​目录​

​​一、环境准备​​

​​1、HBase历史版本​​

​​2、HBase官方文档​​

​​3、Linux SSH免密登录​​

​​4、Linux zk高可用部署​​

​​5、Docker搭建Hadoop集群​​

​​二、HBase安装​​

​​1、下载hbase​​

​​2、解压文件​​

​​3、创建软链接​​

​​三、HBASE配置​​

​​1、regionservers配置​​

​​2、hbase-site.xml配置​​

​​3、hbase-env.sh配置​​

​​4、backup-masters配置​​

​​四、环境变量配置​​

​​1、HBase环境变量配置​​

​​2、配置立即生效​​

​​五、启动HBase​​

​​1、启动Zookeeper​​

​​2、启动Hadoop​​

​​3、启动HBase​​

​​六、验证安装​​

​​1、HBase Shell​​

​​2、HBase WebUI​​

一、环境准备

1、​​HBase​​历史版本

​​Index of /dist/hbase​​

2、HBase官方文档

​​Apache HBase ™ Reference Guide​​

3、Linux ​​SSH​​免密登录

​​大数据入门之 ssh 免密码登录_qq262593421的博客-CSDN博客​​

4、Linux zk高可用部署

​​大数据高可用技术之zookeeper3.4.5安装配置_qq262593421的博客-CSDN博客​​

5、Docker搭建Hadoop集群


二、HBase安装

1、下载hbase

wget -p /usr/local/hadoop/ http://archive.apache.org/dist/hbase/2.1.0/hbase-2.1.0-bin.tar.gz

2、解压文件

cd /usr/local/hadoop
tar zxpf hbase-2.1.0-bin.tar.gz -C /usr/local/hadoop

3、创建软链接

ln -s /usr/local/hadoop/hbase-2.1.0 /usr/local/hadoop/hbase

三、HBASE配置

​1、regionservers配置​

regionservers配置和hadoop的work一样，hadoop的DataNode节点是哪个regionservers就是哪几个

echo 'hadoop01
hadoop02
hadoop03' > /usr/local/hadoop/hbase/conf/regionservers

​2、hbase-site.xml配置​

mv /usr/local/hadoop/hbase/conf/hbase-site.xml /usr/local/hadoop/hbase/conf/hbase-site.xml.init
vim /usr/local/hadoop/hbase/conf/hbase-site.xml
<?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>zookeeper.znode.parent</name>
     <value>/hbase/master</value>
  </property>
  -->
  <property>  
    <name>hbase.master</name>
    <value>60000</value>
    <!-- Hbase HA 方式下只需配置端口 -->
  </property>
  <property>
    <name>hbase.tmp.dir</name>
    <value>/home/cluster/hbase/tmp</value>
  </property>
  <property>
    <name>hbase.rootdir</name>
    <value>hdfs://ns1/hbase</value>
  </property>
  <property>
    <name>hbase.cluster.distributed</name>
    <value>true</value>
  </property>
  <property>
    <name>hbase.zookeeper.property.clientPort</name>
    <value>2181</value>
  </property>
  <property>
    <name>hbase.zookeeper.quorum</name>
    <value>hadoop01,hadoop02,hadoop03</value>
    <!-- <value>hadoop01:2181,hadoop02:2181,hadoop03:2181</value> -->
  </property>
  <property>
    <name>hbase.zookeeper.property.dataDir</name>
    <value>/usr/local/zookeeper/data</value>
  </property>
  <property>
    <name>dfs.datanode.max.transfer.threads</name>
    <value>4096</value>
  </property>
  <!-- 
  <property>
    <name>hbase.master</name>
    <value>hadoop01</value>
  </property>
  -->
  <!-- 
  <property>
    <name>hbase.masters</name>
    <value>hadoop01,hadoop02</value>
    <description>List of master rpc end points for the hbase cluster.</description>
  </property>
  -->
  <property>
    <name>hbase.unsafe.stream.capability.enforce</name>
    <value>false</value>
  </property>
  <!-- 
  <property>
    <name>hbase.lease.recovery.dfs.timeout</name>
    <value>23000</value>
    <description>How much time we allow elapse between calls to recover lease.
    Should be larger than the dfs timeout.</description>
  </property>
  <property>
    <name>dfs.client.socket-timeout</name>
    <value>10000</value>
    <description>Down the DFS timeout from 60 to 10 seconds.</description>
  </property>
  <property>
    <name>dfs.client.socket-timeout</name>
    <value>10000</value>
    <description>Down the DFS timeout from 60 to 10 seconds.</description>
  </property>
  <property>
    <name>dfs.datanode.socket.write.timeout</name>
    <value>10000</value>
    <description>Down the DFS timeout from 8 * 60 to 10 seconds.</description>
  </property>
  <property>
    <name>ipc.client.connect.timeout</name>
    <value>3000</value>
    <description>Down from 60 seconds to 3.</description>
  </property>
  -->

  <!-- 
  <property>
    <name>ipc.client.connect.max.retries.on.timeouts</name>
    <value>2</value>
    <description>Down from 45 seconds to 3 (2 == 3 retries).</description>
  </property>
  <property>
    <name>dfs.namenode.avoid.read.stale.datanode</name>
    <value>true</value>
    <description>Enable stale state in hdfs</description>
  </property>
  <property>
    <name>dfs.namenode.stale.datanode.interval</name>
    <value>20000</value>
    <description>Down from default 30 seconds</description>
  </property>
  <property>
    <name>dfs.namenode.avoid.write.stale.datanode</name>
    <value>true</value>
    <description>Enable stale state in hdfs</description>
  </property>
  -->

