使用Hive读取Hbase中的数据

第一步,启动hadoop,命令:./start-all.sh

第二步,启动hive,命令:

./hive --auxpath /home/dream-victor/hive-0.6.0/lib/hive_hbase-handler.jar,/home/dream-victor/hive-0.6.0/lib/hbase-0.20.3.jar,/home/dream-victor/hive-0.6.0/lib/zookeeper-3.2.2.jar -hiveconf hbase.master=127.0.0.1:60000

这里,-hiveconf hbase.master=指向自己在hbase-site.xml中hbase.master的值

第三步,启动hbase,命令:./start-hbase.sh

第四步,建立关联表,这里我们要查询的表在hbase中已经存在所以,使用CREATE EXTERNAL TABLE来建立,如下:

CREATE EXTERNAL TABLE hbase_table_2(key string, value string) 
STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler' 
WITH SERDEPROPERTIES ("hbase.columns.mapping" = "data:1") 
TBLPROPERTIES("hbase.table.name" = "test");  

 hbase.columns.mapping指向对应的列族;多列时,data:1,data:2;多列族时,data1:1,data2:1;

 hbase.table.name指向对应的表;

 hbase_table_2(key string, value string),这个是关联表

我们看一下HBase中要查询的表的结构,

hbase(main):001:0> describe 'test'
DESCRIPTION                                                             ENABLED                               
 {NAME => 'test', FAMILIES => [{NAME => 'data', COMPRESSION => 'NONE',  true                                  
 VERSIONS => '3', TTL => '2147483647', BLOCKSIZE => '65536', IN_MEMORY                                        
 => 'false', BLOCKCACHE => 'true'}]}                                                                          
1 row(s) in 0.0810 seconds
hbase(main):002:0>

 在看一下表中的数据,

hbase(main):002:0> scan 'test'
ROW                          COLUMN+CELL                                                                      
 row1                        column=data:1, timestamp=1300847098583, value=value1                             
 row12                       column=data:1, timestamp=1300849056637, value=value3                             
 row2                        column=data:2, timestamp=1300847106880, value=value2                             
3 row(s) in 0.0160 seconds
hbase(main):003:0> 

 列族:data:1、data:2两个

 Key:row1、row12、row2

 value:value1、value3、value2

 hbase_table_2(key string, value string)中对应的test表中的row,value字段对应的是test表中的value

OK,现在可以来看看查询结果了,

我们在hive命令行中先查看一下hbase_table_2,

hive> select * from hbase_table_2;
OK
row1	value1
row12	value3
Time taken: 0.197 seconds
hive>

 对比一下test表中的列族为data:1的数据,

 row1                        column=data:1, timestamp=1300847098583, value=value1                             
 row12                       column=data:1, timestamp=1300849056637, value=value3  

和查询结果相符,没问题,然后我们在hbase中在给列族data:1新增一条数据,

hbase(main):003:0> put 'test','row13','data:1','value4'
0 row(s) in 0.0050 seconds
hbase(main):004:0>

 再查看hbase_table_2表,

hive> select * from hbase_table_2;
OK
row1	value1
row12	value3
row13	value4
Time taken: 0.165 seconds
hive> 

 新增数据value4出现了,说明可以通过hbase_table_2查询hbase的test表

下面我们来查询一下test表中value值为value3的数据,

hive> select * From hbase_table_2 where value='value3';
Total MapReduce jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_201103231022_0001, Tracking URL = http://localhost:50030/jobdetails.jsp?jobid=job_201103231022_0001
Kill Command = /home/dream-victor/hadoop-0.20.2/bin/hadoop job  -Dmapred.job.tracker=localhost:9001 -kill job_201103231022_0001
2011-03-23 11:23:27,807 Stage-1 map = 0%,  reduce = 0%
2011-03-23 11:23:30,824 Stage-1 map = 100%,  reduce = 0%
2011-03-23 11:23:33,854 Stage-1 map = 100%,  reduce = 100%
Ended Job = job_201103231022_0001
OK
row12	value3
Time taken: 11.929 seconds
hive>

 和hbase的test表对比一下,

row12                       column=data:1, timestamp=1300849056637, value=value3

 OK,这样我们就可以使用SQL来对hbase进行查询了。

 

以上只是在命令行里左对应的查询,我们的目的是使用JAVA代码来查询出有用的数据,其实这个也很简单,

首先,启动Hive的命令有点变化,使用如下命令:

./hive --service hiveserver

 这里我们默认使用嵌入的Derby数据库,这里可以在hive-site.xml文件中查看到:


  javax.jdo.option.ConnectionURL
  jdbc:derby:;databaseName=metastore_db;create=true//指定了数据库默认的名字和地址



  javax.jdo.option.ConnectionDriverName
  org.apache.derby.jdbc.EmbeddedDriver

 在此,数据库链接的URL可以使用默认的:jdbc:hive://localhost:10000/default

 有了上面的准备,下面我们就可以使用JAVA代码来读取数据了,如下:

public class HiveTest extends TestCase {

	private static String driverName = "org.apache.hadoop.hive.jdbc.HiveDriver";
	private Connection con;
	private boolean standAloneServer = true;

	public void testSelect() throws SQLException {
		Statement stmt = con.createStatement();
		ResultSet res = stmt.executeQuery("select * from hbase_table_2");
		boolean moreRow = res.next();
		while (moreRow) {
			System.out.println(res.getString(1)+","+res.getString(2));
			moreRow = res.next();
		}
	}

	@Override
	protected void setUp() throws Exception {
		super.setUp();
		Class.forName(driverName);
		con = DriverManager.getConnection(
				"jdbc:hive://localhost:10000/default", "", "");
	}
}

 结果,

row1,value1
row12,value3
row13,value4
row14,test

 查看一下hbase中的结果,

ROW                          COLUMN+CELL                                                                      
 row1                        column=data:1, timestamp=1300847098583, value=value1                             
 row12                       column=data:1, timestamp=1300849056637, value=value3                             
 row13                       column=data:1, timestamp=1300850443699, value=value4                             
 row14                       column=data:1, timestamp=1300867550502, value=test

 OK,完美了,不过还是希望这样的需求少一点,毕竟Hbase产生的初衷不是为了支持结构化查询。

你可能感兴趣的:(hadoop系列)