说完了Hive我们接着来看另外一个建立在Hadoop基础上的存储引擎HBase,HBase以内存作为缓存数据落地到HDFS的Key-Value数据库,因为使用内存缓存极大保障了数据的实时性和实时查询能力,在实时场景的大数据存储HBase是不可或缺的解决方案,常见又在使用这项技术的业务就是短链,比如你在微信给你的朋友发个URL最终你的朋友获取到的是微信的一个短链接(QQ淘宝都是如此),在HBase中就存储了这样一个对应关系,这一切都归功于HBase的吞吐量和实时响应速度.
1. 准备工作
准备软件包
zookeeper-3.4.10.tar.gzhbase-1.3.1-bin.tar.gzHbase依赖于Zookeeper和Hadoop集群所以我们在之前配置好的Hadoop集群下来配置整体的Hbase集群服务器清单
# hadoop-1 192.168.1.101 NameNode DataNode$ hadoop-2 192.168.1.102 DataNode$ hadoop-3 192.168.1.103 DataNodeZookeeper安装
> cd /app/install/> tar -zxvf zookeeper-3.4.10.tar.gz> mv zookeeper-3.4.10 /usr/local/修改配置文件
> cd /usr/local/zookeeper-3.4.10/conf/> cp zoo_sample.cfg zoo.cfg> vim zoo.cfgtickTime=2000dataDir=/usr/local/zookeeper-3.4.10/dataclientPort=2181initLimit=10syncLimit=5server.1=hadoop-1:2888:3888server.2=hadoop-2:2888:3888server.3=hadoop-3:2888:3888所有节点修改环境变量
> vim /etc/profile# zookeeperexport ZOOKEEPER_HOME=/usr/local/zookeeper-3.4.10export PATH=$ZOOKEEPER_HOME/bin:$PATH> source /etc/profile将zookeeper目录复制到其他节点上
> scp -r /usr/local/zookeeper-3.4.10/ root@hadoop-2:/usr/local/zookeeper-3.4.10> scp -r /usr/local/zookeeper-3.4.10/ root@hadoop-3:/usr/local/zookeeper-3.4.10添加myid文件(每节点都需要)
> cd /usr/local/zookeeper-3.4.10> mkdir data> echo "1" > data/myid注意，每个节点myid文件要不一致
启动并测试
# 在三台机器上分别执行> zkServer.sh start# 查看状态[root@hadoop-1 zookeeper-3.4.10]# zkServer.sh statusZooKeeper JMX enabled by defaultUsing config: /usr/local/zookeeper-3.4.10/bin/../conf/zoo.cfgMode: follower[root@hadoop-2 zookeeper-3.4.10]# zkServer.sh statusZooKeeper JMX enabled by defaultUsing config: /usr/local/zookeeper-3.4.10/bin/../conf/zoo.cfgMode: leader[root@hadoop-3 zookeeper-3.4.10]# zkServer.sh statusZooKeeper JMX enabled by defaultUsing config: /usr/local/zookeeper-3.4.10/bin/../conf/zoo.cfgMode: follower2.安装HBase
> cd /app/install/> tar -zxvf hbase-1.3.1-bin.tar.gz > mv hbase-1.3.1 /usr/local/修改配置文件
> vim /usr/local/hbase-1.3.1/conf/hbase-env.sh# 配置Java环境变量export JAVA_HOME=/usr/local/jdk1.8# hbase使用外部的zkexport HBASE_MANAGES_ZK=false增加相应配置
> vim /usr/local/hbase-1.3.1/conf/hbase-site.xmlhbase.rootdirhdfs://hadoop-1:9000/hbasehbase.cluster.distributedtruehbase.zookeeper.quorumhadoop-1:2181,hadoop-2:2181,hadoop-3:2181增加子节点
> vim /usr/local/hbase-1.3.1/conf/regionservershadoop-2hadoop-3创建hdfs中数据存放路径b
> hdfs dfs -mkdir /user/hadoop/hbase复制到其他节点
> scp -r /usr/local/hbase-1.3.1/ root@hadoop-2:/usr/local/hbase-1.3.1> scp -r /usr/local/hbase-1.3.1/ root@hadoop-3:/usr/local/hbase-1.3.1# 分别赋予权限chown -R hadoop:hadoop /usr/local/hbase-1.3.1/所有节点配置环境变量
> vim /etc/profile# hbaseexport HBASE_HOME=/usr/local/hbase-1.3.1export PATH=$HBASE_HOME/bin:$PATH> source /etc/profile启动集群
su hadoopstart-hbase.sh通过JPS可以查看到主节点上有HMaster进程子节点上有HRegionServer进程
内网可以访问Hbase管理界面 http://hadoop-1:16010
3.基本操作
通过如下命令可以进入Hbase的shell操作界面
hbase shellhbase(main):001:0>一般操作
查询服务器状态
hbase(main):024:0>status1 active master, 0 backup masters, 2 servers, 0 dead, 1.0000 average load查询HBase版本信息
