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[HBase] hbase的基本操作 (一)_hbase操作
作者：很楠不爱3 | 2024-04-28 13:13:33
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hbase操作
HBase是一个分布式的、面向列的开源数据库。HBase是Google Bigtable的开源实现，它利用Hadoop HDFS作为其文件存储系统，利用Hadoop MapReduce来处理HBase中的海量数据，利用Zookeeper作为协同服务。
Hbase的组成结构可用表形容：
hbase是一张表：表中有一个唯一键是 row key, 每个row key 对应 N（N >= 1）个列族。每个列族由N个列组成（N>=1）。
1.创表
create ‘table’, ‘column_family_1’,‘column_family_2’,‘column_family_3’…
hbase(main):032:0> create 'hbase_test','column_family_1', 'column_family_2', 'column_family_3'
0 row(s) in 1.2620 seconds
=> Hbase::Table - hbase_test
hbase(main):033:0>
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创表的关键字是**create，”hbase_test”**是表名；”column_family_1”，”column_family_2”，”column_family_3”是三个不同的列族名。
2.删除表
相应的，删除表可用drop命令：
表创建成功后，默认状态是enable，即“使用中”的状态，删除表之前需先设置表为“关闭中”。
设置表为“使用中”：enable ‘hbase_test’
设置表为“关闭中”：disable ‘hbase_test’
disable 'hbase_test'
drop 'hbase_test'
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依次执行上述命令，可删除表成功。
3.查看所有表
可用list 命令查看当前创建的表：
list
hbase(main):026:0> list
TABLE
ai_ns:testtable
demo
dmp:hbase_tags
emp
fund1
hbase_tags
hbase_test
hbase_weitest
jemp
scores
test1
11 row(s) in 0.1130 seconds
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4.查看表结构
可使用describe命令查看表结构，其规范为：
describe ‘table’
hbase(main):033:0> describe 'hbase_test'
Table hbase_test is ENABLED
hbase_test
COLUMN FAMILIES DESCRIPTION
{NAME => 'column_family_1', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE',
MIN_VERSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'}
{NAME => 'column_family_2', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE',
MIN_VERSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'}
{NAME => 'column_family_3', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE',
MIN_VERSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'}
3 row(s) in 0.0290 seconds
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5.是否
exists 'user':是否存在
is_enbaled 'user':是否启用
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6.插入与更新数据
如何插入数据呢？较为普遍的方法是put命令，其命令规范为：
put ‘table’, ‘row key’, ‘column_family:column’, ‘value’
hbase(main):007:0> put 'hbase_test','key_1','column_family_1:column_1','value1'
0 row(s) in 0.1710 seconds
hbase(main):008:0> put 'hbase_test','key_1','column_family_1:column_2','value2'
0 row(s) in 0.0150 seconds
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查看创表过程，相比也知道”hbase_test”是表名；’key_1’ 是row key；’column_family_1:column_1’ 是列族以及列族对应的列，中间用”:”分隔；’value1’ 是”colum_1”这个列的值。表格的其他数据，可以用此方法全部插入：
put 'hbase_test','key_2','column_family_1:column_1','value4'
put 'hbase_test','key_2','column_family_1:column_2','value5'
put 'hbase_test','key_3','column_family_1:column_2','value5'
put 'hbase_test','key_4','column_family_1:column_1','value1'
put 'hbase_test','key_4','column_family_2:column_3','value3'
put 'hbase_test','key_4','column_family_3:','value1'
put 'hbase_test','key_4','column_family_3:','value1'
put 'hbase_test','key_5','column_family_1:column_1','value1'
put 'hbase_test','key_5','column_family_2:column_3','value4'
put 'hbase_test','key_5','column_family_3:','value2'
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put方法可以插入新数据，同样也运用于更新，使用方法与上述一致。
