hadoop 2.2 +hbase 0.98 利用自还zookeeper 实现单机伪分布集成

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是一个分布式的、面向列的开源数据库,源于google的一篇论文《bigtable:一个结构化数据的分布式存储系统》。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。
hadoop 2.2.0 与hbase 0.96 集成时一直不成功,hbase 0.96 单机也不成功,今天下载了hbase0.98 ,将 原来hbase-0.96.2-hadoop1的配置文件 cp  hbase-0.98.4-hadoop2/conf

启动,进行命令,运行命令,成功。
配置文件 内容:
hbase-site.xml
<configuration>
  <property>
      <name>hbase.rootdir</name>
          <value>hdfs://localhost:9000/hbase</value>  //此处根据实际情况配置
  </property>
  <property>
      <name>hbase.zookeeper.property.dataDir</name>
      <value>/home/hadoop/zookeeper</value>
  </property>
<property>
  <name>hbase.cluster.distributed </name>
  <value>true</value>
</property>
</configuration>

hbase-env.sh
export JAVA_HOME=/usr/java/jdk1.7.0_65
export HBASE_CLASSPATH=$HADOOP_HOME/conf
export HBASE_OPTS="-XX:+UseConcMarkSweepGC"
export HBASE_MANAGES_ZK=true

启动过程及
[hadoop@localhost Downloads]$ cd hbase-0.98.4-hadoop2
[hadoop@localhost hbase-0.98.4-hadoop2]$ ls
bin  CHANGES.txt  conf  docs  hbase-webapps  lib  LICENSE.txt  NOTICE.txt  README.txt
[hadoop@localhost hbase-0.98.4-hadoop2]$ ./bin/start-hbase.sh
localhost: starting zookeeper, logging to /home/hadoop/Downloads/hbase-0.98.4-hadoop2/bin/../logs/hbase-hadoop-zookeeper-localhost.out
starting master, logging to /home/hadoop/Downloads/hbase-0.98.4-hadoop2/bin/../logs/hbase-hadoop-master-localhost.out
localhost: starting regionserver, logging to /home/hadoop/Downloads/hbase-0.98.4-hadoop2/bin/../logs/hbase-hadoop-regionserver-localhost.out
[hadoop@localhost hbase-0.98.4-hadoop2]$ ./bin/hbase shell
2014-08-02 00:03:00,946 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 0.98.4-hadoop2, r890e852ce1c51b71ad180f626b71a2a1009246da, Mon Jul 14 19:45:06 PDT 2014

hbase(main):001:0> list
TABLE                                                                                                                                
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/hadoop/Downloads/hbase-0.98.4-hadoop2/lib/slf4j-log4j12-1.6.4.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/hadoop/hadoop-2.2.0/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 2.6480 seconds

=> []
hbase(main):002:0>  create 'test', 'cf'
0 row(s) in 0.9590 seconds

=> Hbase::Table - test
hbase(main):003:0> list
TABLE                                                                                                                                
test                                                                                                                                 
1 row(s) in 0.0530 seconds

=> ["test"]
hbase(main):004:0> status
1 servers, 0 dead, 3.0000 average load

(1)建立一个表scores,有两个列族grad和courese
复制代码 代码如下:

hbase(main):001:0> create ‘scores','grade', ‘course'

可以使用list命令来查看当前HBase里有哪些表。使用describe命令来查看表结构。(记得所有的表明、列名都需要加上引号)

(2)按设计的表结构插入值:
复制代码 代码如下:

put ‘scores','Tom','grade:','5′
put ‘scores','Tom','course:math','97′
put ‘scores','Tom','course:art','87′
put ‘scores','Jim','grade','4′
put ‘scores','Jim','course:','89′
put ‘scores','Jim','course:','80′

这样表结构就起来了,其实比较自由,列族里边可以自由添加子列很方便。如果列族下没有子列,加不加冒号都是可以的。

put命令比较简单,只有这一种用法:
hbase> put ‘t1′, ‘r1′, ‘c1′, ‘value', ts1

t1指表名,r1指行键名,c1指列名,value指单元格值。ts1指时间戳,一般都省略掉了。

(3)根据键值查询数据

get ‘scores','Jim'
get ‘scores','Jim','grade'

可能你就发现规律了,HBase的shell操作,一个大概顺序就是操作关键词后跟表名,行名,列名这样的一个顺序,如果有其他条件再用花括号加上。
get有用法如下:

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']

(4)扫描所有数据

scan ‘scores'

也可以指定一些修饰词:TIMERANGE, FILTER, LIMIT, STARTROW, STOPROW, TIMESTAMP, MAXLENGTH,or COLUMNS。没任何修饰词,就是上边例句,就会显示所有数据行。

例句如下:
复制代码 代码如下:

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)}


过滤器filter有两种方法指出:

a. Using a filterString – more information on this is available in the
Filter Language document attached to the HBASE-4176 JIRA
b. Using the entire package name of the filter.

