Hbase的安装和基本使用

发布时间：2020-07-10 00:21:18 来源：网络阅读：202 作者：KeepInUp 栏目：大数据

Hbase介绍

HBase是一个开源的非关系型分布式数据库（NoSQL），它参考了谷歌的BigTable建模，实现的编程语言为 Java。它是Apache软件基金会的Hadoop项目的一部分，运行于HDFS文件系统之上，为 Hadoop 提供类似于BigTable 规模的服务。因此，它可以容错地存储海量稀疏的数据。

Hbase安装

安装环境
三台虚拟机：master、slave1、slave2，
已经安装好Hadoop环境和zookeeper

下载Hbase安装包，根据你自己的需求下载对应的安装包

wget http://archive.apache.org/dist/hbase/0.98.24/hbase-0.98.24-hadoop2-bin.tar.gz

也可以直接去镜像网站下载，地址：http://archive.apache.org/dist/
下载好后，解压安装包

tar -zxvf hbase-0.98.24-hadoop2-bin.tar.gz

添加Hbase的环境变量

//打开~/.bashrc文件
vim ~/.bashrc
//然后在里边追加两行
export HBASE_HOME=/usr/local/src/hbase-0.98.24-hadoop2
export PATH=$PATH:$HBASE_HOME/bin
//然后保存退出，source一下
source ~/.bashrc

配置Hbase
打开Hbase目录下conf/hbase-env.sh（如果没有新建一个）

vim conf/hbase-env.sh
//添加下边两个配置
export JAVA_HOME=/usr/local/src/jdk1.8.0_171  //java home
export HBASE_MANAGES_ZK=false  //是否使用自带的zookeeper，自己有安装的话就用自己的，没有就用自带的

配置hbase-site.xml文件

vim conf/hbase-site.xml
//添加如下配置
<configuration>
        <property>
                <name>hbase.rootdir</name>
                <value>hdfs://master:9000/hbase</value>
        </property>
        <property>
                <name>hbase.cluster.distributed</name>
                <value>true</value>
        </property>
        <property>
                <name>hbase.zookeeper.quorum</name>
                <value>master,slave1,slave2</value>
        </property>
        <property>
                <name>dfs.replication</name>
                <value>2</value>
        </property>
</configuration>

修改regionservers文件

vim conf/regionservers
//添加需要安装regionserver的机器节点
slave1
slave2

到这里Hbase简单的环境就搭建好了

Hbase的启动

启动Hbase需要首先启动Hadoop和zookeeper

启动Hadoop

master机器节点

//进入到Hadoop目录的sbin下
./start-all.sh

查看Hadoop是不是启动成功
master机器节点，jps查看进程看到图中进程说明成功启动
Hbase的安装和基本使用
slave机器节点，jps查看

Zookeeper启动

master和slave节点都执行，进入zookeeper安装目录bin目录下

zkServer.sh start

然后jps查看进程，能看到QuorumPeerMain说明Zookeeper启动成功
Hbase的安装和基本使用

####启动Hbase
在Hadoop和Zookeeper都启动之后就可以启动Hbase了，进入Hbase的安装目录的bin目录下

./start-hbase.sh

jps查看进程，在master能看到Hmaster进程，在slave节点能看到HRegionServer进程，说明Hbase启动成功
Hbase的安装和基本使用

也可以通过网址来检查，http://master:60010/master-status

Hbase简单的shell命令操作

进入shell命令模式，在bin目录下执行

./hbase shell
hbase(main):001:0>

查看当前所有表

hbase(main):003:0> list
TABLE                                                                                                                       
0 row(s) in 0.1510 seconds

=> []

创建表

hbase(main):006:0> create 'test_table' , 'mate_data', 'action'
0 row(s) in 2.4390 seconds

=> Hbase::Table - test_table

查看表详情

hbase(main):009:0> desc 'test_table'
Table test_table is ENABLED                                                                                                 
test_table                                                                                                                  
COLUMN FAMILIES DESCRIPTION                                                                                                 
{NAME => 'action', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_EN
CODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VERSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', 
REPLICATION_SCOPE => '0'}                                                                                                   
{NAME => 'mate_data', 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'}                                                                                                
2 row(s) in 0.0520 seconds

