5 hbase-shell +

Posted 2020-08-14 大数据和人工智能躺过的坑

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本博文的主要内容有

　　.HBase的单机模式（1节点）安装

　　.HBase的单机模式（1节点）的启动

　　.HBase的伪分布模式（1节点）安装

　　 .HBase的伪分布模式（1节点）的启动

　　 .HBase的分布模式（3、5节点）安装

　 .HBase的分布模式（3、5节点）的启动

　　　　　　见博客： HBase HA的分布式集群部署

　　　.HBase环境搭建60010端口无法访问问题解决方案

　　　　-------------　　　注意　HBase1.X版本之后，没60010了。 -------------　

　　　　　　　　参考：http://blog.csdn.net/tian_li/article/details/50601210

　　 .进入HBase Shell

　　 .为什么在HBase，需要使用zookeeper？

　　 .关于HBase的更多技术细节，强烈必多看

　　　 .获取命令列表：help帮助命令

　　　　.创建表：create命令

　　　　.向表中加入行：put命令

　　　　.从表中检索行：get命令

　　　　.读取多行：scan命令

　　　　.统计表中的行数：count命令

　　　　.删除行：delete命令

　　　　.清空表：truncate命令

　　　　.删除表:drop命令

　　　　.更换表：alter命令

想说的是，

HBase的安装包里面有自带zookeeper的。很多系统部署也是直接启动上面的zookeeper。 本来也是没有问题的，想想吧，系统里也只有hbase在用zookeeper。
先启动zookeeper，再将hbase起来就好了 。
但是今天遇到了一个很蛋疼的问题。和同事争论了很久。  因为我们是好多hbase集群共用一个zookeeper的，其中一个集群需要从hbase 0.90.2 升级到hbase 0.92上，自然，包也要更新。
但是其中一台regionserver上面同时也有跑zookeeper，而zookeeper还是用hbase 0.90.2 自带的zookeeper在跑。 
现在好了，升级一个regionserver，连着zookeeper也要受到牵连，看来必须要重启，不然，jar包替换掉，可能会影响到zk正在跑的经常。
但是重启zk毕竟对正在连接这个zk的client端会有短暂的影响。 
真是蛋疼。本来只是升级hbase，zk却强耦合了。  
虽然后来证明zookeeper只要启动了，哪怕jar包删除也不会影响到正在跑的zk进程，但是这样的不规范带来的风险，实在是没有必要。
 所以作为运维，我强烈建议zk 和hbase分开部署，就直接部署官方的zk 好了，因为zk本身就是一个独立的服务，没有必要和hbase 耦合在一起。
在分布式的系统部署上面，一个角色就用一个专门的文件夹管理，不要用同一个目录下，这样子真的容易出问题。 
当然datanode和tasktracker另当别论，他们本身关系密切。

　　当然，这里，我是玩的单节点的集群，来安装HBase而已，只是来玩玩。所以，完全，只需用HBase的安装包里自带的zookeeper就好了。

除非，是多节点的分布式集群，最好用外部的zookeeper。

HDFS的版本，不同，HBase里的内部也不一样。

http://hbase.apache.org/

https://issues.apache.org/jira/browse/HBASE/?selectedTab=com.atlassian.jira.jira-projects-plugin:summary-panel

　.HBase的单机模式安装

[hadoop@weekend110 app]$ ls
hadoop-2.4.1 hbase-0.96.2-hadoop2 hive-0.12.0 jdk1.7.0_65
[hadoop@weekend110 app]$ cd hbase-0.96.2-hadoop2/
[hadoop@weekend110 hbase-0.96.2-hadoop2]$ ls
bin CHANGES.txt conf docs hbase-webapps lib LICENSE.txt logs NOTICE.txt README.txt
[hadoop@weekend110 hbase-0.96.2-hadoop2]$ cd conf/
[hadoop@weekend110 conf]$ ls
hadoop-metrics2-hbase.properties hbase-env.cmd hbase-env.sh hbase-policy.xml hbase-site.xml log4j.properties regionservers
[hadoop@weekend110 conf]$ vim hbase-env.sh

# Tell HBase whether it should manage it\'s own instance of Zookeeper or not.
export HBASE_MANAGES_ZK=true

设HBASE_MANAGES_ZK=true，在启动HBase时，HBase把Zookeeper作为自身的一部分运行。

export JAVA_HOME=/home/hadoop/app/jdk1.7.0_65

[hadoop@weekend110 conf]$ ls
hadoop-metrics2-hbase.properties hbase-env.cmd hbase-env.sh hbase-policy.xml hbase-site.xml log4j.properties regionservers
[hadoop@weekend110 conf]$ vim hbase-site.xml

<configuration>
　　<property>
　　　　<name>hbase.rootdir</name>
　　　　<value>file:///tmp/hbase-hadoop/hbase</value>
　　</property>
　　<property>
　　　　<name>dfs.replication</name>
　　　　<value>1</value>
　　</property>
</configuration>

在这里，有些资料上说，file:///tmp/hbase-${user.name}/hbase

　　可以看到，默认情况下HBase的数据存储在根目录下的tmp文件夹下的。熟悉Linux的人知道，此文件夹为临时文件夹。也就是说，当系统重启的时候，此文件夹中的内容将被清空。这样用户保存在HBase中的数据也会丢失，这当然是用户不想看到的事情。因此，用户需要将HBase数据的存储位置修改为自己希望的存储位置。

　　比如，可以，/home/hadoop/data/hbase，当然，我这里，是因为，伪分布模式和分布式模式，都玩过了。方便，练习加强HBase的shell操作。而已，拿单机模式玩玩。