当然，put方法类似的还有很多，但大同小异，可以使用help "put"命令查看：
hbase(main):046:0> help "put"
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'
hbase> put 't1', 'r1', 'c1', 'value'
hbase> put 't1', 'r1', 'c1', 'value', ts1
hbase> put 't1', 'r1', 'c1', 'value', {ATTRIBUTES=>{'mykey'=>'myvalue'}}
hbase> put 't1', 'r1', 'c1', 'value', ts1, {ATTRIBUTES=>{'mykey'=>'myvalue'}}
hbase> put 't1', 'r1', 'c1', 'value', ts1, {VISIBILITY=>'PRIVATE|SECRET'}
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, {ATTRIBUTES=>{'mykey'=>'myvalue'}}
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7.读取数据（get）
以上这样的插入数据方式，很容易联想到获取数据是否也是类似格式呢？
没错，获取数据get 命令与之相似：
获得表名为hbase_test的row_key为key_1的全部数据。
hbase(main):020:0> get 'hbase_test','key_1'
COLUMN CELL
column_family_1:column_1 timestamp=1534259899359, value=value1
column_family_1:column_2 timestamp=1534259904389, value=value2
2 row(s) in 0.0220 seconds
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同样的，类似的get方法还有别的，用help "get"命令查看：
hbase(main):047:0> help "get"
Get row or cell contents; pass table name, row, and optionally
a dictionary of column(s), timestamp, timerange and versions. Examples:
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']
hbase> get 't1', 'r1', {COLUMN => 'c1', ATTRIBUTES => {'mykey'=>'myvalue'}}
hbase> get 't1', 'r1', {COLUMN => 'c1', AUTHORIZATIONS => ['PRIVATE','SECRET']}
hbase> get 't1', 'r1', {CONSISTENCY => 'TIMELINE'}
hbase> get 't1', 'r1', {CONSISTENCY => 'TIMELINE', REGION_REPLICA_ID => 1}
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8.读取数据（scan）
使用get命令虽然方便，但是终究只是某一个row key下的数据，若需要查看所有数据，明显不能满足我们工作需求。别急，还可以使用scan命令查看数据：
scan ‘hbase_test’
hbase(main):021:0> scan 'hbase_test'
ROW COLUMN+CELL
key_1 column=column_family_1:column_1, timestamp=1534259899359, value=value1
key_1 column=column_family_1:column_2, timestamp=1534259904389, value=value2
key_2 column=column_family_1:column_1, timestamp=1534259909024, value=value4
key_2 column=column_family_1:column_2, timestamp=1534259913358, value=value5
key_3 column=column_family_1:column_2, timestamp=1534259917322, value=value5
key_4 column=column_family_1:column_1, timestamp=1534259924209, value=value1
key_4 column=column_family_2:column_3, timestamp=1534259928680, value=value3
key_4 column=column_family_3:, timestamp=1534259936240, value=value1
key_5 column=column_family_1:column_1, timestamp=1534259939697, value=value1
key_5 column=column_family_2:column_3, timestamp=1534259943330, value=value4
key_5 column=column_family_3:, timestamp=1534259947358, value=value2
5 row(s) in 0.0420 seconds
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以上为获取某张表的所有数据，若只需取’column_family_1’列族下的数据，则：
scan ‘hbase_test’,{COLUMN => ‘column_family_1’}
hbase(main):002:0> scan 'hbase_test',{COLUMN => 'column_family_1'}
ROW COLUMN+CELL
key_1 column=column_family_1:column_1, timestamp=1534259899359, value=value1
key_1 column=column_family_1:column_2, timestamp=1534259904389, value=value2
key_2 column=column_family_1:column_1, timestamp=1534259909024, value=value4
key_2 column=column_family_1:column_2, timestamp=1534259913358, value=value5
key_3 column=column_family_1:column_2, timestamp=1534259917322, value=value5
