安装hbase

本文详细介绍了在安装HBase之前如何确保Zookeeper、Java和Hadoop的正确配置,特别是强调了Hadoop版本与HBase版本的兼容性。接着,重点讲述了ntp同步Linux集群时间的步骤,包括选择基准服务器、配置NTP服务、设置客户端访问权限以及启动NTP服务。最后,概述了HBase的配置过程,包括环境变量设置、站点配置、regionsevers配置以及启动HBase和进行测试。

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1.hbase安装注意事项
hbase开始安装前确保安装了zookeeper、java、hadoop
以及hadoop版本号对应的hbse版本。以免发生不兼容现象。安装时一定要同步ntp时间
2.ntp同步liunx集群时间
(1)选择其中一台作为基准服务器,安装ntp
机器mini1,mini2,mini3

yum install ntp  

(2)服务器配置
mini1上调整时间
可以联网的情况下执行命令,确保mini1上的时间与本地时间保持一致

ntpdate 0.centos.pool.ntp.org   #该网址为centos网络上的时间同步服务器

一般情况下,我们的集群为内网环境,无法和外网进行联网同步之间,那么手动执行命令调整时间

date -s '2008-05-23 01:01:01' + '%F %T' #2008-05-23 01:01:01为将要设定的时间

host1上修改配置文件/etc/ntp.conf

vi /etc/ntp.conf

添加下面两行,表示将本地的硬件时间也作为同步的时间源之一,这样在不联网的时候可以把本机时间作为同步时间源, 在内网环境下,可以把配置文件中其他的server都删除掉。

server 127.127.1.0 # local clock

fudge 127.127.1.0 stratum 10

如果集群是在一个封闭的局域网内,可以屏蔽掉默认的server:

#server 0.centos.pool.ntp.org iburst
#server 1.centos.pool.ntp.org iburst
#server 2.centos.pool.ntp.org iburst
#server 3.centos.pool.ntp.org iburst

host1上配置客户端的授权

restrict 192.168.71.221 mask 255.255.255.250 nomodify notrap

也就是给指定的机器(客户端)设置访问NTP Server的权限,这是通过restrict配置项实现的,以下是它的格式说明。

其中parameter的参数主要有:
ignore : 拒绝所有类型的ntp连接
nomodify : 客户端不能使用ntpc与ntpq两支程式来修改服务器的时间参数
noquery : 客户端不能使用ntpq、ntpc等指令来查询服务器时间,等于不提供ntp的网络校时
notrap : 不提供trap这个远程时间登录的功能
notrust : 拒绝没有认证的客户端
nopeer : 不与其他同一层的ntp服务器进行时间同步
(3)客户机配置
mini2,mini3上修改配置文件/etc/ntp.conf

vi /etc/ntp.conf

删除其他的server 开头的配置项,这里一定要删除,只同步我们配置的那台服务器,添加上面设置的NTP服务器地址

server mini1

查看与时间同步服务器的时间偏差

ntpdc -c loopinfo

查看当前同步的时间服务器,查看没问题就安装成功了

ntpq -p	

(4)启动ntp服务
service ntpd start #启动ntpd时间服务器
chkconfig ntpd on #开机自启动

3.hbase配置
(1)hbase-env.sh环境变量配置

#!/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.
# */

# Set environment variables here.

# This script sets variables multiple times over the course of starting an hbase process,
# so try to keep things idempotent unless you want to take an even deeper look
# into the startup scripts (bin/hbase, etc.)

# The java implementation to use.  Java 1.8+ required.
  export JAVA_HOME=/root/apps/jdk1.8.0_171

# Extra Java CLASSPATH elements.  Optional.
# export HBASE_CLASSPATH=
  export JAVA_CLASSPATH=,:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tool.jar
# The maximum amount of heap to use. Default is left to JVM default.
# export HBASE_HEAPSIZE=1G

# Uncomment below if you intend to use off heap cache. For example, to allocate 8G of 
# offheap, set the value to "8G".
# export HBASE_OFFHEAPSIZE=1G

# Extra Java runtime options.
# Below are what we set by default.  May only work with SUN JVM.
# For more on why as well as other possible settings,
# see http://hbase.apache.org/book.html#performance
export HBASE_OPTS="$HBASE_OPTS -XX:+UseConcMarkSweepGC"

# Uncomment one of the below three options to enable java garbage collection logging for the server-side processes.

# This enables basic gc logging to the .out file.
# export SERVER_GC_OPTS="-verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps"

# This enables basic gc logging to its own file.
# If FILE-PATH is not replaced, the log file(.gc) would still be generated in the HBASE_LOG_DIR .
# export SERVER_GC_OPTS="-verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps -Xloggc:<FILE-PATH>"

