HBase的Shell命令和JavaAPI

HBase的shell操作和JavaAPI的使用：

Shell

表操作

创建表

create 'student','info'           #表名  列族

 插入表

put 'student','1001','info:sex','male'
put 'student','1001','info:age','18'
put 'student','1002','info:name','Janna'
put 'student','1002','info:sex','female'
put 'student','1002','info:age','20'

 查看表数据

scan 'student'
scan 'student',{STARTROW => '1001', STOPROW  => '1002'}   #左闭右开
scan 'student',{STARTROW => '1001'}

 查看表结构

describe 'student'
desc 'student'             #效果相同

 更新指定字段

put 'student','1001','info:name','Nick'
put 'student','1001','info:age','100'  #  表明  rowkey  列族:列 值

 查看指定行数据

get 'student','1001'

 统计表行数

count 'student'

 删除数据

deleteall 'student','1001'

 删除rowkey的某一列

delete 'student','1002','info:sex'

 清空数据

truncate 'student'
#表的操作顺序为先disable，然后再truncate。

 删除表

disable 'student'

 表更表信息

alter 'student',{NAME=>'info',VERSIONS=>3} ##将info列族中的数据存放3个版本：

 Java API

环境准备

<dependency>
    <groupId>org.apache.hbase</groupId>
    <artifactId>hbase-server</artifactId>
    <version>1.3.1</version>
</dependency>

<dependency>
    <groupId>org.apache.hbase</groupId>
    <artifactId>hbase-client</artifactId>
    <version>1.3.1</version>
</dependency>

 HBaseAPI

获取Configuration对象

public static Configuration conf;
static{
	//使用HBaseConfiguration的单例方法实例化
	conf = HBaseConfiguration.create();
conf.set("hbase.zookeeper.quorum", "192.168.1.101"); ## 换成自己的ZK节点IP
conf.set("hbase.zookeeper.property.clientPort", "2181");
}

 判断表是否存在

public static boolean isTableExist(String tableName) throws MasterNotRunningException,
 ZooKeeperConnectionException, IOException{
//在HBase中管理、访问表需要先创建HBaseAdmin对象
	HBaseAdmin admin = new HBaseAdmin(conf);
	return admin.tableExists(tableName);
}

 创建表

public static void createTable(String tableName, String... columnFamily) throws
 MasterNotRunningException, ZooKeeperConnectionException, IOException{
	HBaseAdmin admin = new HBaseAdmin(conf);
	//判断表是否存在
	if(isTableExist(tableName)){
		System.out.println("表" + tableName + "已存在");
		//System.exit(0);
	}else{
		//创建表属性对象,表名需要转字节
		HTableDescriptor descriptor = new HTableDescriptor(TableName.valueOf(tableName));
		//创建多个列族
		for(String cf : columnFamily){
			descriptor.addFamily(new HColumnDescriptor(cf));
		}
		//根据对表的配置，创建表
		admin.createTable(descriptor);
		System.out.println("表" + tableName + "创建成功！");
	}
}

 删除表

public static void dropTable(String tableName) throws MasterNotRunningException,
 ZooKeeperConnectionException, IOException{
	HBaseAdmin admin = new HBaseAdmin(conf);
	if(isTableExist(tableName)){
		admin.disableTable(tableName);
		admin.deleteTable(tableName);
		System.out.println("表" + tableName + "删除成功！");
	}else{
		System.out.println("表" + tableName + "不存在！");
	}
}

 插入数据

public static void addRowData(String tableName, String rowKey, String columnFamily, String
 column, String value) throws IOException{
	//创建HTable对象
	HTable hTable = new HTable(conf, tableName);
	//向表中插入数据
	Put put = new Put(Bytes.toBytes(rowKey));
	//向Put对象中组装数据
	put.add(Bytes.toBytes(columnFamily), Bytes.toBytes(column), Bytes.toBytes(value));
	hTable.put(put);
	hTable.close();
	System.out.println("插入数据成功");
}

 删除多行数据

public static void deleteMultiRow(String tableName, String... rows) throws IOException{
	HTable hTable = new HTable(conf, tableName);
	List<Delete> deleteList = new ArrayList<Delete>();
	for(String row : rows){
		Delete delete = new Delete(Bytes.toBytes(row));
		deleteList.add(delete);
	}
	hTable.delete(deleteList);
	hTable.close();
}

 获取所有数据

public static void getAllRows(String tableName) throws IOException{
	HTable hTable = new HTable(conf, tableName);
	//得到用于扫描region的对象
	Scan scan = new Scan();
	//使用HTable得到resultcanner实现类的对象
	ResultScanner resultScanner = hTable.getScanner(scan);
	for(Result result : resultScanner){
		Cell[] cells = result.rawCells();
		for(Cell cell : cells){
			//得到rowkey
			System.out.println("行键:" + Bytes.toString(CellUtil.cloneRow(cell)));
			//得到列族
			System.out.println("列族" + Bytes.toString(CellUtil.cloneFamily(cell)));
			System.out.println("列:" + Bytes.toString(CellUtil.cloneQualifier(cell)));
			System.out.println("值:" + Bytes.toString(CellUtil.cloneValue(cell)));
		}
	}
}

