2018-09-26---hbase表操作命令

创建表

create 'test1', 'lf', 'sf'

lf: column family of LONG values (binary value)

-- sf: column family of STRING values

导入数据

put 'test1', 'user1|ts1', 'sf:c1', 'sku1'

put 'test1', 'user1|ts2', 'sf:c1', 'sku188'

put 'test1', 'user1|ts3', 'sf:s1', 'sku123'

put 'test1', 'user2|ts4', 'sf:c1', 'sku2'

put 'test1', 'user2|ts5', 'sf:c2', 'sku288'

put 'test1', 'user2|ts6', 'sf:s1', 'sku222'

一个用户（userX），在什么时间（tsX），作为rowkey

对什么产品（value：skuXXX），做了什么操作作为列名，比如，c1: click from homepage; c2: click from ad; s1: search from homepage; b1: buy

查询案例

谁的值=sku188

scan 'test1', FILTER=>"ValueFilter(=,'binary:sku188')"

ROW                          COLUMN+CELL                    

user1|ts2                   column=sf:c1, timestamp=1409122354918, value=sku188

谁的值包含88

scan 'test1', FILTER=>"ValueFilter(=,'substring:88')"

ROW                          COLUMN+CELL    

user1|ts2                   column=sf:c1, timestamp=1409122354918, value=sku188

user2|ts5                   column=sf:c2, timestamp=1409122355030, value=sku288

通过广告点击进来的(column为c2)值包含88的用户

scan 'test1', FILTER=>"ColumnPrefixFilter('c2') AND ValueFilter(=,'substring:88')"

ROW                          COLUMN+CELL

user2|ts5                   column=sf:c2, timestamp=1409122355030, value=sku288

通过搜索进来的(column为s)值包含123或者222的用户

scan 'test1', FILTER=>"ColumnPrefixFilter('s') AND ( ValueFilter(=,'substring:123') OR ValueFilter(=,'substring:222') )"

ROW                          COLUMN+CELL

user1|ts3                   column=sf:s1, timestamp=1409122354954, value=sku123

user2|ts6                   column=sf:s1, timestamp=1409122355970, value=sku222

rowkey为user1开头的

scan 'test1', FILTER => "PrefixFilter ('user1')"

ROW                          COLUMN+CELL

user1|ts1                   column=sf:c1, timestamp=1409122354868, value=sku1

user1|ts2                   column=sf:c1, timestamp=1409122354918, value=sku188

user1|ts3                   column=sf:s1, timestamp=1409122354954, value=sku123

FirstKeyOnlyFilter: 一个rowkey可以有多个version,同一个rowkey的同一个column也会有多个的值, 只拿出key中的第一个column的第一个version

KeyOnlyFilter: 只要key,不要value

scan 'test1', FILTER=>"FirstKeyOnlyFilter() AND ValueFilter(=,'binary:sku188') AND KeyOnlyFilter()"

ROW                          COLUMN+CELL

user1|ts2                   column=sf:c1, timestamp=1409122354918, value=

从user1|ts2开始,找到所有的rowkey以user1开头的

scan 'test1', {STARTROW=>'user1|ts2', FILTER => "PrefixFilter ('user1')"}

ROW                          COLUMN+CELL

user1|ts2                   column=sf:c1, timestamp=1409122354918, value=sku188

user1|ts3                   column=sf:s1, timestamp=1409122354954, value=sku123

从user1|ts2开始,找到所有的到rowkey以user2开头

scan 'test1', {STARTROW=>'user1|ts2', STOPROW=>'user2'}

ROW                          COLUMN+CELL

user1|ts2                   column=sf:c1, timestamp=1409122354918, value=sku188

user1|ts3                   column=sf:s1, timestamp=1409122354954, value=sku123

查询rowkey里面包含ts3的

importorg.apache.hadoop.hbase.filter.CompareFilter

import org.apache.hadoop.hbase.filter.SubstringComparator

import org.apache.hadoop.hbase.filter.RowFilter

scan 'test1', {FILTER => RowFilter.new(CompareFilter::CompareOp.valueOf('EQUAL'), SubstringComparator.new('ts3'))}

ROW                          COLUMN+CELL

user1|ts3                   column=sf:s1, timestamp=1409122354954, value=sku123

查询rowkey里面包含ts的

importorg.apache.hadoop.hbase.filter.CompareFilter

import org.apache.hadoop.hbase.filter.SubstringComparator

import org.apache.hadoop.hbase.filter.RowFilter

scan 'test1', {FILTER => RowFilter.new(CompareFilter::CompareOp.valueOf('EQUAL'), SubstringComparator.new('ts'))}

ROW                          COLUMN+CELL

user1|ts1                   column=sf:c1, timestamp=1409122354868, value=sku1

user1|ts2                   column=sf:c1, timestamp=1409122354918, value=sku188

user1|ts3                   column=sf:s1, timestamp=1409122354954, value=sku123

user2|ts4                   column=sf:c1, timestamp=1409122354998, value=sku2

user2|ts5                   column=sf:c2, timestamp=1409122355030, value=sku288

user2|ts6                   column=sf:s1, timestamp=1409122355970, value=sku222

加入一条测试数据

put 'test1', 'user2|err', 'sf:s1', 'sku999'

