER_INSTANCES, to set the number of worker processes per node
# - SPARK_WORKER_DIR, to set the working directory of worker processes
# - SPARK_WORKER_OPTS, to set config properties only for the worker (e.g. "-Dx=y")
# - SPARK_DAEMON_MEMORY, to allocate to the master, worker and history server themselves (default: 1g).
# - SPARK_HISTORY_OPTS, to set config properties only for the history server (e.g. "-Dx=y")
# - SPARK_SHUFFLE_OPTS, to set config properties only for the external shuffle service (e.g. "-Dx=y")
# - SPARK_DAEMON_JAVA_OPTS, to set config properties for all daemons (e.g. "-Dx=y")
# - SPARK_PUBLIC_DNS, to set the public dns name of the master or workers

# Generic options for the daemons used in the standalone deploy mode
# - SPARK_CONF_DIR      Alternate conf dir. (Default: ${SPARK_HOME}/conf)
# - SPARK_LOG_DIR       Where log files are stored.  (Default: ${SPARK_HOME}/logs)
# - SPARK_PID_DIR       Where the pid file is stored. (Default: /tmp)
# - SPARK_IDENT_STRING  A string representing this instance of spark. (Default: $USER)
# - SPARK_NICENESS      The scheduling priority for daemons. (Default: 0)




export JAVA_HOME=/home/spark/app/jdk
export SCALA_HOME=/home/spark/app/scala
export HADOOP_HOME=/home/spark/app/hadoop
export HADOOP_CONF_DIR=/home/spark/app/hadoop/etc/hadoop
export SPARK_MASTER_IP=192.168.80.145
export SPARK_WORKER_MERMORY=1G

slaves

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

# A Spark Worker will be started on each of the machines listed below.

slave1
slave2

　　大家一定要去看我的前期博客。

　　下面，我是接着直接来下载并安装配置Zeppelin

　　首先一点想说的是版本问题，为什么本博文的标题我会写清楚版本号呢！原因就是版本不对真的很会坑人。

　  博主我也尝试过hadoop-2.7.3.tar.gz + spark-2.1.0-bin-hadoop2.7.tgz。

　　但是呢，对于zeppelin的版本，目前官网开发团队确实做的不太好，控制版本有待完善。

　　坑人的地方在哪里呢，Zeppelin0.6.2不支持Spark2.1.0这个版本

　　于是我又仔细的查看了官网的教程：

　　得出的结论是我必须要装老版本的，还好的是支持Spark2.0，于是我又安装了Spark2.0.2

　　不过呢如果你没有任何的集群环境，上面这篇是值得参考的，只不过你得自己改下版本号，从2.1.0到2.0.2，其他完全一样。

　　

　　当然，庆幸的是，教大家，灵活会用软连接，实现多版本的使用。

大数据各子项目的环境搭建之建立与删除软连接（博主推荐）

1、下载Zeppelin安装包

　　Apache Zeppelin官方提供了Source包和二进制包，我们可以根据需要下载相关的包进行安装。

wget http://archive.apache.org/dist/zeppelin/zeppelin-0.6.2/zeppelin-0.6.2-bin-all.tgz

或者

wget  http://ftp.meisei-u.ac.jp/mirror/apache/dist/incubator/zeppelin/0.6.2-incubating/zeppelin-0.6.2-incubating-bin-all.tgz

http://mirrors.tuna.tsinghua.edu.cn/apache/zeppelin/zeppelin-0.6.2/zeppelin-0.6.2-bin-all.tgz

　　　或者，去官网

 

　　我一般，是喜欢将软件安装在/usr/local/app下，或者/home/hadoop/app、或者/home/spark/app下

 

2、解压并为创建软连接

tar -xvf zeppelin-0.6.2-bin-all.tgz

spark@master:~/app$ pwd
/home/spark/app
spark@master:~/app$ ls
hadoop        jdk1.7.0_79  scala-2.10.5               zookeeper
hadoop-2.7.3  jdk1.8.0_60  spark                      zookeeper-3.4.6
jdk           scala        spark-2.0.2-bin-hadoop2.7
spark@master:~/app$ cp /home/zhouls/Downloads/zeppelin-0.6.2-bin-all.tgz .
spark@master:~/app$ ls
hadoop        jdk1.8.0_60   spark-2.0.2-bin-hadoop2.7
hadoop-2.7.3  scala         zeppelin-0.6.2-bin-all.tgz
jdk           scala-2.10.5  zookeeper
jdk1.7.0_79   spark         zookeeper-3.4.6
spark@master:~/app$ tar -zxvf zeppelin-0.6.2-bin-all.tgz 