hbase(main):025:0>version1.3.1, r930b9a55528fe45d8edce7af42fef2d35e77677a, Thu Apr 6 19:36:54 PDT 2017二、DDL操作
1.创建一个表
hbase(main):011:0>create 'member','member_id','address','info' 0 row(s) in 1.2210seconds2.获得表的描述
hbase(main):012:0>listTABLE member 1 row(s) in 0.0160secondshbase(main):006:0>describe 'member'DESCRIPTION ENABLED {NAME => 'member', FAMILIES => [{NAME=> 'address', BLOOMFILTER => 'NONE', REPLICATION_SCOPE => '0', true VERSIONS => '3', COMPRESSION => 'NONE',TTL => '2147483647', BLOCKSIZE => '65536', IN_MEMORY => 'fa lse', BLOCKCACHE => 'true'}, {NAME =>'info', BLOOMFILTER => 'NONE', REPLICATION_SCOPE => '0', VERSI ONS => '3', COMPRESSION => 'NONE', TTL=> '2147483647', BLOCKSIZE => '65536', IN_MEMORY => 'false', BLOCKCACHE => 'true'}]} 1 row(s) in 0.0230seconds3.删除一个列族，alter，disable，enable
我们之前建了3个列族，但是发现member_id这个列族是多余的，因为他就是主键，所以我们要将其删除。
hbase(main):003:0>alter 'member',{NAME=>'member_id',METHOD=>'delete'}ERROR: Table memberis enabled. Disable it first before altering.直接操作会报错，如果需要删除列族的时候必须先将表给disable掉。
hbase(main):004:0>disable 'member' 0 row(s) in 2.0390secondshbase(main):005:0>alter'member',{NAME=>'member_id',METHOD=>'delete'}0 row(s) in 0.0560secondshbase(main):006:0>describe 'member'DESCRIPTION ENABLED {NAME => 'member', FAMILIES => [{NAME=> 'address', BLOOMFILTER => 'NONE', REPLICATION_SCOPE => '0',false VERSIONS => '3', COMPRESSION => 'NONE',TTL => '2147483647', BLOCKSIZE => '65536', IN_MEMORY => 'fa lse', BLOCKCACHE => 'true'}, {NAME =>'info', BLOOMFILTER => 'NONE', REPLICATION_SCOPE => '0', VERSI ONS => '3', COMPRESSION => 'NONE', TTL=> '2147483647', BLOCKSIZE => '65536', IN_MEMORY => 'false', BLOCKCACHE => 'true'}]} 1 row(s) in 0.0230seconds该列族已经删除，我们继续将表enable
hbase(main):008:0> enable 'member' 0 row(s) in 2.0420seconds4.列出所有的表
hbase(main):028:0>listTABLE member temp_table 2 row(s) in 0.0150seconds5.drop一个表
hbase(main):029:0>disable 'temp_table'0 row(s) in 2.0590secondshbase(main):030:0>drop 'temp_table'0 row(s) in 1.1070seconds6.查询表是否存在
hbase(main):021:0>exists 'member'Table member doesexist 0 row(s) in 0.1610seconds7.判断表是否enable
hbase(main):034:0>is_enabled 'member'true 0 row(s) in 0.0110seconds8.判断表是否disable
hbase(main):032:0>is_disabled 'member'false 0 row(s) in 0.0110seconds三、DML操作
1.插入几条记录
put'member','scutshuxue','info:age','24'put'member','scutshuxue','info:birthday','1987-06-17'put'member','scutshuxue','info:company','alibaba'put'member','scutshuxue','address:contry','china'put'member','scutshuxue','address:province','zhejiang'put'member','scutshuxue','address:city','hangzhou'put'member','xiaofeng','info:birthday','1987-4-17'put'member','xiaofeng','info:favorite','movie' put'member','xiaofeng','info:company','alibaba'put'member','xiaofeng','address:contry','china'put'member','xiaofeng','address:province','guangdong'put'member','xiaofeng','address:city','jieyang'put'member','xiaofeng','address:town','xianqiao'2.获取一条数据