增加列簇

hbase(main):010:0> alter 'test_table', {NAME => 'new', VERSIONS => '2', IN_MEMORY => 'true'}
Updating all regions with the new schema...
0/1 regions updated.
1/1 regions updated.
Done.
0 row(s) in 2.2790 seconds

hbase(main):011:0> desc 'test_table'
Table test_table is ENABLED                                                                                                 
test_table                                                                                                                  
COLUMN FAMILIES DESCRIPTION                                                                                                 
{NAME => 'action', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_EN
CODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VERSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', 
REPLICATION_SCOPE => '0'}                                                                                                   
{NAME => 'mate_data', 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 => 'new', BLOOMFILTER => 'ROW', VERSIONS => '2', IN_MEMORY => 'true', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_ENCODI
NG => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VERSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPL
ICATION_SCOPE => '0'}                                                                                                       
3 row(s) in 0.0570 seconds

删除列簇

hbase(main):013:0> alter 'test_table', {NAME => 'new', METHOD => 'delete'}
Updating all regions with the new schema...
0/1 regions updated.
1/1 regions updated.
Done.
0 row(s) in 2.2390 seconds

hbase(main):014:0> desc 'test_table'
Table test_table is ENABLED                                                                                                 
test_table                                                                                                                  
COLUMN FAMILIES DESCRIPTION                                                                                                 
{NAME => 'action', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELLS => 'FALSE', DATA_BLOCK_EN
CODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VERSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', 
REPLICATION_SCOPE => '0'}                                                                                                   
{NAME => 'mate_data', 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'}                                                                                                
2 row(s) in 0.0430 seconds

删除表

//首先disable
hbase(main):016:0> disable 'test_table'
0 row(s) in 1.2980 seconds
//然后再删除
hbase(main):017:0> drop 'test_table'
0 row(s) in 0.2020 seconds
//查看是否删除
hbase(main):018:0> list
TABLE                                                                                                                       
0 row(s) in 0.0070 seconds

=> []

往表里写数据并查看

hbase(main):021:0> put 'test_table', '1001', 'mate_data:name', 'zhangsan'
0 row(s) in 0.1400 seconds

hbase(main):022:0> put 'test_table', '1002', 'mate_data:name', 'lisi'
0 row(s) in 0.0110 seconds

hbase(main):023:0> put 'test_table', '1001', 'mate_data:gender', 'woman'
0 row(s) in 0.0170 seconds

hbase(main):024:0> put 'test_table', '1002', 'mate_data:age', '25'
0 row(s) in 0.0140 seconds

hbase(main):025:0> scan 'test_table'
ROW                              COLUMN+CELL                                                                                
 1001                            column=mate_data:gender, timestamp=1540034584363, value=woman                              
 1001                            column=mate_data:name, timestamp=1540034497293, value=zhangsan                             
 1002                            column=mate_data:age, timestamp=1540034603800, value=25                                    
 1002                            column=mate_data:name, timestamp=1540034519659, value=lisi                                 
2 row(s) in 0.0410 seconds

读取数据

hbase(main):026:0> get 'test_table', '1001'
COLUMN                           CELL                                                                                       
 mate_data:gender                timestamp=1540034584363, value=woman                                                       
 mate_data:name                  timestamp=1540034497293, value=zhangsan                                                    
2 row(s) in 0.0340 seconds

hbase(main):027:0> get 'test_table', '1001', 'mate_data:name'
COLUMN                           CELL                                                                                       
 mate_data:name                  timestamp=1540034497293, value=zhangsan                                                    
1 row(s) in 0.0320 seconds

查看行数

hbase(main):028:0> count 'test_table'
2 row(s) in 0.0390 seconds

=> 2

清空表数据

hbase(main):029:0> truncate 'test_table'
Truncating 'test_table' table (it may take a while):
 - Disabling table...
 - Truncating table...
0 row(s) in 1.5220 seconds