# This enables basic GC logging to its own file with automatic log rolling. Only applies to jdk 1.6.0_34+ and 1.7.0_2+.
# If FILE-PATH is not replaced, the log file(.gc) would still be generated in the HBASE_LOG_DIR .
# export SERVER_GC_OPTS="-verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps -Xloggc:<FILE-PATH> -XX:+UseGCLogFileRotation -XX:NumberOfGCLogFiles=1 -XX:GCLogFileSize=512M"

# Uncomment one of the below three options to enable java garbage collection logging for the client processes.

# This enables basic gc logging to the .out file.
# export CLIENT_GC_OPTS="-verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps"

# This enables basic gc logging to its own file.
# If FILE-PATH is not replaced, the log file(.gc) would still be generated in the HBASE_LOG_DIR .
# export CLIENT_GC_OPTS="-verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps -Xloggc:<FILE-PATH>"

# This enables basic GC logging to its own file with automatic log rolling. Only applies to jdk 1.6.0_34+ and 1.7.0_2+.
# If FILE-PATH is not replaced, the log file(.gc) would still be generated in the HBASE_LOG_DIR .
# export CLIENT_GC_OPTS="-verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps -Xloggc:<FILE-PATH> -XX:+UseGCLogFileRotation -XX:NumberOfGCLogFiles=1 -XX:GCLogFileSize=512M"

# See the package documentation for org.apache.hadoop.hbase.io.hfile for other configurations
# needed setting up off-heap block caching. 

# Uncomment and adjust to enable JMX exporting
# See jmxremote.password and jmxremote.access in $JRE_HOME/lib/management to configure remote password access.
# More details at: http://java.sun.com/javase/6/docs/technotes/guides/management/agent.html
# NOTE: HBase provides an alternative JMX implementation to fix the random ports issue, please see JMX
# section in HBase Reference Guide for instructions.

# export HBASE_JMX_BASE="-Dcom.sun.management.jmxremote.ssl=false -Dcom.sun.management.jmxremote.authenticate=false"
# export HBASE_MASTER_OPTS="$HBASE_MASTER_OPTS $HBASE_JMX_BASE -Dcom.sun.management.jmxremote.port=10101"
# export HBASE_REGIONSERVER_OPTS="$HBASE_REGIONSERVER_OPTS $HBASE_JMX_BASE -Dcom.sun.management.jmxremote.port=10102"
# export HBASE_THRIFT_OPTS="$HBASE_THRIFT_OPTS $HBASE_JMX_BASE -Dcom.sun.management.jmxremote.port=10103"
# export HBASE_ZOOKEEPER_OPTS="$HBASE_ZOOKEEPER_OPTS $HBASE_JMX_BASE -Dcom.sun.management.jmxremote.port=10104"
# export HBASE_REST_OPTS="$HBASE_REST_OPTS $HBASE_JMX_BASE -Dcom.sun.management.jmxremote.port=10105"

# File naming hosts on which HRegionServers will run.  $HBASE_HOME/conf/regionservers by default.
# export HBASE_REGIONSERVERS=${HBASE_HOME}/conf/regionservers

# Uncomment and adjust to keep all the Region Server pages mapped to be memory resident
#HBASE_REGIONSERVER_MLOCK=true
#HBASE_REGIONSERVER_UID="hbase"

# File naming hosts on which backup HMaster will run.  $HBASE_HOME/conf/backup-masters by default.
# export HBASE_BACKUP_MASTERS=${HBASE_HOME}/conf/backup-masters

# Extra ssh options.  Empty by default.
# export HBASE_SSH_OPTS="-o ConnectTimeout=1 -o SendEnv=HBASE_CONF_DIR"

# Where log files are stored.  $HBASE_HOME/logs by default.
# export HBASE_LOG_DIR=${HBASE_HOME}/logs

# Enable remote JDWP debugging of major HBase processes. Meant for Core Developers 
# export HBASE_MASTER_OPTS="$HBASE_MASTER_OPTS -Xdebug -Xrunjdwp:transport=dt_socket,server=y,suspend=n,address=8070"
# export HBASE_REGIONSERVER_OPTS="$HBASE_REGIONSERVER_OPTS -Xdebug -Xrunjdwp:transport=dt_socket,server=y,suspend=n,address=8071"
# export HBASE_THRIFT_OPTS="$HBASE_THRIFT_OPTS -Xdebug -Xrunjdwp:transport=dt_socket,server=y,suspend=n,address=8072"
# export HBASE_ZOOKEEPER_OPTS="$HBASE_ZOOKEEPER_OPTS -Xdebug -Xrunjdwp:transport=dt_socket,server=y,suspend=n,address=8073"

# A string representing this instance of hbase. $USER by default.
# export HBASE_IDENT_STRING=$USER

# The scheduling priority for daemon processes.  See 'man nice'.
# export HBASE_NICENESS=10

# The directory where pid files are stored. /tmp by default.
# export HBASE_PID_DIR=/var/hadoop/pids

# Seconds to sleep between slave commands.  Unset by default.  This
# can be useful in large clusters, where, e.g., slave rsyncs can
# otherwise arrive faster than the master can service them.
# export HBASE_SLAVE_SLEEP=0.1

