hbase shell之常用过滤器设置

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转载来源：http://www.cnblogs.com/luogankun/p/3939712.html

HBase基础之常用过滤器hbase shell操作

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

import org.apache.hadoop.hbase.filter.CompareFilterimport org.apache.hadoop.hbase.filter.SubstringComparatorimport org.apache.hadoop.hbase.filter.RowFilterscan '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

import org.apache.hadoop.hbase.filter.CompareFilterimport org.apache.hadoop.hbase.filter.SubstringComparatorimport org.apache.hadoop.hbase.filter.RowFilterscan '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.RegexStringComparatorimport org.apache.hadoop.hbase.filter.CompareFilterimport org.apache.hadoop.hbase.filter.SubstringComparatorimport org.apache.hadoop.hbase.filter.RowFilterscan '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

import org.apache.hadoop.hbase.filter.CompareFilterimport org.apache.hadoop.hbase.filter.SingleColumnValueFilterimport org.apache.hadoop.hbase.filter.SubstringComparatorscan '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 zkclils /[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$??lPBUFcZxid = 0x107ctime = Wed Aug 27 14:52:21 HKT 2014mZxid = 0x10bmtime = Wed Aug 27 14:52:22 HKT 2014pZxid = 0x107cversion = 0dataVersion = 2aclVersion = 0ephemeralOwner = 0x0dataLength = 31numChildren = 0

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