Hbase常用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 => 'info1', VERSIONS => '3'}

向user表中插入信息，row key为rk0001，列族info中添加name列标示符，值为zhangsan
put 'user', 'rk0001', 'info:name', 'zhangsan'

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

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

向user表中插入信息，row key为rk0001，列族data中添加pic列标示符，值为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为rk0001，info列族的所有信息
get 'user', 'rk0001', 'info'

获取user表中row key为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为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为rk0001，列族为info，版本号最新5个的信息
get 'people', 'rk0002', {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为rk0001，cell的值为zhangsan的信息
get 'people', 'rk0001', {FILTER => "ValueFilter(=, 'binary:图片')"}

获取user表中row key为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 'people', {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表中列族为info、列标示符为name的信息
scan 'user', {COLUMNS => 'info:name'}

查询user表中列族为info、列标示符为name的信息,并且版本最新的5个
scan 'users', {COLUMNS => 'info:age', 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 'people', {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]}

删除数据
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'

//值过滤器
get 'person', 'rk0001', {FILTER => "ValueFilter(=, 'binary:中国')"}
get 'users', 'zhangyifei', {FILTER => "ValueFilter(=, 'binary:china')"}
//字段过滤器
get 'person', 'rk0001', {FILTER => "(QualifierFilter(=,'substring:a'))"}
get 'users', 'zhangyifei', {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'}
//行健区间查询
scan 'person', {COLUMNS => 'info', STARTROW => '20140201', ENDROW => '20140301'}
//时间区间查询
scan 'person', {COLUMNS => 'info:name', TIMERANGE => [1395978233636, 1395987769587]}
scan 'users', {COLUMNS => 'info:name', TIMERANGE => [1429757594916, 1429757594885]}
delete 'person', 'rk0001', 'info:name'
//添加列族
alter 'person', NAME => 'ffff'
//修改列族的版本号
alter 'users', NAME => 'info', VERSIONS => 10
 

get 'user', 'rk0002', {COLUMN => ['info:name', 'data:pic']}
 scan 'users', {COLUMNS => 'info',RAW => true, VERSIONS => 3

}

Hbase行健过滤

1.使用startRow和stopRow进行行健过滤

2.使用rowFilter(,regx)正则进行rowKey过滤

Hbase常用过滤器:

    行健过滤器RowFilter 

单列值过滤器SingleColumnValueFilter

注:过滤器可以使用过滤器list

条件是一个枚举变量

new FilterList( Operator.MUST_PASS_ALL , rowFilters )

Hbase添加java自定义过滤器

import org.apache.hadoop.hbase.filter.CompareFilter
import org.apache.hadoop.hbase.filter.SingleColumnValueFilter
import org.apache.hadoop.hbase.filter.SubstringComparator
import org.apache.hadoop.hbase.util.Bytes
scan 't_mec_ide_bind', { COLUMNS => 'mecIde:MNO', FILTER =>SingleColumnValueFilter.new(Bytes.toBytes('mecIde'),Bytes.toBytes('MNO'),CompareFilter::CompareOp.valueOf('EQUAL'),Bytes.toBytes("836581050460151"))}




echo "import org.apache.hadoop.hbase.filter.CompareFilter
import org.apache.hadoop.hbase.filter.SingleColumnValueFilter
import org.apache.hadoop.hbase.filter.SubstringComparator
import org.apache.hadoop.hbase.util.Bytes
scan 't_mec_ide_bind', { COLUMNS => 'mecIde:MNO', FILTER =>SingleColumnValueFilter.new(Bytes.toBytes('mecIde'),Bytes.toBytes('MNO'),CompareFilter::CompareOp.valueOf('EQUAL'),Bytes.toBytes("836581050460151"))}" | hbase shell > myText




echo "import org.apache.hadoop.hbase.filter.CompareFilter
import org.apache.hadoop.hbase.filter.SingleColumnValueFilter
import org.apache.hadoop.hbase.filter.SubstringComparator
import org.apache.hadoop.hbase.util.Bytes
scan 't_mec_ide_bind', { COLUMNS => 'mecIde:MNO', FILTER =>SingleColumnValueFilter.new(Bytes.toBytes('mecIde'),Bytes.toBytes('MNO'),CompareFilter::CompareOp.valueOf('EQUAL'),Bytes.toBytes("700000000000521"))}" | hbase shell > myText