查询rowkey里面以user开头的，新加入的测试数据并不符合正则表达式的规则，故查询不出来

import org.apache.hadoop.hbase.filter.RegexStringComparator

importorg.apache.hadoop.hbase.filter.CompareFilter

import org.apache.hadoop.hbase.filter.SubstringComparator

import org.apache.hadoop.hbase.filter.RowFilter

scan 'test1', {FILTER => RowFilter.new(CompareFilter::CompareOp.valueOf('EQUAL'),RegexStringComparator.new('^user\d+\|ts\d+$'))}

ROW                          COLUMN+CELL

user1|ts1                   column=sf:c1, timestamp=1409122354868, value=sku1

user1|ts2                   column=sf:c1, timestamp=1409122354918, value=sku188

user1|ts3                   column=sf:s1, timestamp=1409122354954, value=sku123

user2|ts4                   column=sf:c1, timestamp=1409122354998, value=sku2

user2|ts5                   column=sf:c2, timestamp=1409122355030, value=sku288

user2|ts6                   column=sf:s1, timestamp=1409122355970, value=sku222

加入测试数据

put 'test1', 'user1|ts9', 'sf:b1', 'sku1'

b1开头的列中并且值为sku1的

scan 'test1', FILTER=>"ColumnPrefixFilter('b1') AND ValueFilter(=,'binary:sku1')"

ROW                          COLUMN+CELL                                                                       

user1|ts9                   column=sf:b1, timestamp=1409124908668, value=sku1

SingleColumnValueFilter的使用，b1开头的列中并且值为sku1的

importorg.apache.hadoop.hbase.filter.CompareFilter

import org.apache.hadoop.hbase.filter.SingleColumnValueFilter

import org.apache.hadoop.hbase.filter.SubstringComparator

scan 'test1', {COLUMNS => 'sf:b1', FILTER => SingleColumnValueFilter.new(Bytes.toBytes('sf'), Bytes.toBytes('b1'), CompareFilter::CompareOp.valueOf('EQUAL'), Bytes.toBytes('sku1'))}

ROW                          COLUMN+CELL

user1|ts9                   column=sf:b1, timestamp=1409124908668, value=sku1

hbase zkcli 的使用

hbase zkcli

ls /

[hbase, zookeeper]

[zk: hadoop000:2181(CONNECTED) 1] ls /hbase

[meta-region-server, backup-masters, table, draining, region-in-transition, running, table-lock, master, namespace, hbaseid, online-snapshot, replication, splitWAL, recovering-regions, rs]

[zk: hadoop000:2181(CONNECTED) 2] ls /hbase/table

[member, test1, hbase:meta, hbase:namespace]

[zk: hadoop000:2181(CONNECTED) 3] ls /hbase/table/test1

[]

[zk: hadoop000:2181(CONNECTED) 4] get /hbase/table/test1

?master:60000}l$??lPBUF

cZxid = 0x107

ctime = Wed Aug 27 14:52:21 HKT 2014

mZxid = 0x10b

mtime = Wed Aug 27 14:52:22 HKT 2014

pZxid = 0x107

cversion = 0

dataVersion = 2

aclVersion = 0

ephemeralOwner = 0x0

dataLength = 31

numChildren = 0

hbase表操作命令

1、认证及进入：

kinit 命令进行认证，进入命令：hbase shell    查看当前用户（whoami）

2、展示表：

list

3、查看表结构：

describe  "table.name"

4、扫描表

scan 'table.name',{LIMIT=>5}

5、值包含8888888

scan "table.name",FILTER=>"ValueFilter(=,'binary:888888')"

6、值含有888888

scan "table.name",FILTER=>"ValueFilter(=,'substring:888888')"

7、column为：c2 的值包含 8888888

scan "table.name",FILTER=>"ColumPrefixFilter('c2') AND ValueFilter(=,'substring:88')"

8、column 为：s1 的值为包含88或者66

scan  “table.name”FILTER=>"ColumPrefixFilter('s') AND (ValueFilter(=,'substring:88'）OR ValueFilter(='substring:66')) "

9、rowkey 为user1开头的

scan 'test1' ,FILTER =>"PrefixFilter('user1')"

10、get的用法（t为表名，r为row，c为行）

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′, ‘c1′

hbase> get ‘t1′, ‘r1′, ‘c1′, ‘c2′

hbase> get ‘t1′, ‘r1′, ['c1', 'c2']

11、scan

hbase> scan ‘.META.'

hbase> scan ‘.META.', {COLUMNS => ‘info:regioninfo'}

hbase> scan ‘t1′, {COLUMNS => ['c1', 'c2'], LIMIT => 10, STARTROW => ‘xyz'}

hbase> scan ‘t1′, {COLUMNS => ‘c1′, TIMERANGE => [1303668804, 1303668904]}

hbase> scan ‘t1′, {FILTER => “(PrefixFilter (‘row2′) AND (QualifierFilter (>=, ‘binary:xyz'))) AND (TimestampsFilter ( 123, 456))”}

hbase> scan ‘t1′, {FILTER => org.apache.hadoop.hbase.filter.ColumnPaginationFilter.new(1, 0)}