获取一个id的所有数据
hbase(main):001:0>get 'member','scutshuxue'COLUMN CELL address:city timestamp=1321586240244, value=hangzhou address:contry timestamp=1321586239126, value=china address:province timestamp=1321586239197, value=zhejiang info:age timestamp=1321586238965, value=24 info:birthday timestamp=1321586239015, value=1987-06-17 info:company timestamp=1321586239071, value=alibaba 6 row(s) in 0.4720seconds获取一个id，一个列族的所有数据
hbase(main):002:0>get 'member','scutshuxue','info'COLUMN CELL info:age timestamp=1321586238965, value=24 info:birthday timestamp=1321586239015, value=1987-06-17 info:company timestamp=1321586239071, value=alibaba 3 row(s) in 0.0210seconds获取一个id，一个列族中一个列的所有数据
hbase(main):002:0>get 'member','scutshuxue','info:age' COLUMN CELL info:age timestamp=1321586238965, value=24 1 row(s) in 0.0320seconds6.更新一条记录
将scutshuxue的年龄改成99
hbase(main):004:0>put 'member','scutshuxue','info:age' ,'99'0 row(s) in 0.0210secondshbase(main):005:0>get 'member','scutshuxue','info:age' COLUMN CELL info:age timestamp=1321586571843, value=99 1 row(s) in 0.0180seconds3.通过timestamp来获取两个版本的数据
hbase(main):010:0>get 'member','scutshuxue',{COLUMN=>'info:age',TIMESTAMP=>1321586238965}COLUMN CELL info:age timestamp=1321586238965, value=24 1 row(s) in 0.0140secondshbase(main):011:0>get 'member','scutshuxue',{COLUMN=>'info:age',TIMESTAMP=>1321586571843}COLUMN CELL info:age timestamp=1321586571843, value=99 1 row(s) in 0.0180seconds4.全表扫描：
hbase(main):013:0>scan 'member'ROW COLUMN+CELL scutshuxue column=address:city, timestamp=1321586240244, value=hangzhou scutshuxue column=address:contry, timestamp=1321586239126, value=china scutshuxue column=address:province, timestamp=1321586239197, value=zhejiang scutshuxue column=info:age,timestamp=1321586571843, value=99 scutshuxue column=info:birthday, timestamp=1321586239015, value=1987-06-17 scutshuxue column=info:company, timestamp=1321586239071, value=alibaba temp column=info:age, timestamp=1321589609775, value=59 xiaofeng column=address:city, timestamp=1321586248400, value=jieyang xiaofeng column=address:contry, timestamp=1321586248316, value=china xiaofeng column=address:province, timestamp=1321586248355, value=guangdong xiaofeng column=address:town, timestamp=1321586249564, value=xianqiao xiaofeng column=info:birthday, timestamp=1321586248202, value=1987-4-17 xiaofeng column=info:company, timestamp=1321586248277, value=alibaba xiaofeng column=info:favorite, timestamp=1321586248241, value=movie 3 row(s) in 0.0570seconds5.删除id为temp的值的‘info:age’字段
hbase(main):016:0>delete 'member','temp','info:age'0 row(s) in 0.0150secondshbase(main):018:0>get 'member','temp'COLUMN CELL 0 row(s) in 0.0150seconds6.删除整行
hbase(main):001:0>deleteall 'member','xiaofeng'0 row(s) in 0.3990seconds7.查询表中有多少行：
hbase(main):019:0>count 'member' 2 row(s) in 0.0160seconds8.给”xiaofeng”这个id增加'info:age'字段，并使用counter实现递增