　　.HBase的单机模式的启动

总结就是：先启动hadoop集群的进程，再启动hbase的进程

[hadoop@weekend110 hbase-0.96.2-hadoop2]$ cd bin
[hadoop@weekend110 bin]$ ls
get-active-master.rb hbase-common.sh hbase-jruby region_mover.rb start-hbase.cmd thread-pool.rb
graceful_stop.sh hbase-config.cmd hirb.rb regionservers.sh start-hbase.sh zookeepers.sh
hbase hbase-config.sh local-master-backup.sh region_status.rb stop-hbase.cmd
hbase-cleanup.sh hbase-daemon.sh local-regionservers.sh replication stop-hbase.sh
hbase.cmd hbase-daemons.sh master-backup.sh rolling-restart.sh test
[hadoop@weekend110 bin]$ jps
2443 NameNode
2970 NodeManager
2539 DataNode
2729 SecondaryNameNode
2866 ResourceManager
4634 Jps
[hadoop@weekend110 bin]$ ./start-hbase.sh
starting master, logging to /home/hadoop/app/hbase-0.96.2-hadoop2/logs/hbase-hadoop-master-weekend110.out
[hadoop@weekend110 bin]$ jps
2443 NameNode
2970 NodeManager
2539 DataNode
2729 SecondaryNameNode
2866 ResourceManager
4740 HMaster
4819 Jps
[hadoop@weekend110 bin]$ hbase shell
2016-10-12 12:43:11,095 INFO [main] Configuration.deprecation: hadoop.native.lib is deprecated. Instead, use io.native.lib.available
HBase Shell; enter \'help<RETURN>\' for list of supported commands.
Type "exit<RETURN>" to leave the HBase Shell
Version 0.96.2-hadoop2, r1581096, Mon Mar 24 16:03:18 PDT 2014

hbase(main):001:0> list
TABLE
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/hadoop/app/hbase-0.96.2-hadoop2/lib/slf4j-log4j12-1.6.4.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/hadoop/app/hadoop-2.4.1/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
0 row(s) in 3.8200 seconds

=> []
hbase(main):002:0> create \'mygirls\', {NAME => \'base_info\',VERSION => 3},{NAME => \'extra_info\'}
Unknown argument ignored for column family base_info: 1.8.7
0 row(s) in 1.1560 seconds

=> Hbase::Table - mygirls
hbase(main):003:0>

测试

http://weekend110:60010/

.HBase的伪分布模式（1节点）安装

1、 hbase-0.96.2-hadoop2-bin.tar.gz压缩包的上传

sftp> cd /home/hadoop/app

sftp> put c:/hbase-0.96.2-hadoop2-bin.tar.gz

Uploading hbase-0.96.2-hadoop2-bin.tar.gz to /home/hadoop/app/hbase-0.96.2-hadoop2-bin.tar.gz

100% 77507KB 19376KB/s 00:00:04

c:/hbase-0.96.2-hadoop2-bin.tar.gz: 79367504 bytes transferred in 4 seconds (19376 KB/s)

sftp>

或者，通过

这里不多赘述。具体，可以看我的其他博客

2、 hbase-0.96.2-hadoop2-bin.tar.gz压缩包的解压

[hadoop@weekend110 app]$ ls

hadoop-2.4.1 hbase-0.96.2-hadoop2-bin.tar.gz hive-0.12.0 jdk1.7.0_65 zookeeper-3.4.6

[hadoop@weekend110 app]$ ll

total 77524

drwxr-xr-x. 11 hadoop hadoop 4096 Jul 18 20:11 hadoop-2.4.1

-rw-r--r--. 1 root root 79367504 May 20 13:51 hbase-0.96.2-hadoop2-bin.tar.gz

drwxrwxr-x. 10 hadoop hadoop 4096 Oct 10 21:30 hive-0.12.0

drwxr-xr-x. 8 hadoop hadoop 4096 Jun 17 2014 jdk1.7.0_65

drwxr-xr-x. 10 hadoop hadoop 4096 Jul 30 10:28 zookeeper-3.4.6

[hadoop@weekend110 app]$ tar -zxvf hbase-0.96.2-hadoop2-bin.tar.gz

3、删除压缩包hbase-0.96.2-hadoop2-bin.tar.gz

4、将HBase文件权限赋予给hadoop用户，这一步，不需。

5、HBase的配置

　　注意啦，在hbase-0.96.2-hadoop2的目录下，有hbase-webapps，即，说明，可以通过web网页来访问HBase。

[hadoop@weekend110 app]$ ls

hadoop-2.4.1 hbase-0.96.2-hadoop2 hive-0.12.0 jdk1.7.0_65 zookeeper-3.4.6

[hadoop@weekend110 app]$ cd hbase-0.96.2-hadoop2/

[hadoop@weekend110 hbase-0.96.2-hadoop2]$ ll

total 436

drwxr-xr-x. 4 hadoop hadoop 4096 Mar 25 2014 bin

-rw-r--r--. 1 hadoop hadoop 403242 Mar 25 2014 CHANGES.txt

drwxr-xr-x. 2 hadoop hadoop 4096 Mar 25 2014 conf

drwxr-xr-x. 27 hadoop hadoop 4096 Mar 25 2014 docs

drwxr-xr-x. 7 hadoop hadoop 4096 Mar 25 2014 hbase-webapps

drwxrwxr-x. 3 hadoop hadoop 4096 Oct 11 17:49 lib

-rw-r--r--. 1 hadoop hadoop 11358 Mar 25 2014 LICENSE.txt

-rw-r--r--. 1 hadoop hadoop 897 Mar 25 2014 NOTICE.txt

-rw-r--r--. 1 hadoop hadoop 1377 Mar 25 2014 README.txt

[hadoop@weekend110 hbase-0.96.2-hadoop2]$ cd conf/

[hadoop@weekend110 conf]$ ls

hadoop-metrics2-hbase.properties hbase-env.cmd hbase-env.sh hbase-policy.xml hbase-site.xml log4j.properties regionservers

