Hadoop之HBASE
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HBase是一个开源的、分布式的，多版本的，面向列的，半结构化的NoSql数据库，提供高性能的随机读写结构化数据的能力。它可以直接使用本地文件系统，也可以使用Hadoop的HDFS文件存储系统。不过，为了提高数据的可靠性和系统的健壮性，并且发挥HBase处理大数据的能力，使用HDFS作为文件存储系统才更为稳妥。
HBase存储的数据从逻辑上来看就像一张很大的表，并且它的数据列可以根据需要动态地增加。除此之外，每个单元（cell，由行和列所确定的位置）中的数据又可以具有多个版本（通过时间戳来区别）。从下图可以看出，HBase还具有这样的特点：它向下提供了存储，向上提供了运算。另外，在HBase之上还可以使用Hadoop的MapReduce计算模型来并行处理大规模数据，这也是它具有强大性能的核心所在。它将数据存储与并行计算完美地结合在一起。
HBase 和 HDFS
HDFS
HBase
HDFS是适于存储大容量文件的分布式文件系统。
HBase是建立在HDFS之上的数据库。
HDFS不支持快速单独记录查找。
HBase提供在较大的表快速查找。
它提供了高延迟批量处理;没有批处理概念。
它提供了数十亿条记录低延迟访问单个行记录（随机存取）。
它提供的数据只能顺序访问。
HBase内部使用哈希表和提供随机接入，并且其存储索引，可将在HDFS文件中的数据进行快速查找。
HBASE表具有以下特点：
大：一个表可以有上亿行，上百万列
面向列：面向列(族)的存储和权限控制，列(族)独立检索。
稀疏：对于为空(null)的列，并不占用存储空间，因此，表可以设计的非常稀疏。
HBase以表的形式存储数据。表有行和列组成。列划分为若干个列族(row family)。下面是HBASE表的逻辑视图：
在shell客户端展示：
> scan 'member'
ROW COLUMN+CELL lisi column=address:, timestamp=1567757931802, value=sichuan lisi column=info:, timestamp=1567757982455, value=info2
lisi column=info:love, timestamp=1567758039091, value=movie lisi column=school:, timestamp=1567758005941, value=xinhua zhangsan column=address:city, timestamp=1567755403595, value=beijing zhangsan column=info:, timestamp=1567755827530, value=info1 zhangsan column=info:age, timestamp=1567756662127, value=26
zhangsan column=info:birthday, timestamp=1567755398376, value=1993-11-20 zhangsan column=info:country, timestamp=1567755402535, value=china zhangsan column=school:, timestamp=1567757294341, value=shiyan 2 row(s)
Took 0.0945 seconds下面依次介绍这些结构：
Row key：用来检索记录的主键，类似key-value结构的key。访问hbase table的行，只有三种方式：
通过单个row key访问；
通过row key的range；
全表扫描；
列族：hbase表中的每个列，都属于某个列族，列族属于表结构（必须在使用表之前定义），列不属于（插入数据的时候可以随时添加列），比如上面的info，address，school这些属于列族，info:age，info:love这些属于列。
Cell：row key和列以及时间戳唯一确定的单元，用来存储真实的数据，cell中的数据没有类型，全部是字节码形式存储。
时间戳：每个cell中保存着同一份数据的多个版本，版本通过时间戳来索引。为了避免数据存在过多版本造成的的管理 (包括存贮和索引)负担，hbase提供了两种数据版本回收方式。一是保存数据的最后n个版本，二是保存最近一段时间内的版本（比如最近七天）。用户可以针对每个列族进行设置。
wget http://apache.01link.hk/hbase/2.2.0/hbase-2.2.0-bin.tar.gz
tar -zxvf hbase-2.2.0-bin.tar.gz
cd hbase-2.2.0
vim conf/hbase-site.xml
＜configuration＞
<property>
<name>hbase.rootdir</name>
<value>file:///tmp/hbase-${user.name}/hbase</value>
</property>
＜/configuration＞
# 单机模式运行，使用的是本次文件存储。不依赖Hadoop
./bin/start-hbase.sh
# 查看进程
jps
9758 HMaster
# 启动成功后可以在 http://localhost:16010 访问hbase的web页面
# 停止Hbase服务
./bin/stop-hbase.sh
# 进入HBASE shell
./bin/hbase shell
HBase Shell
Use "help" to get list of supported commands.
Use "exit" to quit this interactive shell.