 获取某一行数据

public static void getRow(String tableName, String rowKey) throws IOException{
	HTable table = new HTable(conf, tableName);
	Get get = new Get(Bytes.toBytes(rowKey));
	//get.setMaxVersions();显示所有版本
    //get.setTimeStamp();显示指定时间戳的版本
	Result result = table.get(get);
	for(Cell cell : result.rawCells()){
		System.out.println("行键:" + Bytes.toString(result.getRow()));
		System.out.println("列族" + Bytes.toString(CellUtil.cloneFamily(cell)));
		System.out.println("列:" + Bytes.toString(CellUtil.cloneQualifier(cell)));
		System.out.println("值:" + Bytes.toString(CellUtil.cloneValue(cell)));
		System.out.println("时间戳:" + cell.getTimestamp());
	}
}

 获取某一行指定“列族:列”的数据

public static void getRowQualifier(String tableName, String rowKey, String family, String
 qualifier) throws IOException{
	HTable table = new HTable(conf, tableName);
	Get get = new Get(Bytes.toBytes(rowKey));
	get.addColumn(Bytes.toBytes(family), Bytes.toBytes(qualifier));
	Result result = table.get(get);
	for(Cell cell : result.rawCells()){
		System.out.println("行键:" + Bytes.toString(result.getRow()));
		System.out.println("列族" + Bytes.toString(CellUtil.cloneFamily(cell)));
		System.out.println("列:" + Bytes.toString(CellUtil.cloneQualifier(cell)));
		System.out.println("值:" + Bytes.toString(CellUtil.cloneValue(cell)));
	}
}

 MapReduce

HBase的相关JavaAPI，可以实现伴随HBase操作的MapReduce过程，使用MapReduce将数据从本地文件系统导入到HBase的表中或者从HBase中读取一些原始数据后使用MapReduce做数据分析。

Hive集成Hbase

编译:hive-hbase-handler-1.2.2.jar

ln -s $HBASE_HOME/lib/hbase-common-1.3.1.jar  $HIVE_HOME/lib/hbase-common-1.3.1.jar
ln -s $HBASE_HOME/lib/hbase-server-1.3.1.jar $HIVE_HOME/lib/hbase-server-1.3.1.jar
ln -s $HBASE_HOME/lib/hbase-client-1.3.1.jar $HIVE_HOME/lib/hbase-client-1.3.1.jar
ln -s $HBASE_HOME/lib/hbase-protocol-1.3.1.jar $HIVE_HOME/lib/hbase-protocol-1.3.1.jar
ln -s $HBASE_HOME/lib/hbase-it-1.3.1.jar $HIVE_HOME/lib/hbase-it-1.3.1.jar
ln -s $HBASE_HOME/lib/htrace-core-3.1.0-incubating.jar $HIVE_HOME/lib/htrace-core-3.1.0-incubating.jar
ln -s $HBASE_HOME/lib/hbase-hadoop2-compat-1.3.1.jar $HIVE_HOME/lib/hbase-hadoop2-compat-1.3.1.jar
ln -s $HBASE_HOME/lib/hbase-hadoop-compat-1.3.1.jar $HIVE_HOME/lib/hbase-hadoop-compat-1.3.1.jar

 hive-site.xml中修改zookeeper的属性，如下：

<property>
	  <name>hive.zookeeper.quorum</name>
 	 <value>datanode1,datanode2,datanode3</value>
 	 <description>The list of ZooKeeper servers to talk to. This is only needed for read/write locks.</description>
</property>
<property>
 	 <name>hive.zookeeper.client.port</name>
 	 <value>2181</value>
  	<description>The port of ZooKeeper servers to talk to. This is only needed for read/write locks.</description>
</property>

 案例

创建hive关联表

CREATE TABLE hive_hbase_emp_table(
empno int,
ename string,
job string,
mgr int,
hiredate string,
sal double,
comm double,
deptno int)
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES ("hbase.columns.mapping" = ":key,info:ename,info:job,info:mgr,info:hiredate,info:sal,info:comm,info:deptno")
TBLPROPERTIES ("hbase.table.name" = "hbase_hive_emp_table_");

 在Hive中创建临时中间表，用于load文件中的数据

CREATE TABLE emp(
empno int,
ename string,
job string,
mgr int,
hiredate string,
sal double,
comm double,
deptno int)
row format delimited fields terminated by ',';

 向Hive中间表中load数据

load data local inpath '/home/hadoop/emp.csv' into table emp;

 通过insert命令将中间表中的数据导入到Hive关联HBase的那张表中

insert into table hive_hbase_emp_table select * from emp;

 查看HIVE表

select * from hive_hbase_emp_table;

 查看HBase表

scan ‘hbase_emp_table’

在HBase中已经存储了某一张表hbase_emp_table，然后在Hive中创建一个外部表来关联HBase中的hbase_emp_table这张表，使之可以借助Hive来分析HBase这张表中的数据。

Hive创建表

CREATE EXTERNAL TABLE relevance_hbase_emp(
empno int,
ename string,
job string,
mgr int,
hiredate string,
sal double,
comm double,
deptno int)
STORED BY 
'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES ("hbase.columns.mapping" = 
":key,info:ename,info:job,info:mgr,info:hiredate,info:sal,info:comm,info:deptno") 
TBLPROPERTIES ("hbase.table.name" = "hbase_emp_table");

 关联后就可以使用Hive函数进行一些分析操作了

select * from relevance_hbase_emp;