[hadoop@weekend110 conf]$

对于，多节点里，安装HBase，这里不多说了。具体，可以看我的博客

1.上传hbase安装包

2.解压

3.配置hbase集群，要修改3个文件（首先zk集群已经安装好了）

注意：要把hadoop的hdfs-site.xml和core-site.xml 放到hbase/conf下

3.1修改hbase-env.sh

export JAVA_HOME=/usr/java/jdk1.7.0_55

//告诉hbase使用外部的zk

export HBASE_MANAGES_ZK=false

vim hbase-site.xml

<name>hbase.rootdir</name>

<value>hdfs://ns1/hbase</value>

</property>

<name>hbase.cluster.distributed</name>

</property>

<name>hbase.zookeeper.quorum</name>

<value>weekend04:2181,weekend05:2181,weekend06:2181</value>

</property>

</configuration>

vim regionservers

weekend03

weekend04

weekend05

weekend06

3.2拷贝hbase到其他节点

scp -r /weekend/hbase-0.96.2-hadoop2/ weekend02:/weekend/

scp -r /weekend/hbase-0.96.2-hadoop2/ weekend03:/weekend/

scp -r /weekend/hbase-0.96.2-hadoop2/ weekend04:/weekend/

scp -r /weekend/hbase-0.96.2-hadoop2/ weekend05:/weekend/

scp -r /weekend/hbase-0.96.2-hadoop2/ weekend06:/weekend/

4.将配置好的HBase拷贝到每一个节点并同步时间。

5.启动所有的hbase

分别启动zk

./zkServer.sh start

启动hbase集群

start-dfs.sh

启动hbase，在主节点上运行：

start-hbase.sh

6.通过浏览器访问hbase管理页面

192.168.1.201:60010

7.为保证集群的可靠性，要启动多个HMaster

hbase-daemon.sh start master

我这里，因，考虑到自己玩玩，伪分布集群里安装HBase。

hbase-env.sh

[hadoop@weekend110 conf]$ ls

hadoop-metrics2-hbase.properties hbase-env.cmd hbase-env.sh hbase-policy.xml hbase-site.xml log4j.properties regionservers

[hadoop@weekend110 conf]$ vim hbase-env.sh

/home/hadoop/app/jdk1.7.0_65

单节点的hbase-env.sh，需要修改2处。

export JAVA_HOME=/home/hadoop/app/jdk1.7.0_65

export HBASE_MANAGES_ZK=false

.为什么在HBase，需要使用zookeeper？

　　大家，很多人，都有一个疑问，为什么在HBase，需要使用zookeeper？至于为什么最好使用外部安装的zookeeper，而不是HBase自带的zookeeper，这里，我实在是不多赘述了。

　　zookeeper存储的是HBase中ROOT表和META表的位置。此外，zookeeper还负责监控多个机器的状态（每台机器到zookeeper中注册一个实例）。当某台机器发生故障时

，zookeeper会第一时间感知到，并通知HBase Master进行相应的处理。同时，当HBase Master发生故障的时候，zookeeper还负责HBase Master的恢复工作，能够保证还在同一时刻系统中只有一台HBase Master提供服务。

　　具体例子，见

HBase HA的分布式集群部署的最低端。

hbase-site.xml

[hadoop@weekend110 conf]$ ls

hadoop-metrics2-hbase.properties hbase-env.cmd hbase-env.sh hbase-policy.xml hbase-site.xml log4j.properties regionservers

[hadoop@weekend110 conf]$ vim hbase-site.xml

<name>hbase.zookeeper.property.dataDir</name>

<value>/home/hadoop/data/zookeeper/zkdata</value>

</property>

<name>hbase.tmp.dir</name>

<value>/home/hadoop/data/tmp/hbase</value>

</property>

<name>hbase.zookeeper.property.clientPort</name>

</property>

<name>hbase.rootdir</name>

<value>hdfs://weekend110:9000/hbase</value>

</property>

<name>hbase.cluster.distributed</name>

<value>false</value>

</property>

<name>dfs.replication</name>

</property>

</configuration>

新建目录

/home/hadoop/data/zookeeper/zkdata

/home/hadoop/data/tmp/hbase

[hadoop@weekend110 conf]$ pwd

/home/hadoop/app/hbase-0.96.2-hadoop2/conf

[hadoop@weekend110 conf]$ mkdir -p /home/hadoop/data/zookeeper/zkdata

[hadoop@weekend110 conf]$ mkdir -p /home/hadoop/data/tmp/hbase

[hadoop@weekend110 conf]$

regionservers

weekend110

[hadoop@weekend110 conf]$ ls

hadoop-metrics2-hbase.properties hbase-env.cmd hbase-env.sh hbase-policy.xml hbase-site.xml log4j.properties regionservers

[hadoop@weekend110 conf]$ cp /home/hadoop/app/hadoop-2.4.1/etc/hadoop/{core-site.xml,hdfs-site.xml} ./