For Reference, please visit: http://hbase.apache.org/2.0/book.html#shell
Version 2.2.0, rUnknown, Tue Jun 11 04:30:30 UTC 2019
Took 0.0128 seconds
hbase(main):001:0># 建表
> create 'member','member_id','address','info'
Created table member
Took 1.6592 seconds
=> Hbase::Table - member
# 列出所有表
> list
TABLE
member
1 row(s)
Took 0.1501 seconds
=> ["member"]
# 列出表描述
> describe 'member'
Table member is ENABLED member COLUMN FAMILIES DESCRIPTION {NAME => 'address', VERSIONS => '1', EVICT_BLOCKS_ON_CLOSE => 'false', NEW_VERSION_BEHAVIOR => 'false', KEEP_DELETED_CELLS => 'FALSE', CACHE_DATA_ON_WRITE => 'false', DATA_BLOCK_ENCODING => 'NO
NE', TTL => 'FOREVER', MIN_VERSIONS => '0', REPLICATION_SCOPE => '0', BLOOMFILTER => 'ROW', CACHE_INDEX_ON_WRITE => 'false', IN_MEMORY => 'false', CACHE_BLOOMS_ON_WRITE => 'false', PREFETCH_BLO
CKS_ON_OPEN => 'false', COMPRESSION => 'NONE', BLOCKCACHE => 'true', BLOCKSIZE => '65536'}
{NAME => 'info', VERSIONS => '1', EVICT_BLOCKS_ON_CLOSE => 'false', NEW_VERSION_BEHAVIOR => 'false', KEEP_DELETED_CELLS => 'FALSE', CACHE_DATA_ON_WRITE => 'false', DATA_BLOCK_ENCODING => 'NONE'
, TTL => 'FOREVER', MIN_VERSIONS => '0', REPLICATION_SCOPE => '0', BLOOMFILTER => 'ROW', CACHE_INDEX_ON_WRITE => 'false', IN_MEMORY => 'false', CACHE_BLOOMS_ON_WRITE => 'false', PREFETCH_BLOCKS
_ON_OPEN => 'false', COMPRESSION => 'NONE', BLOCKCACHE => 'true', BLOCKSIZE => '65536'}
{NAME => 'member_id', VERSIONS => '1', EVICT_BLOCKS_ON_CLOSE => 'false', NEW_VERSION_BEHAVIOR => 'false', KEEP_DELETED_CELLS => 'FALSE', CACHE_DATA_ON_WRITE => 'false', DATA_BLOCK_ENCODING => '
NONE', TTL => 'FOREVER', MIN_VERSIONS => '0', REPLICATION_SCOPE => '0', BLOOMFILTER => 'ROW', CACHE_INDEX_ON_WRITE => 'false', IN_MEMORY => 'false', CACHE_BLOOMS_ON_WRITE => 'false', PREFETCH_B
LOCKS_ON_OPEN => 'false', COMPRESSION => 'NONE', BLOCKCACHE => 'true', BLOCKSIZE => '65536'}
3 row(s)
QUOTAS
0 row(s)
Took 0.6478 seconds
# 删除一个列族，alter，disable，enable
> alter 'member',{NAME=>'member_id',METHOD=>'delete'}
# 在用describe 查看表会发现只有两个列族了
# 删除一个表,首先要先disable这个表
> disable 'member'
> drop 'member'
# 表是否存在
> exists 'member'
# 判断表是否enable
> is_enabled 'member'
# 判断表是否disable
> is_disabled 'member'# 插入数据
put'member','zhangsan','info:age','24'
put'member','zhangsan','info:birthday','1993-11-20'
put'member','zhangsan','info:country','china'
put'member','zhangsan','address:city','beijing'
put'member','lisi','info:birthday','1998-09-09'
put'member','lisi','info:favotite','movie'
put'member','lisi','address:city','beijing'
# 获取一个id的所有数据
> get'member','zhangsan'
COLUMN CELL address:city timestamp=1567754003312, value=beijing info:age timestamp=1567753903167, value=24 info:birthday timestamp=1567753950339, value=1993-11-20 info:country timestamp=1567753964169, value=china 1 row(s)
Took 0.1351 seconds
# 获取一个id，一个列族的所有数据
> get'member','zhangsan','info'
COLUMN CELL info:age timestamp=1567753903167, value=24 info:birthday timestamp=1567753950339, value=1993-11-20 info:country timestamp=1567753964169, value=china 1 row(s)
Took 0.0455 seconds
# 获取一个id，一个列族中一个列的所有数据
> get'member','zhangsan','info:age'
COLUMN CELL info:age timestamp=1567753903167, value=24 1 row(s)
Took 0.0364 seconds
# 更新一条记录
> put'member','zhangsan','info:age','25'
> get'member','zhangsan','info:age'
COLUMN CELL info:age timestamp=1567754315161, value=25 1 row(s)
Took 0.0491 seconds
# 通过timestamp来获取指定版本的数据
> get'member','zhangsan',{COLUMN=>'info:age',TIMESTAMP=>1567753903167}
COLUMN CELL info:age timestamp=1567753903167, value=24 1 row(s)
Took 0.0342 seconds
# 全表扫描
> scan 'member'
ROW COLUMN+CELL