还有一个CACHE_BLOCKS修饰词,开关scan的缓存的,默认是开启的(CACHE_BLOCKS=>true),可以选择关闭(CACHE_BLOCKS=>false)。

(5)删除指定数据
复制代码 代码如下:

delete ‘scores','Jim','grade'
delete ‘scores','Jim'

删除数据命令也没太多变化,只有一个:

hbase> delete ‘t1′, ‘r1′, ‘c1′, ts1

另外有一个deleteall命令,可以进行整行的范围的删除操作,慎用!
如果需要进行全表删除操作,就使用truncate命令,其实没有直接的全表删除命令,这个命令也是disable,drop,create三个命令组合出来的。

(6)修改表结构
复制代码 代码如下:

disable ‘scores'
alter ‘scores',NAME=>'info'
enable ‘scores'

alter命令使用如下(如果无法成功的版本,需要先通用表disable):
a、改变或添加一个列族:

hbase> alter ‘t1′, NAME => ‘f1′, VERSIONS => 5

b、删除一个列族:
复制代码 代码如下:

hbase> alter ‘t1′, NAME => ‘f1′, METHOD => ‘delete'
hbase> alter ‘t1′, ‘delete' => ‘f1′

c、也可以修改表属性如MAX_FILESIZE
MEMSTORE_FLUSHSIZE, READONLY,和 DEFERRED_LOG_FLUSH:
hbase> alter ‘t1′, METHOD => ‘table_att', MAX_FILESIZE => '134217728′
d、可以添加一个表协同处理器

hbase> alter ‘t1′, METHOD => ‘table_att', ‘coprocessor'=> ‘hdfs:///foo.jar|com.foo.FooRegionObserver|1001|arg1=1,arg2=2′

一个表上可以配置多个协同处理器,一个序列会自动增长进行标识。加载协同处理器(可以说是过滤程序)需要符合以下规则:

[coprocessor jar file location] | class name | [priority] | [arguments]

e、移除coprocessor如下:

hbase> alter ‘t1′, METHOD => ‘table_att_unset', NAME => ‘MAX_FILESIZE'
hbase> alter ‘t1′, METHOD => ‘table_att_unset', NAME => ‘coprocessor$1′

f、可以一次执行多个alter命令:

hbase> alter ‘t1′, {NAME => ‘f1′}, {NAME => ‘f2′, METHOD => ‘delete'}

(7)统计行数:
复制代码 代码如下:

hbase> count ‘t1′
hbase> count ‘t1′, INTERVAL => 100000
hbase> count ‘t1′, CACHE => 1000
hbase> count ‘t1′, INTERVAL => 10, CACHE => 1000

count一般会比较耗时,使用mapreduce进行统计,统计结果会缓存,默认是10行。统计间隔默认的是1000行(INTERVAL)。

(8)disable 和 enable 操作
很多操作需要先暂停表的可用性,比如上边说的alter操作,删除表也需要这个操作。disable_all和enable_all能够操作更多的表。

(9)表的删除
先停止表的可使用性,然后执行删除命令。

drop ‘t1′

以上是一些常用命令详解,具体的所有hbase的shell命令如下,分了几个命令群,看英文是可以看出大概用处的,详细的用法使用help “cmd” 进行了解。

复制代码 代码如下:

COMMAND GROUPS:
Group name: general
Commands: status, version

Group name: ddl
Commands: alter, alter_async, alter_status, create, describe, disable, disable_all, drop, drop_all,
enable, enable_all, exists, is_disabled, is_enabled, list, show_filters

Group name: dml
Commands: count, delete, deleteall, get, get_counter, incr, put, scan, truncate

Group name: tools
Commands: assign, balance_switch, balancer, close_region, compact, flush, hlog_roll, major_compact,
move, split, unassign, zk_dump

Group name: replication
Commands: add_peer, disable_peer, enable_peer, list_peers, remove_peer, start_replication,
stop_replication

Group name: security
Commands: grant, revoke, user_permission

4. hbase shell脚本
既然是shell命令,当然也可以把所有的hbase shell命令写入到一个文件内,想linux shell脚本程序那样去顺序的执行所有命令。如同写linux shell,把所有hbase shell命令书写在一个文件内,然后执行如下命令即可:
复制代码 代码如下:

$ hbase shell test.hbaseshell

方便好用。

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