hbase(main):057:0*incr 'member','xiaofeng','info:age' COUNTER VALUE = 1hbase(main):058:0>get 'member','xiaofeng','info:age' COLUMN CELL info:age timestamp=1321590997648, value=x00x00x00x00x00x00x00x01 1 row(s) in 0.0140secondshbase(main):059:0>incr 'member','xiaofeng','info:age'COUNTER VALUE = 2hbase(main):060:0>get 'member','xiaofeng','info:age' COLUMN CELL info:age timestamp=1321591025110, value=x00x00x00x00x00x00x00x02 1 row(s) in 0.0160seconds获取当前count的值
hbase(main):069:0>get_counter 'member','xiaofeng','info:age' COUNTER VALUE = 29.将整张表清空：
hbase(main):035:0>truncate 'member'Truncating 'member'table (it may take a while): - Disabling table... - Dropping table... - Creating table...0 row(s) in 4.3430seconds可以看出，hbase是先将掉disable掉，然后drop掉后重建表来实现truncate的功能的。
4. 其他
导出Hbase数据
# 导出到hdfshbase org.apache.hadoop.hbase.mapreduce.Driver export member /hbase/export/member# 导出文件列表[hadoop@sunmi-hadoop-1 hbase-1.3.1]$ hdfs dfs -ls /hbase/export/memberFound 2 items-rw-r--r-- 2 hadoop supergroup 0 2017-08-01 15:11 /hbase/export/member/_SUCCESS-rw-r--r-- 2 hadoop supergroup 775 2017-08-01 15:11 /hbase/export/member/part-m-00000# 导入需要先创建表create 'member2','address','info' $ 通过导出的数据导入hbase org.apache.hadoop.hbase.mapreduce.Driver import member2 /hbase/export/member# 查询数据 get 'member2','sc utshuxue'预分区
类似于Hive的分区和桶的概念,用法如下
> create 't1', 'cf', SPLITS => ['20150501000000000', '20150515000000000', '20150601000000000']或者> create 't2', 'cf', SPLITS_FILE => '/home/hadoop/splitfile.txt'/home/hadoop/splitfile.txt中存储内容如下：201505010000000002015051500000000020150601000000000从HBase的Web UI中可以查看到表的分区
启动thrift 服务
Hbase 有两套Thrift调用方式 分别是Thrift1 和 thrift2 大部分开源和Thrift相结合的都是使用 thrift1 但是 Thrift2 是对于 thrift1 的简化 更适合编写代码中使用 可以通过指定端口的方式来同时运行两个服务 --infoport 9096 -p 9091 推荐thrift模式 thrift2 使用指定端口
PS:但是有些服务仅仅支持thrift1的协议比如我们后面要说的的
/usr/local/hbase-1.3.1/bin/hbase-daemon.sh --config /usr/local/hbase-1.3.1/conf foreground_start thrift --infoport 9096 -p 9091启动 Thrift2 服务
# 开启本机的thrift服务hbase-daemon.sh start thrift2# 开启集群其余机器thrift服务hbase-daemons.sh start thrift2使用Supervisor守护进程方式前台运行
/usr/local/hbase-1.3.1/bin/hbase-daemon.sh --config /usr/local/hbase-1.3.1/conf foreground_start thrift2注意如果程序长连接使用HBase服务会出现过一段时间断开的问题应为 超时机制 60S 超时断掉了 这个时候可以通过设置配置文件来解决,因此在conf/hbase-site.xml中添加上配置即可：
> vim /usr/local/hbase-1.3.1/conf/hbase-site.xmlhbase.thrift.server.socket.read.timeout6000000eg:milisecond服务持续运行
一般使用Supervisor来进行持续执行,当服务因为异常原因终止之后会自己拉起来,但是运行程序的一定要是前台运行的程序,Hbase主要运行hbasemaster和hbaseregionserver就可以正常提供服务了
# hbaseregionserver/usr/local/hbase-1.3.1/bin/hbase-daemon.sh --config /usr/local/hbase-1.3.1/conf foreground_start regionserver# hbasemaster/usr/local/hbase-1.3.1/bin/hbase-daemon.sh --config /usr/local/hbase-1.3.1/conf foreground_start master5 总结
经过本节的介绍大家对HBase也有了一定的了解,HBase在集群模式下能够带来更大的性能和容量优势,但是HBase在统计汇总能力比较弱,下节将介绍HBase和Hive互相结合集成Hive的结构化方便查询统计优点也结合HBase速度的优势,并且解决Hive实时写入的问题.
注:笔者能力有限有说的不对的地方希望大家能够指出,也希望多多交流!
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