# Tell HBase whether it should manage it's own instance of ZooKeeper or not.
  export HBASE_MANAGES_ZK=false

# The default log rolling policy is RFA, where the log file is rolled as per the size defined for the 
# RFA appender. Please refer to the log4j.properties file to see more details on this appender.
# In case one needs to do log rolling on a date change, one should set the environment property
# HBASE_ROOT_LOGGER to "<DESIRED_LOG LEVEL>,DRFA".
# For example:
# HBASE_ROOT_LOGGER=INFO,DRFA
# The reason for changing default to RFA is to avoid the boundary case of filling out disk space as 
# DRFA doesn't put any cap on the log size. Please refer to HBase-5655 for more context.

(2)hbase-site.xml配置

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
/**
 *
 * 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.
 */
-->
<configuration>
 <property>
  <name>hbase.master</name>             #hbasemaster的主机和端口
  <value>mini1:60000</value>
  </property>
  <property>
  <name>hbase.master.maxclockskew</name>    #时间同步允许的时间差
  <value>180000</value>
  </property>
  <property>
  <name>hbase.rootdir</name>
  <value>hdfs://ns1/hbase</value>#hbase共享目录,持久化hbase数据
  </property>
  <property>
  <name>hbase.cluster.distributed</name>  #是否分布式运行,false即为单机
  <value>true</value>
  </property>
  <property>
  <name>hbase.zookeeper.quorum</name>#zookeeper地址
  <value>mini1,mini2,mini3</value>
  </property>
  <property>
  <name>hbase.zookeeper.property.dataDir</name>#zookeeper配置信息快照的位置
  <value>/home/hadoop/apps/hbase/tmp/zookeeper</value>
  </property>
</configuration>

(3)配置regionsevers’将从节点信息写入
将hadoop配置中的core-site.xml与hdfs-site.sh拷贝到conf文件夹
(4)启动hbase
bin/start-hbase.sh
启动hbaseshell 测试

### 在Hadoop上安装和配置HBase #### 确保Hadoop已正确安装和配置 为了使HBase能够正常工作,必须先确认Hadoop已经成功安装并运行。以下是验证步骤: 1. **启动Hadoop集群** 使用命令 `start-dfs.sh` 和 `start-yarn.sh` 来启动Hadoop服务[^1]。 2. **查看Hadoop版本** 执行以下命令来检查当前Hadoop的版本号,并确保其与计划使用的HBase版本兼容: ```bash hadoop version ``` #### 安装HBase 完成上述准备工作后,可以继续进行HBase安装过程。 1. **下载HBase软件包** 前往Apache官网或其他可信源下载适合的HBase版本(例如HBase-2.4.14)。可以通过wget工具获取文件: ```bash wget https://archive.apache.org/dist/hbase/2.4.14/hbase-2.4.14-bin.tar.gz ``` 2. **解压并重命名** 将压缩包解压到目标路径,并将其命名为便于识别的形式: ```bash tar -zxvf hbase-2.4.14-bin.tar.gz -C /usr/local/ mv /usr/local/hbase-2.4.14 /usr/local/hbase ``` 3. **设置环境变量** 修改用户的 `.bashrc` 文件以添加HBase的相关路径: ```bash export HBASE_HOME=/usr/local/hbase export PATH=$PATH:$HBASE_HOME/bin source ~/.bashrc ``` 4. **调整权限** 更改HBase目录的所有者以及访问权限以便于后续操作: ```bash chown -R hadoop:hadoop /usr/local/hbase/ chmod 777 /usr/local/hbase/ ``` 5. **测试安装是否成功** 运行如下命令检验HBase是否被正确部署: ```bash hbase version ``` #### 配置HBase伪分布式模式 为了让HBase能够在单节点环境中模拟分布式行为,需执行以下配置更改。 1. **编辑hbase-env.sh** 设置Java环境以及其他必要的参数,在 `/usr/local/hbase/conf/hbase-env.sh` 中加入以下内容: ```bash export JAVA_HOME=/path/to/java export HBASE_MANAGES_ZK=true ``` 2. **修改hbase-site.xml** 更新核心站点配置文件 `/usr/local/hbase/conf/hbase-site.xml` ,定义存储位置和其他选项: ```xml <configuration> <property> <name>hbase.rootdir</name> <value>hdfs://localhost:9000/hbase</value> </property> <property> <name>hbase.cluster.distributed</name> <value>true</value> </property> </configuration> ``` 3. **启动HBase服务** 利用内置脚本开启Master及RegionServer进程: ```bash start-hbase.sh ``` 通过以上流程即可实现HBase在基于Hadoop平台上的初步搭建与调试[^2]。 ---
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