key_4 column=column_family_1:column_1, timestamp=1534259924209, value=value1
key_5 column=column_family_1:column_1, timestamp=1534259939697, value=value1
5 row(s) in 0.0330 seconds
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上述表达式 等同于 scan ‘hbase_test’,{COLUMN => [‘column_family_1’]}
若需取’column_family_1’，’column_family_2’多列列族数据：
scan ‘hbase_test’,{COLUMN => [‘column_family_1’,‘column_family_2’]}
hbase(main):004:0> scan 'hbase_test',{COLUMN => ['column_family_1', 'column_family_2']}
ROW COLUMN+CELL
key_1 column=column_family_1:column_1, timestamp=1534259899359, value=value1
key_1 column=column_family_1:column_2, timestamp=1534259904389, value=value2
key_2 column=column_family_1:column_1, timestamp=1534259909024, value=value4
key_2 column=column_family_1:column_2, timestamp=1534259913358, value=value5
key_3 column=column_family_1:column_2, timestamp=1534259917322, value=value5
key_4 column=column_family_1:column_1, timestamp=1534259924209, value=value1
key_4 column=column_family_2:column_3, timestamp=1534259928680, value=value3
key_5 column=column_family_1:column_1, timestamp=1534259939697, value=value1
key_5 column=column_family_2:column_3, timestamp=1534259943330, value=value4
5 row(s) in 0.0270 seconds
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再细致一点，你可能会有获取’column_family_1’列族下，’column_1’列的数据：
hbase(main):005:0> scan 'hbase_test',{COLUMN => ['column_family_1:column_1']}
ROW COLUMN+CELL
key_1 column=column_family_1:column_1, timestamp=1534259899359, value=value1
key_2 column=column_family_1:column_1, timestamp=1534259909024, value=value4
key_4 column=column_family_1:column_1, timestamp=1534259924209, value=value1
key_5 column=column_family_1:column_1, timestamp=1534259939697, value=value1
4 row(s) in 0.0190 seconds
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同样的，多列数据可以这样获取：
hbase(main):006:0> scan 'hbase_test',{COLUMN => ['column_family_1:column_1','column_family_2:column_3']}
ROW COLUMN+CELL
key_1 column=column_family_1:column_1, timestamp=1534259899359, value=value1
key_2 column=column_family_1:column_1, timestamp=1534259909024, value=value4
key_4 column=column_family_1:column_1, timestamp=1534259924209, value=value1
key_4 column=column_family_2:column_3, timestamp=1534259928680, value=value3
key_5 column=column_family_1:column_1, timestamp=1534259939697, value=value1
key_5 column=column_family_2:column_3, timestamp=1534259943330, value=value4
4 row(s) in 0.0390 seconds
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若要获取row key 大于等于某key的情况：
hbase(main):007:0> scan 'hbase_test',{COLUMN => ['column_family_1:column_1','column_family_2:column_3'], STARTROW => 'key_2'}
ROW COLUMN+CELL
key_2 column=column_family_1:column_1, timestamp=1534259909024, value=value4
key_4 column=column_family_1:column_1, timestamp=1534259924209, value=value1
key_4 column=column_family_2:column_3, timestamp=1534259928680, value=value3
key_5 column=column_family_1:column_1, timestamp=1534259939697, value=value1
key_5 column=column_family_2:column_3, timestamp=1534259943330, value=value4
3 row(s) in 0.0210 seconds
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同样，获取row key 小于某key的情况：
hbase(main):008:0> scan 'hbase_test',{COLUMN => ['column_family_1:column_1','column_family_2:column_3'], STOPROW => 'key_2'}