 

spark@master:~/app$ ls
hadoop        jdk1.8.0_60   spark-2.0.2-bin-hadoop2.7   zookeeper-3.4.6
hadoop-2.7.3  scala         zeppelin-0.6.2-bin-all
jdk           scala-2.10.5  zeppelin-0.6.2-bin-all.tgz
jdk1.7.0_79   spark         zookeeper
spark@master:~/app$ rm zeppelin-0.6.2-bin-all.tgz 
spark@master:~/app$ ln -s zeppelin-0.6.2-bin-all/ zeppelin
spark@master:~/app$ ll
total 36
drwxrwxr-x  9 spark spark 4096 Jun  7 12:23 ./
drwxr-xr-x  7 spark spark 4096 Jun  7 00:53 ../
lrwxrwxrwx  1 spark spark   12 Jun  6 22:27 hadoop -> hadoop-2.7.3/
drwxr-xr-x 10 spark spark 4096 Jun  6 23:39 hadoop-2.7.3/
lrwxrwxrwx  1 spark spark   12 Jun  6 21:47 jdk -> jdk1.8.0_60//
drwxr-xr-x  8 spark spark 4096 Apr 11  2015 jdk1.7.0_79/
drwxr-xr-x  8 spark spark 4096 Aug  5  2015 jdk1.8.0_60/
lrwxrwxrwx  1 spark spark   13 Jun  7 00:14 scala -> scala-2.10.5//
drwxrwxr-x  9 spark spark 4096 Feb 27  2015 scala-2.10.5/
lrwxrwxrwx  1 spark spark   26 Jun  6 22:28 spark -> spark-2.0.2-bin-hadoop2.7//
drwxr-xr-x 12 spark spark 4096 Nov  8  2016 spark-2.0.2-bin-hadoop2.7/
lrwxrwxrwx  1 spark spark   23 Jun  7 12:23 zeppelin -> zeppelin-0.6.2-bin-all//
drwxr-xr-x  8 spark spark 4096 Oct 12  2016 zeppelin-0.6.2-bin-all/
lrwxrwxrwx  1 spark spark   16 Jun  7 00:46 zookeeper -> zookeeper-3.4.6//
drwxr-xr-x 10 spark spark 4096 Jun  7 00:54 zookeeper-3.4.6/
spark@master:~/app$ 

 3、修改环境变量配置

 

#zeppelin
export ZEPPELIN_HOME=/home/spark/app/zeppelin
export PATH=$PATH:$ZEPPELIN_HOME_HOME/bin

 

root@master:~# vim /etc/profile
root@master:~# source /etc/profile
root@master:~# 

　　说明，成功生效。

4.安装并修改配置文件：

（1）安装

　　网络安装版需要运行下面的命令：

./bin/install-interpreter.sh --all

　　　

　　而完整版不需要，直接进入到zeppelin的根目录修改配置文件即可。（我这里）

cd zepplin-0.6.2-bin-all

 

 

（2）/home/spark/app/zeppelin-0.6.2-bin-all/conf/zeppelin-env.sh

export JAVA_HOME=/home/spark/app/jdk
export SPARK_HOME=/home/spark/app/spark
export HADOOP_HOME=/home/spark/app/hadoop
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export ZEPPELIN_HOME_INTP_JAVA_OPTS="-XX:PermSize=512M -XX:MaxPermSize=1024M"

spark@master:~/app$ cd zeppelin-0.6.2-bin-all/
spark@master:~/app/zeppelin-0.6.2-bin-all$ pwd
/home/spark/app/zeppelin-0.6.2-bin-all
spark@master:~/app/zeppelin-0.6.2-bin-all$ ls
bin          lib       notebook   zeppelin-server-0.6.2.jar
conf         LICENSE   NOTICE     zeppelin-web-0.6.2.war
interpreter  licenses  README.md
spark@master:~/app/zeppelin-0.6.2-bin-all$ cd conf/
spark@master:~/app/zeppelin-0.6.2-bin-all/conf$ pwd
/home/spark/app/zeppelin-0.6.2-bin-all/conf
spark@master:~/app/zeppelin-0.6.2-bin-all/conf$ ls
configuration.xsl  README.md                  zeppelin-env.sh.template
interpreter-list   shiro.ini                  zeppelin-site.xml.template
log4j.properties   zeppelin-env.cmd.template
spark@master:~/app/zeppelin-0.6.2-bin-all/conf$ mv zeppelin-env.sh.template zeppelin-env.sh
spark@master:~/app/zeppelin-0.6.2-bin-all/conf$ ls
configuration.xsl  README.md                  zeppelin-env.sh
interpreter-list   shiro.ini                  zeppelin-site.xml.template
log4j.properties   zeppelin-env.cmd.template
spark@master:~/app/zeppelin-0.6.2-bin-all/conf$ vi zeppelin-env.sh 

