本文共 5357 字，大约阅读时间需要 17 分钟。
2. 改动hive/conf下hive-site.xml文件。在底部加入例如以下内容：
[html] view plaincopy
<!-- <property> <name>hive.exec.scratchdir</name> <value>/usr/local/hive/tmp</value> </property> --> <property> <name>hive.querylog.location</name> <value>/usr/local/hive/logs</value> </property> <property> <name>hive.aux.jars.path</name> <value>file:///usr/local/hive/lib/hive-hbase-handler-0.8.0.jar,file:///usr/local/hive/lib/hbase-0.90.5.jar,file:///usr/local/hive/lib/zookeeper-3.3.2.jar</value> </property> 注意：假设hive-site.xml不存在则自行创建，或者把hive-default.xml.template文件改名后使用。 详细请參见：http://blog.csdn.net/kunshan_shenbin/article/details/7210020 3. 拷贝hbase-0.90.5.jar到全部hadoop节点(包含master)的hadoop/lib下。 4. 拷贝hbase/conf下的hbase-site.xml文件到全部hadoop节点(包含master)的hadoop/conf下。 注意。hbase-site.xml文件配置信息參照：http://blog.csdn.net/kunshan_shenbin/article/details/7209990 注意，假设3,4两步跳过的话。执行hive时非常可能出现例如以下错误：[html] view plaincopy
org.apache.hadoop.hbase.ZooKeeperConnectionException: HBase is able to connect to ZooKeeper but the connection closes immediately. This could be a sign that the server has too many connections (30 is the default). Consider inspecting your ZK server logs for that error and then make sure you are reusing HBaseConfiguration as often as you can. See HTable's javadoc for more information. at org.apache.hadoop. hbase.zookeeper.ZooKeeperWatcher. 參考：http://blog.sina.com.cn/s/blog_410d18710100vlbq.html 如今能够尝试启动Hive了。 单节点启动： | > bin/hive -hiveconf hbase.master=master:60000 |
集群启动：
> bin/hive -hiveconf hbase.zookeeper.quorum=slave
怎样hive-site.xml文件里没有配置hive.aux.jars.path，则能够依照例如以下方式启动。
> bin/hive --auxpath /usr/local/hive/lib/hive-hbase-handler-0.8.0.jar, /usr/local/hive/lib/hbase-0.90.5.jar, /usr/local/hive/lib/zookeeper-3.3.2.jar -hiveconf hbase.zookeeper.quorum=slave
接下来能够做一些測试了。
1.创建hbase识别的数据库： [sql] view plaincopy CREATE TABLE hbase_table_1(key int, value string) STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler' WITH SERDEPROPERTIES ("hbase.columns.mapping" = ":key,cf1:val") TBLPROPERTIES ("hbase.table.name" = "xyz"); hbase.table.name 定义在hbase的table名称 hbase.columns.mapping 定义在hbase的列族 2.使用sql导入数据 a) 新建hive的数据表 [sql] view plaincopy <span><span></span></span>hive> CREATE TABLE pokes (foo INT, bar STRING); b) 批量插入数据 [sql] view plaincopyhive> LOAD DATA LOCAL INPATH './examples/files/kv1.txt' OVERWRITE INTO TABLE
pokes;
c) 使用sql导入hbase_table_1 [sql] view plaincopy hive> INSERT OVERWRITE TABLE hbase_table_1 SELECT * FROM pokes WHERE foo=86; 3. 查看数据 [sql] view plaincopy hive> select * from hbase_table_1; 这时能够登录Hbase去查看数据了. > /usr/local/hbase/bin/hbase shell hbase(main):001:0> describe 'xyz' hbase(main):002:0> scan 'xyz' hbase(main):003:0> put 'xyz','100','cf1:val','www.360buy.com' 这时在Hive中能够看到刚才在Hbase中插入的数据了。 hive> select * from hbase_table_1 4. hive訪问已经存在的hbase 使用CREATE EXTERNAL TABLE [sql] view plaincopy CREATE EXTERNAL TABLE hbase_table_2(key int, value string) STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler' WITH SERDEPROPERTIES ("hbase.columns.mapping" = "cf1:val") TBLPROPERTIES("hbase.table.name" = "some_existing_table"); 多列和多列族（Multiple Columns and Families） 1．创建数据库 Java代码 CREATE TABLE hbase_table_2(key int, value1 string, value2 int, value3 int) STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler' WITH SERDEPROPERTIES ( "hbase.columns.mapping" = ":key,a:b,a:c,d:e" ); 2.插入数据 Java代码 INSERT OVERWRITE TABLE hbase_table_2 SELECT foo, bar, foo+1, foo+2 FROM pokes WHERE foo=98 OR foo=100; 这个有3个hive的列（value1和value2，value3），2个hbase的列族（a，d） Hive的2列（value1和value2）相应1个hbase的列族（a。在hbase的列名称b，c）。hive的另外1列（value3）相应列（e）位于列族（d） 3.登录hbase查看结构 Java代码hbase(main):003:0> describe "hbase_table_2"
DESCRIPTION ENABLED {NAME => 'hbase_table_2', FAMILIES => [{NAME => 'a', COMPRESSION => 'N true ONE', VERSIONS => '3', TTL => '2147483647', BLOCKSIZE => '65536', IN_M EMORY => 'false', BLOCKCACHE => 'true'}, {NAME => 'd', COMPRESSION => 'NONE', VERSIONS => '3', TTL => '2147483647', BLOCKSIZE => '65536', IN _MEMORY => 'false', BLOCKCACHE => 'true'}]} 1 row(s) in 1.0630 seconds 4.查看hbase的数据 Java代码hbase(main):004:0> scan 'hbase_table_2'
ROW COLUMN+CELL 100 column=a:b, timestamp=1297695262015, value=val_100 100 column=a:c, timestamp=1297695262015, value=101 100 column=d:e, timestamp=1297695262015, value=102 98 column=a:b, timestamp=1297695242675, value=val_98 98 column=a:c, timestamp=1297695242675, value=99 98 column=d:e, timestamp=1297695242675, value=100 2 row(s) in 0.0380 seconds5.在hive中查看
Java代码hive> select * from hbase_table_2;
OK 100 val_100 101 102 98 val_98 99 100 Time taken: 3.238 seconds 參考资料： http://running.iteye.com/blog/898399 http://heipark.iteye.com/blog/1150648 http://www.javabloger.com/article/apache-hadoop-hive-hbase-integration.html本文转自mfrbuaa博客园博客，原文链接：http://www.cnblogs.com/mfrbuaa/p/5094133.html，如需转载请自行联系原作者