通过Python脚本来操作Hbase

不能通过Python脚本来直接操作Hbase，必须要借助thrift服务作为中间层，所以需要两个Python模块：hbase模块和thrift模块，和安装thrift来实现Python对Hbase的操作
####安装thrift并获得thrift模块

下载安装thrift

wget http://archive.apache.org/dist/thrift/0.11.0/thrift-0.11.0.tar.gz
tar -zxvf thrift-0.11.0.tar.gz
cd thrift-0.11.0/
./configure
make
make install
cd lib/py/build/lib.linux-x86_64-2.7

然后就能看到thrift模块

获得hbase模块

下载Hbase源码包

wget http://archive.apache.org/dist/hbase/0.98.24/hbase-0.98.24-src.tar.gz
tar -zxvf hbase-0.98.24-src.tar.gz

产生hbase模块

//进入该目录
cd /usr/local/src/hbase-0.98.24/hbase-thrift/src/main/resources/org/apache/hadoop/hbase/thrift
//执行如下命令，产生gen-py目录
thrift --gen py Hbase.thrift
//进入该目录就能得到生成的hbase模块
cd gen-py

使用Python写数据

创建表

from thrift.transport import TSocket
from thrift.protocol import TBinaryProtocol

from hbase import Hbase
from hbase.ttypes import *

transport = TSocket.TSocket('master', 9090)
transport = TTransport.TBufferedTransport(transport)

protocol = TBinaryProtocol.TBinaryProtocol(transport)

client = Hbase.Client(protocol)

transport.open()

base_info_contents = ColumnDescriptor(name='columnName1', maxVersions=1)
other_info_contents = ColumnDescriptor(name='columnName2', maxVersions=1)

client.createTable('tableName', [base_info_contents,other_info_contents])

插入数据

from thrift.transport import TSocket
from thrift.protocol import TBinaryProtocol

from hbase import Hbase
from hbase.ttypes import *

transport = TSocket.TSocket('master', 9090)
transport = TTransport.TBufferedTransport(transport)

protocol = TBinaryProtocol.TBinaryProtocol(transport)

client = Hbase.Client(protocol)

transport.open()

table_name = 'tableName'
rowKey = 'rowKeyName'
mutations = [Mutation(column="columnName:columnPro", value="valueName")]
client.mutateRow(table_name,rowKey,mutations,None)

查看数据

from thrift.transport import TSocket
from thrift.protocol import TBinaryProtocol

from hbase import Hbase
from hbase.ttypes import *

transport = TSocket.TSocket('master', 9090)
transport = TTransport.TBufferedTransport(transport)

protocol = TBinaryProtocol.TBinaryProtocol(transport)

client = Hbase.Client(protocol)

transport.open()

table_name = 'tableName'
rowKey = 'rowKeyName'

result = client.getRow(table_name,rowKey,None)

for l in result:
    print "the row is "+ l.row
    for k,v in l.columns.items():
        print '\t'.join([k,v.value])

from thrift.transport import TSocket
from thrift.protocol import TBinaryProtocol

from hbase import Hbase
from hbase.ttypes import *

transport = TSocket.TSocket('master', 9090)
transport = TTransport.TBufferedTransport(transport)

protocol = TBinaryProtocol.TBinaryProtocol(transport)

client = Hbase.Client(protocol)

transport.open()

table_name = 'tableName'

scan = TScan()

id = client.scannerOpenWithScan(table_name,scan,None)
result = client.scannerGetList(id,10)

for l in result:
    print "========="
    print "the row is "+ l.row
    for k,v in l.columns.items():
        print '\t'.join([k,v.value])

向AI问一下细节

Hbase的安装和基本使用

Hbase介绍

Hbase安装

Hbase的启动

启动Hadoop

Zookeeper启动

Hbase简单的shell命令操作

通过Python脚本来操作Hbase

获得hbase模块

使用Python写数据

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