 

export JAVA_HOME=/home/spark/app/jdk
export SPARK_HOME=/home/spark/app/spark
export HADOOP_HOME=/home/spark/app/hadoop
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export ZEPPELIN_HOME_INTP_JAVA_OPTS="-XX:PermSize=512M -XX:MaxPermSize=1024M"

 　　以上，主要是设置Java、Spark、Hadoop的安装路径，并且设置Java内存的使用量。

 

（3）/home/spark/app/zeppelin-0.6.2-bin-all/conf/zeppelin-site.xml

　　这里，我跟大家普及一个大数据领域的端口知识。（以下是我习惯用的端口情况）

YARN web ui 是8088

HBase web ui是60010、60030

Hadoop web ui是50070

Spark web ui是8081

Ooize web ui是11000

Kibana web ui是5601

Hue web ui是8888

Elasticsearch/Kopf/Head web ui是9200

Resourcemanager web ui是23188

History web ui是19888

Azakban web ui是8443

Storm web ui是9999

　　基于以上考虑，

为了防止端口冲突我将zeppelin的默认端口8080改为8099，具体情况要看自己的机子决定：

<property>
  <name>zeppelin.server.port</name>
  <value>8099</value>
  <description>Server port.</description>
</property>

 

 

 

4.启动或关闭：

修改之前的启动脚本为:（当然大家，也可不修改）

#!/bin/bash
echo -e "33[31m ========Start The Cluster======== 33[0m"
echo -e "33[31m Starting Hadoop Now !!! 33[0m"
/opt/hadoop-2.7.3/sbin/start-all.sh
echo -e "33[31m Starting Spark Now !!! 33[0m"
/opt/spark-2.0.2-bin-hadoop2.7/sbin/start-all.sh
echo -e "33[31m Starting Zeppelin Now !!! 33[0m"
/opt/zeppelin-0.6.2-bin-all/bin/zeppelin-daemon.sh start
echo -e "33[31m The Result Of The Command "jps" :  33[0m"
jps
echo -e "33[31m ========END======== 33[0m"

修改之前的关闭脚本为：（当然大家，也可不修改）

#!/bin/bash
echo -e "33[31m ===== Stoping The Cluster ====== 33[0m"
echo -e "33[31m Stoping Zeppelin Now !!! 33[0m"
/opt/zeppelin-0.6.2-bin-all/bin/zeppelin-daemon.sh stop
echo -e "33[31m Stoping Spark Now !!! 33[0m"
/opt/spark-2.0.2-bin-hadoop2.7/sbin/stop-all.sh
echo -e "33[31m Stopting Hadoop Now !!! 33[0m"
/opt/hadoop-2.7.3/sbin/stop-all.sh
echo -e "33[31m The Result Of The Command "jps" :  33[0m"
jps
echo -e "33[31m ======END======== 33[0m"

 

 

启动Apache Zeppelin

　　在zeppelin_home目录下执行如下命令：

spark@master:~/app/zeppelin-0.6.2-bin-all$ bin/zeppelin-daemon.sh start

spark@master:~/app/zeppelin-0.6.2-bin-all$ pwd
/home/spark/app/zeppelin-0.6.2-bin-all
spark@master:~/app/zeppelin-0.6.2-bin-all$ ls
bin          lib       notebook   zeppelin-server-0.6.2.jar
conf         LICENSE   NOTICE     zeppelin-web-0.6.2.war
interpreter  licenses  README.md
spark@master:~/app/zeppelin-0.6.2-bin-all$ bin/zeppelin-daemon.sh start
Log dir doesn't exist, create /home/spark/app/zeppelin/logs
Pid dir doesn't exist, create /home/spark/app/zeppelin/run
Zeppelin start                                             [  OK  ]
spark@master:~/app/zeppelin-0.6.2-bin-all$ ls
bin          LICENSE   NOTICE                     zeppelin-web-0.6.2.war
conf         licenses  README.md
interpreter  logs      run
lib          notebook  zeppelin-server-0.6.2.jar
spark@master:~/app/zeppelin-0.6.2-bin-all$ 

　　其启动/停止命令： bin/zeppelin-daemon.sh start/stop。

　启动之后，打开localhost:8099访问zepplin主页。

http://localhost:8099/#/

 　　我这里是

 

　　在打开Zeppelin Web UI界面之后，然后如下

 　　然后，可以看到

 

 　　其实啊，这样的显示风格不难，我不知道，如果大家有玩过python来做机器学习、深度学习、数据挖掘的话。其实，这样的风格就很简单啦。

 如果大家感兴趣的话，可以继续关注我的博客。会陆续有这方面的优质博文。大家一起进步共同学习！

　　后续博客

Zeppelin的入门使用系列之创建新的Notebook（一）