[hadoop@weekend110 conf]$ ls

core-site.xml hbase-env.cmd hbase-policy.xml hdfs-site.xml regionservers

hadoop-metrics2-hbase.properties hbase-env.sh hbase-site.xml log4j.properties

[hadoop@weekend110 conf]$

vi /etc/profile

[hadoop@weekend110 conf]$ su root

Password:

[root@weekend110 conf]# vim /etc/profile

export JAVA_HOME=/home/hadoop/app/jdk1.7.0_65

export HADOOP_HOME=/home/hadoop/app/hadoop-2.4.1

export ZOOKEEPER_HOME=/home/hadoop/app/zookeeper-3.4.6

export HIVE_HOME=/home/hadoop/app/hive-0.12.0

export HBASE_HOME=/home/hadoop/app/hbase-0.96.2-hadoop2

export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$ZOOKEEPER_HOME/bin:$HIVE_HOME/bin:$HBASE_HOME/bin

[root@weekend110 conf]# source /etc/profile

[root@weekend110 conf]# su hadoop

.HBase的伪分布模式的启动

由于伪分布模式的运行基于HDFS，因此在运行HBase之前首先需要启动HDFS，

[hadoop@weekend110 hadoop-2.4.1]$ jps

5802 Jps

[hadoop@weekend110 hadoop-2.4.1]$ sbin/start-all.sh

This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh

Starting namenodes on [weekend110]

weekend110: starting namenode, logging to /home/hadoop/app/hadoop-2.4.1/logs/hadoop-hadoop-namenode-weekend110.out

weekend110: starting datanode, logging to /home/hadoop/app/hadoop-2.4.1/logs/hadoop-hadoop-datanode-weekend110.out

Starting secondary namenodes [0.0.0.0]

0.0.0.0: starting secondarynamenode, logging to /home/hadoop/app/hadoop-2.4.1/logs/hadoop-hadoop-secondarynamenode-weekend110.out

starting yarn daemons

starting resourcemanager, logging to /home/hadoop/app/hadoop-2.4.1/logs/yarn-hadoop-resourcemanager-weekend110.out

weekend110: starting nodemanager, logging to /home/hadoop/app/hadoop-2.4.1/logs/yarn-hadoop-nodemanager-weekend110.out

[hadoop@weekend110 hadoop-2.4.1]$ jps

6022 DataNode

6149 SecondaryNameNode

5928 NameNode

6287 ResourceManager

6426 Jps

6387 NodeManager

[hadoop@weekend110 hadoop-2.4.1]$

[hadoop@weekend110 hbase-0.96.2-hadoop2]$ pwd

/home/hadoop/app/hbase-0.96.2-hadoop2

[hadoop@weekend110 hbase-0.96.2-hadoop2]$ ls

bin CHANGES.txt conf docs hbase-webapps lib LICENSE.txt NOTICE.txt README.txt

[hadoop@weekend110 hbase-0.96.2-hadoop2]$ cd bin

[hadoop@weekend110 bin]$ ls

get-active-master.rb hbase-common.sh hbase-jruby region_mover.rb start-hbase.cmd thread-pool.rb

graceful_stop.sh hbase-config.cmd hirb.rb regionservers.sh start-hbase.sh zookeepers.sh

hbase hbase-config.sh local-master-backup.sh region_status.rb stop-hbase.cmd

hbase-cleanup.sh hbase-daemon.sh local-regionservers.sh replication stop-hbase.sh

hbase.cmd hbase-daemons.sh master-backup.sh rolling-restart.sh test

[hadoop@weekend110 bin]$ ./start-hbase.sh

starting master, logging to /home/hadoop/app/hbase-0.96.2-hadoop2/logs/hbase-hadoop-master-weekend110.out

[hadoop@weekend110 bin]$ jps

6022 DataNode

6149 SecondaryNameNode

5928 NameNode

6707 Jps

6287 ResourceManager

6530 HMaster

6387 NodeManager

[hadoop@weekend110 bin]$

http://weekend110:60010/

参考博客：http://blog.csdn.net/u013575812/article/details/46919011

[hadoop@weekend110 bin]$ pwd

/home/hadoop/app/hbase-0.96.2-hadoop2/bin

[hadoop@weekend110 bin]$ hadoop dfsadmin -safemode leave

DEPRECATED: Use of this script to execute hdfs command is deprecated.

Instead use the hdfs command for it.

Safe mode is OFF

[hadoop@weekend110 bin]$ jps

6022 DataNode

7135 Jps

6149 SecondaryNameNode

5928 NameNode

6287 ResourceManager

6387 NodeManager

[hadoop@weekend110 bin]$ ./start-hbase.sh

starting master, logging to /home/hadoop/app/hbase-0.96.2-hadoop2/logs/hbase-hadoop-master-weekend110.out

[hadoop@weekend110 bin]$ jps

6022 DataNode

7245 HMaster

6149 SecondaryNameNode

5928 NameNode

6287 ResourceManager

6387 NodeManager

7386 Jps

[hadoop@weekend110 bin]$

依旧如此，继续...解决!