ROW COLUMN+CELL
key_1 column=column_family_1:column_1, timestamp=1534259899359, value=value1
1 row(s) in 0.0330 seconds
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大于等于key_2，小于key_5：
hbase(main):009:0> scan 'hbase_test',{COLUMN => ['column_family_1:column_1','column_family_2:column_3'], STARTROW => 'key_2', STOPROW => 'key_5'}
ROW COLUMN+CELL
key_2 column=column_family_1:column_1, timestamp=1534259909024, value=value4
key_4 column=column_family_1:column_1, timestamp=1534259924209, value=value1
key_4 column=column_family_2:column_3, timestamp=1534259928680, value=value3
2 row(s) in 0.0180 seconds
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上述要注意关键字STARTROW与STOPROW稍有区别，STARTROW后的row key 是包含在内，而STOPROW后的row key 则是不包含的关系，相当于“左闭右开”的关系。
使用scan 命令扫描一张表的数据时，我们常常会限制下输出row key条数：
scan ‘hbase_test’,{LIMIT => 2}
hbase(main):013:0> scan 'hbase_test', {LIMIT => 2}
ROW COLUMN+CELL
key_1 column=column_family_1:column_1, timestamp=1534259899359, value=value1
key_1 column=column_family_1:column_2, timestamp=1534259904389, value=value2
key_2 column=column_family_1:column_1, timestamp=1534259909024, value=value4
key_2 column=column_family_1:column_2, timestamp=1534259913358, value=value5
2 row(s) in 0.0190 seconds
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看到上述输出你可能会懵，明明是 “LIMIT => 2” 为什么会返回四条数据，前面说了，row key 是唯一主键，这个限制的数量是针对主键row key的。
若想以反序获取两行数据：
hbase(main):016:0> scan 'hbase_test', {LIMIT => 2, REVERSED => true}
ROW COLUMN+CELL
key_5 column=column_family_1:column_1, timestamp=1534259939697, value=value1
key_5 column=column_family_2:column_3, timestamp=1534259943330, value=value4
key_5 column=column_family_3:, timestamp=1534259947358, value=value2
key_4 column=column_family_1:column_1, timestamp=1534259924209, value=value1
key_4 column=column_family_2:column_3, timestamp=1534259928680, value=value3
key_4 column=column_family_3:, timestamp=1534259936240, value=value1
2 row(s) in 0.0390 seconds
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不要疑惑为什么不是与scan ‘hbase_test’, {LIMIT => 2}数据的输出内容不一致。默认情况下REVERSED => false,当设置REVERSED => true时，数据反向读取2行，自然与之前不一致。可以理解为mysql中select * from dual asc limit 2与select * from dual desc limit 2这样的区别。
scan的更多使用方法可用**help ‘scan’**查看：
hbase(main):025:0> help 'scan'
Scan a table; pass table name and optionally a dictionary of scanner
specifications. Scanner specifications may include one or more of:
TIMERANGE, FILTER, LIMIT, STARTROW, STOPROW, ROWPREFIXFILTER, TIMESTAMP,
MAXLENGTH or COLUMNS, CACHE or RAW, VERSIONS, ALL_METRICS or METRICS
If no columns are specified, all columns will be scanned.
To scan all members of a column family, leave the qualifier empty as in
'col_family'.
The filter can be specified in two ways:
1. Using a filterString - more information on this is available in the
Filter Language document attached to the HBASE-4176 JIRA
2. Using the entire package name of the filter.
If you wish to see metrics regarding the execution of the scan, the
ALL_METRICS boolean should be set to true. Alternatively, if you would
prefer to see only a subset of the metrics, the METRICS array can be
defined to include the names of only the metrics you care about.