  <!-- 
  <property>
    <name>hbase.security.authentication</name>
    <value>simple</value>
  </property>
  <property>
    <name>hbase.security.authorization</name>
    <value>true</value>
  </property>
  <property>
    <name>hbase.coprocessor.master.classes</name>
    <value>org.apache.hadoop.hbase.security.access.AccessController</value>
  </property>
  <property>
    <name>hbase.coprocessor.region.classes</name>
    <value>org.apache.hadoop.hbase.security.access.AccessController</value>
  </property>
  <property>
    <name>hbase.coprocessor.regionserver.classes</name>
    <value>org.apache.hadoop.hbase.security.access.AccessController</value>
  </property>
  <property>
    <name>hbase.security.authentication</name>
    <value>simple</value>
  </property>
  <property>
    <name>hbase.rpc.engine</name>
    <value>org.apache.hadoop.hbase.ipc.SecureRpcEngine</value>
  </property>
  -->

  <!-- HFile v3 Support -->
  <property>
    <name>hfile.format.version</name>
    <value>3</value>
  </property>
  <!-- HBase Superuser -->
  <property>
    <name>hbase.superuser</name>
    <value>hbase,admin,root,hdfs,zookeeper,hive,hadoop,hue,impala,spark,kylin</value>
  </property>

  <!-- geomesa-hbase -->
  <!--
  <property>
    <name>hbase.coprocessor.user.region.classes</name>
    <value>org.locationtech.geomesa.hbase.coprocessor.GeoMesaCoprocessor</value>
  </property>
  -->
  <property>
    <name>hbase.table.sanity.checks</name>
    <value>false</value>
  </property>
  <property>
    <name>hbase.coprocessor.abortonerror</name>
    <value>false</value>
  </property>

  <!-- adjust and optimize --> 
  <property>
    <name>hfile.block.cache.size</name> 
    <value/>
    <!-- <value>0.2</value> -->
    <description>stofile的读缓存占用Heap的大小百分比。该值直接影响数据读的性能当然是越大越好，如果写比读少很多，开到0.4-0.5也没问题，如果读写均衡，设置为0.3左右。如果写比读多，果断使用默认就行。</description>
  </property>
  <!-- 启用multiwal https://www.jianshu.com/p/b23800d9b227-->
  <property>
    <name>hbase.wal.provider</name>
    <value>multiwal</value>
    <description>MultiWAL: 如果每个RegionServer只有一个WAL，由于HDFS必须是连续的，导致必须写WAL连续的，然后出现性能问题。MultiWAL可以让RegionServer同时写多个WAL并行的，通过HDFS底层的多管道，最终提升总的吞吐量，但是不会提升单个Region的吞吐量。</description>
  </property>

  <!-- phoenix config -->
  <!-- 
  <property>
    <name>hbase.regionserver.wal.codec</name>
    <value>org.apache.hadoop.hbase.regionserver.wal.IndexedWALEditCodec</value>
  </property> 
  <property>
    <name>phoenix.schema.isNamespaceMappingEnabled</name>
    <value>true</value>
  </property>
  <property>
    <name>phoenix.schema.mapSystemTablesToNamespace</name>
    <value>true</value>
  </property>
  <property>
    <name>phoenix.functions.allowUserDefinedFunctions</name>
    <value>true</value>
    <description>enable UDF functions</description>
  </property>
  -->

</configuration>

​3、hbase-env.sh配置​

mv /usr/local/hadoop/hbase/conf/hbase-env.sh /usr/local/hadoop/hbase/conf/hbase-env.sh.init
vim /usr/local/hadoop/hbase/conf/hbase-env.sh
#!/usr/bin/env bash

export HBASE_OPTS="-XX:+UseConcMarkSweepGC -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -Xloggc:/usr/local/hadoop/hbase/logs/jvm-gc-hbase.log"

export JAVA_HOME=/usr/java/jdk1.8
export HBASE_HEAPSIZE=4G

export HADOOP_HOME=/usr/local/hadoop/hadoop
export HBASE_HOME=/usr/local/hadoop/hbase
export HBASE_CLASSPATH=/usr/local/hadoop/hadoop/etc/hadoop
export HBASE_MANAGES_ZK=false
export HBASE_PID_DIR=/var/hadoop/pids

​4、backup-masters配置​

启动hbase时会将配置的backup-masters节点作为备用HMaster

echo 'hadoop01
hadoop02' > /usr/local/hadoop/hbase/conf/backup-masters

四、环境变量配置

1、HBase环境变量配置

echo '
## hbase config
export HBASE_HOME=/usr/local/hadoop/hbase
export PATH=$PATH:$HBASE_HOME/bin' >> /etc/profile

2、配置立即生效

source /etc/profile

五、启动HBase

1、启动​​Zookeeper​​ 

zkServer.sh start

2、启动Hadoop

hdfs --daemon start zkfc
start-all.sh

3、启动HBase

start-hbase.sh

六、验证安装

1、HBase Shell

hbase shell
create 'tb1','cmf1','cmf2','cmf3'
list
list_namespace

2、HBase WebUI

​​http://hadoop01:16010​​​ ​​http://127.0.0.1:16011​​

​​http://hadoop02:16010​​​ ​​http://127.0.0.1:16012​​