参考博客:http://www.th7.cn/db/nosql/201510/134214.shtml

　　在安装hbase-0.96.2-hadoop2时发现一个问题，hbase能够正常使用，hbase shell 完全可用，但是60010页面却打不开，最后找到问题，是因为很多版本的hbase的master web 默认是不运行的，所以需要自己配置默认端口。

配置如下

　　在hbase-site.xml中加入一下内容即可

　　　　<property>
　　　　　　<name>hbase.master.info.port</name>
　　　　　　<value>60010</value>
　　　　</property>

　　　 <property>
　　　　　　<name>hbase.regionserver .info.port</name>
　　　　　　<value>60020</value>
　　　　</property>

<configuration>
　　<property>
　　　　<name>hbase.zookeeper.property.dataDir</name>
　　　　<value>/home/hadoop/data/zookeeper/zkdata</value>
　　</property>
　　<property>
　　　　<name>hbase.tmp.dir</name>
　　　　<value>/home/hadoop/data/tmp/hbase</value>
　　</property>
　　<property>
　　　　<name>hbase.zookeeper.property.clientPort</name>
　　　　<value>2181</value>
　　</property>
　　<property>
　　　　<name>hbase.master.info.port</name>
　　　　<value>60010</value>
　　</property>
　　<property>
　　　　<name>hbase.regionserver.info.port</name>
　　　　<value>60020</value>
　　</property>
　　<property>
　　　　<name>hbase.rootdir</name>
　　　　<value>hdfs://weekend110:9000/hbase</value>
　　</property>
　　<property>
　　　　<name>hbase.cluster.distributed</name>
　　　　<value>false</value>
　　</property>
　　<property>
　　　　<name>dfs.replication</name>
　　　　<value>1</value>
　　</property>
</configuration>

进入HBase Shell

进入hbase命令行
./hbase shell

显示hbase中的表
list

创建user表，包含info、data两个列族
create \'user\', \'info1\', \'data1\'
create \'user\', {NAME => \'info\', VERSIONS => \'3\'}

向user是表中插入信息，row key是rk0001，列族是info中添加name是列修饰符（标识符），值是zhangsan
put \'user\', \'rk0001\', \'info:name\', \'zhangsan\'

向user表中插入信息，row key是rk0001，列族info中添加gender列标示符，值是female
put \'user\', \'rk0001\', \'info:gender\', \'female\'

向user表中插入信息，row key是rk0001，列族info中添加age列标示符，值是20
put \'user\', \'rk0001\', \'info:age\', 20

向user表中插入信息，row key是rk0001，列族data中添加pic列标示符，值是picture
put \'user\', \'rk0001\', \'data:pic\', \'picture\'

获取user表中row key为rk0001的所有信息
get \'user\', \'rk0001\'

获取user表中row key是rk0001，info列族的所有信息
get \'user\', \'rk0001\', \'info\'

获取user表中row key是rk0001，info列族的name、age列标示符的信息
get \'user\', \'rk0001\', \'info:name\', \'info:age\'

获取user表中row key是rk0001，info、data列族的信息
get \'user\', \'rk0001\', \'info\', \'data\'
get \'user\', \'rk0001\', {COLUMN => [\'info\', \'data\']}

get \'user\', \'rk0001\', {COLUMN => [\'info:name\', \'data:pic\']}

获取user表中row key是rk0001，列族是info，版本号最新5个的信息
get \'user\', \'rk0001\', {COLUMN => \'info\', VERSIONS => 2}
get \'user\', \'rk0001\', {COLUMN => \'info:name\', VERSIONS => 5}
get \'user\', \'rk0001\', {COLUMN => \'info:name\', VERSIONS => 5, TIMERANGE => [1392368783980, 1392380169184]}

获取user表中row key是rk0001，cell的值是zhangsan的信息
get \'people\', \'rk0001\', {FILTER => "ValueFilter(=, \'binary:图片\')"}

获取user表中row key是rk0001，列标示符中含有a的信息
get \'people\', \'rk0001\', {FILTER => "(QualifierFilter(=,\'substring:a\'))"}

put \'user\', \'rk0002\', \'info:name\', \'fanbingbing\'
put \'user\', \'rk0002\', \'info:gender\', \'female\'
put \'user\', \'rk0002\', \'info:nationality\', \'中国\'
get \'user\', \'rk0002\', {FILTER => "ValueFilter(=, \'binary:中国\')"}

查询user表中的所有信息
scan \'user\'

查询user表中列族为info的信息
scan \'user\', {COLUMNS => \'info\'}
scan \'user\', {COLUMNS => \'info\', RAW => true, VERSIONS => 5}
scan \'persion\', {COLUMNS => \'info\', RAW => true, VERSIONS => 3}
查询user表中列族为info和data的信息
scan \'user\', {COLUMNS => [\'info\', \'data\']}
scan \'user\', {COLUMNS => [\'info:name\', \'data:pic\']}

查询user表中列族是info、列标示符是name的信息
scan \'user\', {COLUMNS => \'info:name\'}

查询user表中列族是info、列标示符是name的信息,并且版本最新的5个
scan \'user\', {COLUMNS => \'info:name\', VERSIONS => 5}

查询user表中列族为info和data且列标示符中含有a字符的信息
scan \'user\', {COLUMNS => [\'info\', \'data\'], FILTER => "(QualifierFilter(=,\'substring:a\'))"}

查询user表中列族为info，rk范围是[rk0001, rk0003)的数据
scan \'people\', {COLUMNS => \'info\', STARTROW => \'rk0001\', ENDROW => \'rk0003\'}

查询user表中row key以rk字符开头的
scan \'user\',{FILTER=>"PrefixFilter(\'rk\')"}

查询user表中指定范围的数据
scan \'user\', {TIMERANGE => [1392368783980, 1392380169184]}

删除user表row key为rk0001，列标示符为info:name的数据
delete \'people\', \'rk0001\', \'info:name\'
删除user表row key为rk0001，列标示符为info:name，timestamp为1392383705316的数据
delete \'user\', \'rk0001\', \'info:name\', 1392383705316

清空user表中的数据
truncate \'people\'

修改表结构
首先停用user表（新版本不用）
disable \'user\'