Some examples:
hbase> scan 'hbase:meta'
hbase> scan 'hbase:meta', {COLUMNS => 'info:regioninfo'}
hbase> scan 'ns1:t1', {COLUMNS => ['c1', 'c2'], LIMIT => 10, STARTROW => 'xyz'}
hbase> scan 't1', {COLUMNS => ['c1', 'c2'], LIMIT => 10, STARTROW => 'xyz'}
hbase> scan 't1', {COLUMNS => 'c1', TIMERANGE => [1303668804, 1303668904]}
hbase> scan 't1', {REVERSED => true}
hbase> scan 't1', {ALL_METRICS => true}
hbase> scan 't1', {METRICS => ['RPC_RETRIES', 'ROWS_FILTERED']}
hbase> scan 't1', {ROWPREFIXFILTER => 'row2', FILTER => "
(QualifierFilter (>=, 'binary:xyz')) AND (TimestampsFilter ( 123, 456))"}
hbase> scan 't1', {FILTER =>
org.apache.hadoop.hbase.filter.ColumnPaginationFilter.new(1, 0)}
hbase> scan 't1', {CONSISTENCY => 'TIMELINE'}
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9.删除数据（delete）
难免有数据插入不当的情况，可用delete命令删除：
delete ‘hbase_test’,‘key_1’,‘column_family_3’
hbase(main):027:0> put 'hbase_test','key_6','column_family_3:','value6'
0 row(s) in 0.1020 seconds
hbase(main):028:0> get 'hbase_test','key_6','column_family_3:'
COLUMN CELL
column_family_3: timestamp=1534305060905, value=value6
1 row(s) in 0.0190 seconds
hbase(main):029:0> delete 'hbase_test','key_6','column_family_3:'
0 row(s) in 0.0520 seconds
hbase(main):030:0> get 'hbase_test','key_6','column_family_3:'
COLUMN CELL
0 row(s) in 0.0110 seconds
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10.删除数据（deleteall）
delete这个方法只能删除具体到哪一行中的某个列族下的某一列数据，想要删除一整行数据，需用deleteall命令：
deleteall ‘hbase_test’,‘key_1’
hbase(main):041:0> put 'hbase_test','key_7','column_family_3:','value7'
0 row(s) in 0.0150 seconds
hbase(main):042:0> put 'hbase_test','key_7','column_family_2:column_3','value9'
0 row(s) in 0.0130 seconds
hbase(main):043:0> get 'hbase_test','key_7'
COLUMN CELL
column_family_2:column_3 timestamp=1534305920535, value=value9
column_family_3: timestamp=1534305915794, value=value7
2 row(s) in 0.0110 seconds
hbase(main):044:0> deleteall 'hbase_test','key_7'
0 row(s) in 0.0110 seconds
hbase(main):045:0> get 'hbase_test','key_7'
COLUMN CELL
0 row(s) in 0.0090 seconds
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若需删除整张表的数据，可用truncate命令：
truncate ‘hbase_test’
hbase(main):050:0> truncate 'hbase_test'
Truncating 'hbase_test' table (it may take a while):
- Disabling table...
- Truncating table...
0 row(s) in 3.4050 seconds
hbase(main):051:0> scan 'hbase_test'
ROW COLUMN+CELL
0 row(s) in 0.3380 seconds
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11.获取数据get
get 'hbase_test','key_1',{COLUMN => 'info:age',VERSIONS=>1}
获取版本号为1
get 'hbase_test','key_1',{COLUMN => 'info:age',VERSIONS=>2}
获取版本号为2
get 'hbase_test','key_1',{COLUMN => 'info:age',VERSIONS=>3}
获取版本号为3
get 'hbase_test','key_1',{COLUMN => 'info:age',TIMESTAMP=13467489999}
获取时间戳为1346789999
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12.执行脚本
hbase 与 hive一样，都是可以直接执行脚本的。比如之前的put 命令，一个个填写复制粘贴写数据很麻烦，我可以全部put 命令放在一个文件中：
如上，执行完毕后，查看命令是否已正确执行，插入数据：
hbase(main):052:0> scan 'hbase_test'
ROW COLUMN+CELL
key_1 column=column_family_1:column_1, timestamp=1534306889023, value=value1
key_1 column=column_family_1:column_2, timestamp=1534306889072, value=value2
key_2 column=column_family_1:column_1, timestamp=1534306889078, value=value4
key_2 column=column_family_1:column_2, timestamp=1534306889083, value=value5
key_3 column=column_family_1:column_2, timestamp=1534306889093, value=value5
key_4 column=column_family_1:column_1, timestamp=1534306889099, value=value1
key_4 column=column_family_2:column_3, timestamp=1534306889104, value=value3
key_4 column=column_family_3:, timestamp=1534306889116, value=value1
key_5 column=column_family_1:column_1, timestamp=1534306889122, value=value1
key_5 column=column_family_2:column_3, timestamp=1534306889128, value=value4
key_5 column=column_family_3:, timestamp=1534306889144, value=value2
5 row(s) in 0.0270 seconds
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