lisi column=address:city, timestamp=1567754078391, value=beijing lisi column=info:birthday, timestamp=1567754038812, value=1998-09-09 lisi column=info:favotite, timestamp=1567754057750, value=movie zhangsan column=address:city, timestamp=1567754003312, value=beijing zhangsan column=info:age, timestamp=1567754315161, value=25 zhangsan column=info:birthday, timestamp=1567753950339, value=1993-11-20 zhangsan column=info:country, timestamp=1567753964169, value=china 2 row(s)
Took 0.1000 seconds
# 删除指定字段
> delete'member','zhangsan','info:age'
# 这个很有意思，如果有两个版本的数据，那么只会删除最新的一个版本，当再次查询的时候结果就是上一个版本的
> get'member','zhangsan','info:age'
COLUMN CELL info:age timestamp=1567753903167, value=24 1 row(s)
Took 0.0454 seconds
# 再次执行delete就能把当前版本删除
> delete'member','zhangsan','info:age'
> get'member','zhangsan','info:age'
COLUMN CELL 0 row(s)
Took 0.0166 seconds
# 删除整行
> deleteall'member','lisi'
Took 0.0235 seconds
# 查询表中有多少行
> count'member'
1 row(s)
Took 0.3753 seconds => 1
# 给"zhangsan"这个id增加'info:age'字段，并使用counter实现递增
> incr 'member','zhangsan','info:age'
COUNTER VALUE = 1
Took 0.0948 seconds
> get 'member','zhangsan','info:age'
COLUMN CELL info:age timestamp=1567755056584, value=\x00\x00\x00\x00\x00\x00\x00\x01 1 row(s)
Took 0.0504 seconds
> incr 'member','zhangsan','info:age'
COUNTER VALUE = 2
Took 0.0211 seconds
> get 'member','zhangsan','info:age'
COLUMN CELL info:age timestamp=1567755133527, value=\x00\x00\x00\x00\x00\x00\x00\x02 1 row(s)
Took 0.0479 seconds
# 获取当前count的值
> get_counter'member','zhangsan','info:age'
COUNTER VALUE = 2
Took 0.0145 seconds
# 清空整张表
> truncate 'member'
Truncating 'member' table (it may take a while):
Disabling table...
Truncating table...
Took 2.1687 seconds
# 如何查看多个版本的数据，首先需要更新表结构，因为默认只保存一个版本数据，我们将保存的版本数设置为3
> alter'member',{NAME=>'info',VERSIONS=>3}
> put'member','zhangsan','info:age','26'
> scan 'member',{COLUMN=>'info:age',VERSIONS=>3}
ROW COLUMN+CELL zhangsan column=info:age, timestamp=1567756662127, value=26 zhangsan column=info:age, timestamp=1567756297089, value=25 1 row(s)
Took 0.0361 seconds
> get 'member','zhangsan',{COLUMN=>'info',VERSIONS=>3}
COLUMN CELL info: timestamp=1567755827530, value=info1 info:age timestamp=1567756662127, value=26 info:age timestamp=1567756297089, value=25 info:birthday timestamp=1567755398376, value=1993-11-20 info:country timestamp=1567755402535, value=china 1 row(s)
Took 0.0622 seconds问题1：
运行hbase shell时报错：
./bin/hbase shell
2019-09-06 11:03:21,079 WARN [main] util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
HBase Shell
Use "help" to get list of supported commands.
Use "exit" to quit this interactive shell.
For Reference, please visit: http://hbase.apache.org/2.0/book.html#shell
Version 2.2.0, rUnknown, Tue Jun 11 04:30:30 UTC 2019
Took 0.0080 seconds
NotImplementedError: fstat unimplemented unsupported or native support failed to load; see http://wiki.jruby.org/Native-Libraries
initialize at org/jruby/RubyIO.java:1013
open at org/jruby/RubyIO.java:1154
initialize at uri:classloader:/META-INF/jruby.home/lib/ruby/stdlib/irb/input-method.rb:141
initialize at uri:classloader:/META-INF/jruby.home/lib/ruby/stdlib/irb/context.rb:70
initialize at uri:classloader:/META-INF/jruby.home/lib/ruby/stdlib/irb.rb:426
initialize at /home/wangjun/software/hbase-2.2.0/lib/ruby/irb/hirb.rb:47
start at /home/wangjun/software/hbase-2.2.0/bin/../bin/hirb.rb:207
<main> at /home/wangjun/software/hbase-2.2.0/bin/../bin/hirb.rb:219解决方案：
Unable to load native-hadoop library for your platform... using builtin-java classes where applicable这个问题只需要修改conf/hbase-env.sh，加入：
export LD_LIBRARY_PATH=${hadoop_home}/lib/native:$LD_LIBRARY_PATH${hadoop_home}为你的hadoop的安装路径。
NotImplementedError: fstat unimplemented unsupported or native support failed to load这个问题的解决方案：
sudo apt-get install jruby -y
sudo apt-get install asciidoctor -y参考：