添加两个列族f1和f2
alter \'people\', NAME => \'f1\'
alter \'user\', NAME => \'f2\'
启用表
enable \'user\'

###disable \'user\'(新版本不用)
删除一个列族：
alter \'user\', NAME => \'f1\', METHOD => \'delete\' 或 alter \'user\', \'delete\' => \'f1\'

添加列族f1同时删除列族f2
alter \'user\', {NAME => \'f1\'}, {NAME => \'f2\', METHOD => \'delete\'}

将user表的f1列族版本号改为5
alter \'people\', NAME => \'info\', VERSIONS => 5
启用表
enable \'user\'

删除表
disable \'user\'
drop \'user\'

get \'person\', \'rk0001\', {FILTER => "ValueFilter(=, \'binary:中国\')"}
get \'person\', \'rk0001\', {FILTER => "(QualifierFilter(=,\'substring:a\'))"}
scan \'person\', {COLUMNS => \'info:name\'}
scan \'person\', {COLUMNS => [\'info\', \'data\'], FILTER => "(QualifierFilter(=,\'substring:a\'))"}
scan \'person\', {COLUMNS => \'info\', STARTROW => \'rk0001\', ENDROW => \'rk0003\'}

scan \'person\', {COLUMNS => \'info\', STARTROW => \'20140201\', ENDROW => \'20140301\'}
scan \'person\', {COLUMNS => \'info:name\', TIMERANGE => [1395978233636, 1395987769587]}
delete \'person\', \'rk0001\', \'info:name\'

alter \'person\', NAME => \'ffff\'
alter \'person\', NAME => \'info\', VERSIONS => 10

get \'user\', \'rk0002\', {COLUMN => [\'info:name\', \'data:pic\']}

[hadoop@weekend110 bin]$ pwd
/home/hadoop/app/hbase-0.96.2-hadoop2/bin
[hadoop@weekend110 bin]$ ./hbase shell
2016-10-12 10:09:42,925 INFO [main] Configuration.deprecation: hadoop.native.lib is deprecated. Instead, use io.native.lib.available
HBase Shell; enter \'help<RETURN>\' for list of supported commands.
Type "exit<RETURN>" to leave the HBase Shell
Version 0.96.2-hadoop2, r1581096, Mon Mar 24 16:03:18 PDT 2014

hbase(main):001:0>

hbase(main):001:0> help
HBase Shell, version 0.96.2-hadoop2, r1581096, Mon Mar 24 16:03:18 PDT 2014
Type \'help "COMMAND"\', (e.g. \'help "get"\' -- the quotes are necessary) for help on a specific command.
Commands are grouped. Type \'help "COMMAND_GROUP"\', (e.g. \'help "general"\') for help on a command group.

COMMAND GROUPS: //罗列出了所有的命令
Group name: general //通常命令，这些命令将返回集群级的通用信息。
Commands: status, table_help, version, whoami

Group name: ddl //ddl操作命令，这些命令会创建、更换和删除HBase表
Commands: alter, alter_async, alter_status, create, describe, disable, disable_all, drop, drop_all, enable, enable_all, exists, get_table, is_disabled, is_enabled, list, show_filters

Group name: namespace //namespace命令
Commands: alter_namespace, create_namespace, describe_namespace, drop_namespace, list_namespace, list_namespace_tables

Group name: dml　　　　　　//dml操作命令，这些命令会新增、修改和删除HBase表中的数据
Commands: count, delete, deleteall, get, get_counter, incr, put, scan, truncate, truncate_preserve

Group name: tools　　　　 //tools命令，这些命令可以维护HBase集群
Commands: assign, balance_switch, balancer, catalogjanitor_enabled, catalogjanitor_run, catalogjanitor_switch, close_region, compact, flush, hlog_roll, major_compact, merge_region, move, split, trace, unassign, zk_dump

Group name: replication　　　　//replication命令，这些命令可以增加和删除集群的节点
Commands: add_peer, disable_peer, enable_peer, list_peers, list_replicated_tables, remove_peer

Group name: snapshot　　　　 //snapshot命令，这些命令用于对HBase集群进行快照以便备份和恢复集群
Commands: clone_snapshot, delete_snapshot, list_snapshots, rename_snapshot, restore_snapshot, snapshot

Group name: security　　　　　　//security命令，这些命令可以控制HBase的安全性
Commands: grant, revoke, user_permission

SHELL USAGE:
Quote all names in HBase Shell such as table and column names. Commas delimit
command parameters. Type <RETURN> after entering a command to run it.
Dictionaries of configuration used in the creation and alteration of tables are
Ruby Hashes. They look like this:

{\'key1\' => \'value1\', \'key2\' => \'value2\', ...}

and are opened and closed with curley-braces. Key/values are delimited by the
\'=>\' character combination. Usually keys are predefined constants such as
NAME, VERSIONS, COMPRESSION, etc. Constants do not need to be quoted. Type
\'Object.constants\' to see a (messy) list of all constants in the environment.

If you are using binary keys or values and need to enter them in the shell, use
double-quote\'d hexadecimal representation. For example:

hbase> get \'t1\', "key\\x03\\x3f\\xcd"
hbase> get \'t1\', "key\\003\\023\\011"
hbase> put \'t1\', "test\\xef\\xff", \'f1:\', "\\x01\\x33\\x40"

The HBase shell is the (J)Ruby IRB with the above HBase-specific commands added.
For more on the HBase Shell, see http://hbase.apache.org/docs/current/book.html
hbase(main):002:0>

hbase(main):002:0> version
0.96.2-hadoop2, r1581096, Mon Mar 24 16:03:18 PDT 2014

hbase(main):003:0> create

ERROR: wrong number of arguments (0 for 1)

Here is some help for this command:
Creates a table. Pass a table name, and a set of column family
specifications (at least one), and, optionally, table configuration.
Column specification can be a simple string (name), or a dictionary
(dictionaries are described below in main help output), necessarily
including NAME attribute.
Examples: //这里，有例子

Create a table with namespace=ns1 and table qualifier=t1
hbase> create \'ns1:t1\', {NAME => \'f1\', VERSIONS => 5}

Create a table with namespace=default and table qualifier=t1
hbase> create \'t1\', {NAME => \'f1\'}, {NAME => \'f2\'}, {NAME => \'f3\'}
hbase> # The above in shorthand would be the following:
hbase> create \'t1\', \'f1\', \'f2\', \'f3\'
hbase> create \'t1\', {NAME => \'f1\', VERSIONS => 1, TTL => 2592000, BLOCKCACHE => true}
hbase> create \'t1\', {NAME => \'f1\', CONFIGURATION => {\'hbase.hstore.blockingStoreFiles\' => \'10\'}}

Table configuration options can be put at the end.
Examples: //这里，有例子

hbase> create \'ns1:t1\', \'f1\', SPLITS => [\'10\', \'20\', \'30\', \'40\']
hbase> create \'t1\', \'f1\', SPLITS => [\'10\', \'20\', \'30\', \'40\']
hbase> create \'t1\', \'f1\', SPLITS_FILE => \'splits.txt\', OWNER => \'johndoe\'
hbase> create \'t1\', {NAME => \'f1\', VERSIONS => 5}, METADATA => { \'mykey\' => \'myvalue\' }
hbase> # Optionally pre-split the table into NUMREGIONS, using
hbase> # SPLITALGO ("HexStringSplit", "UniformSplit" or classname)
hbase> create \'t1\', \'f1\', {NUMREGIONS => 15, SPLITALGO => \'HexStringSplit\'}
hbase> create \'t1\', \'f1\', {NUMREGIONS => 15, SPLITALGO => \'HexStringSplit\', CONFIGURATION => {\'hbase.hregion.scan.loadColumnFamiliesOnDemand\' => \'true\'}}

You can also keep around a reference to the created table:

hbase> t1 = create \'t1\', \'f1\'

Which gives you a reference to the table named \'t1\', on which you can then
call methods.

hbase(main):004:0>

[hadoop@weekend110 bin]$ jps
2443 NameNode
2970 NodeManager
7515 Jps
2539 DataNode
2729 SecondaryNameNode
2866 ResourceManager
[hadoop@weekend110 bin]$ pwd
/home/hadoop/app/hbase-0.96.2-hadoop2/bin
[hadoop@weekend110 bin]$ ./start-hbase.sh
starting master, logging to /home/hadoop/app/hbase-0.96.2-hadoop2/logs/hbase-hadoop-master-weekend110.out
[hadoop@weekend110 bin]$ jps
2443 NameNode
7623 HMaster
2970 NodeManager
2539 DataNode
2729 SecondaryNameNode
2866 ResourceManager
7686 Jps
[hadoop@weekend110 bin]$ ./hbase shell
2016-10-12 15:53:46,394 INFO [main] Configuration.deprecation: hadoop.native.lib is deprecated. Instead, use io.native.lib.available
HBase Shell; enter \'help<RETURN>\' for list of supported commands.
Type "exit<RETURN>" to leave the HBase Shell
Version 0.96.2-hadoop2, r1581096, Mon Mar 24 16:03:18 PDT 2014

=> []
hbase(main):002:0> create \'mygirls\', {NAME => \'base_info\',VERSIONS => 3},{NAME => \'extra_info\'}
0 row(s) in 1.1080 seconds

=> Hbase::Table - mygirls
hbase(main):003:0>

describe

hbase(main):010:0> describe \'mygirls\'
DESCRIPTION ENABLED
\'mygirls\', {NAME => \'base_info\', DATA_BLOCK_ENCODING => \'NONE\', BLOOMFILTER => \'ROW\', true
REPLICATION_SCOPE => \'0\', VERSIONS => \'3\', COMPRESSION => \'NONE\', MIN_VERSIONS => \'0
\', TTL => \'2147483647\', KEEP_DELETED_CELLS => \'false\', BLOCKSIZE => \'65536\', IN_MEMOR
Y => \'false\', BLOCKCACHE => \'true\'}, {NAME => \'extra_info\', DATA_BLOCK_ENCODING => \'N
ONE\', BLOOMFILTER => \'ROW\', REPLICATION_SCOPE => \'0\', VERSIONS => \'1\', COMPRESSION =>
\'NONE\', MIN_VERSIONS => \'0\', TTL => \'2147483647\', KEEP_DELETED_CELLS => \'false\', BLO
CKSIZE => \'65536\', IN_MEMORY => \'false\', BLOCKCACHE => \'true\'}
1 row(s) in 0.0980 seconds

hbase(main):011:0>

disable 和 drop ，先得disable（下线），再才能drop（删掉）

hbase(main):002:0> disable \'mygirls\'
0 row(s) in 1.2030 seconds

hbase(main):003:0> drop \'mygirls\'
0 row(s) in 0.4270 seconds

hbase(main):004:0>

put

hbase(main):011:0> put

ERROR: wrong number of arguments (0 for 4)

Here is some help for this command:
Put a cell \'value\' at specified table/row/column and optionally
timestamp coordinates. To put a cell value into table \'ns1:t1\' or \'t1\'
at row \'r1\' under column \'c1\' marked with the time \'ts1\', do:

hbase> put \'ns1:t1\', \'r1\', \'c1\', \'value\', ts1 //例子

The same commands also can be run on a table reference. Suppose you had a reference
t to table \'t1\', the corresponding command would be:

hbase> t.put \'r1\', \'c1\', \'value\', ts1 //例子

hbase(main):012:0> put \'mygirls\',\'0001\',\'base_info:name\',\'fengjie\'
0 row(s) in 0.3240 seconds

hbase(main):013:0> put \'mygirls\',\'0001\',\'base_info:age\',\'18\'
0 row(s) in 0.0170 seconds

hbase(main):014:0> put \'mygirls\',\'0001\',\'base_info:sex\',\'jipinnvren\'
0 row(s) in 0.0130 seconds

hbase(main):015:0> put \'mygirls\',\'0001\',\'base_info:boyfriend\',\'huangxiaoming\'
0 row(s) in 0.0590 seconds

get

hbase(main):016:0> get

ERROR: wrong number of arguments (0 for 2)

Here is some help for this command:
Get row or cell contents; pass table name, row, and optionally
a dictionary of column(s), timestamp, timerange and versions. Examples: //例子

hbase> get \'ns1:t1\', \'r1\'
hbase> get \'t1\', \'r1\'
hbase> get \'t1\', \'r1\', {TIMERANGE => [ts1, ts2]}
hbase> get \'t1\', \'r1\', {COLUMN => \'c1\'}
hbase> get \'t1\', \'r1\', {COLUMN => [\'c1\', \'c2\', \'c3\']}
hbase> get \'t1\', \'r1\', {COLUMN => \'c1\', TIMESTAMP => ts1}
hbase> get \'t1\', \'r1\', {COLUMN => \'c1\', TIMERANGE => [ts1, ts2], VERSIONS => 4}
hbase> get \'t1\', \'r1\', {COLUMN => \'c1\', TIMESTAMP => ts1, VERSIONS => 4}
hbase> get \'t1\', \'r1\', {FILTER => "ValueFilter(=, \'binary:abc\')"}
hbase> get \'t1\', \'r1\', \'c1\'
hbase> get \'t1\', \'r1\', \'c1\', \'c2\'
hbase> get \'t1\', \'r1\', [\'c1\', \'c2\']

Besides the default \'toStringBinary\' format, \'get\' also supports custom formatting by
column. A user can define a FORMATTER by adding it to the column name in the get
specification. The FORMATTER can be stipulated:

1. either as a org.apache.hadoop.hbase.util.Bytes method name (e.g, toInt, toString)
2. or as a custom class followed by method name: e.g. \'c(MyFormatterClass).format\'.

Example formatting cf:qualifier1 and cf:qualifier2 both as Integers:
hbase> get \'t1\', \'r1\' {COLUMN => [\'cf:qualifier1:toInt\',
\'cf:qualifier2:c(org.apache.hadoop.hbase.util.Bytes).toInt\'] }

Note that you can specify a FORMATTER by column only (cf:qualifer). You cannot specify
a FORMATTER for all columns of a column family.

The same commands also can be run on a reference to a table (obtained via get_table or
create_table). Suppose you had a reference t to table \'t1\', the corresponding commands
would be:

hbase> t.get \'r1\'
hbase> t.get \'r1\', {TIMERANGE => [ts1, ts2]}
hbase> t.get \'r1\', {COLUMN => \'c1\'}
hbase> t.get \'r1\', {COLUMN => [\'c1\', \'c2\', \'c3\']}
hbase> t.get \'r1\', {COLUMN => \'c1\', TIMESTAMP => ts1}
hbase> t.get \'r1\', {COLUMN => \'c1\', TIMERANGE => [ts1, ts2], VERSIONS => 4}
hbase> t.get \'r1\', {COLUMN => \'c1\', TIMESTAMP => ts1, VERSIONS => 4}
hbase> t.get \'r1\', {FILTER => "ValueFilter(=, \'binary:abc\')"}
hbase> t.get \'r1\', \'c1\'
hbase> t.get \'r1\', \'c1\', \'c2\'
hbase> t.get \'r1\', [\'c1\', \'c2\']

hbase(main):017:0>

hbase(main):017:0> get \'mygirls\',\'0001\'
COLUMN CELL
base_info:age timestamp=1476259587999, value=18
base_info:boyfriend timestamp=1476259597469, value=huangxiaoming
base_info:name timestamp=1476259582217, value=fengjie
base_info:sex timestamp=1476259593138, value=jipinnvren
4 row(s) in 0.0320 seconds

hbase(main):018:0> put \'mygirls\',\'0001\',\'base_info:name\',\'fengbaobao\'
0 row(s) in 0.0140 seconds

hbase(main):019:0> get \'mygirls\',\'0001\'
COLUMN CELL
base_info:age timestamp=1476259587999, value=18
base_info:boyfriend timestamp=1476259597469, value=huangxiaoming
base_info:name timestamp=1476259871197, value=fengbaobao
base_info:sex timestamp=1476259593138, value=jipinnvren
4 row(s) in 0.0480 seconds

hbase(main):020:0> get \'mygirls\',\'0001\',{COLUMN => \'base_info:name\',VERSIONS => 10}
COLUMN CELL
base_info:name timestamp=1476259871197, value=fengbaobao
base_info:name timestamp=1476259582217, value=fengjie
2 row(s) in 0.0700 seconds

得到，2个版本。意思是，最多可得到10个版本

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