Hive命令详解：创建、修改与数据操作

创建表 hive> CREATE TABLE pokes (foo INT, bar STRING); 
创建表并创建索引字段ds hive> CREATE TABLE invites (foo INT, bar STRING) PARTITIONED BY (ds STRING); 
显示所有表 hive> SHOW TABLES; 
按正条件（正则表达式）显示表， hive> SHOW TABLES '.*s'; 
表添加一列 hive> ALTER TABLE pokes ADD COLUMNS (new_col INT); 
添加一列并增加列字段注释 hive> ALTER TABLE invites ADD COLUMNS (new_col2 INT COMMENT 'a comment'); 
更改表名 hive> ALTER TABLE events RENAME TO 3koobecaf; 
删除列 hive> DROP TABLE pokes; alter table t_user_bill_03 replace columns(i_145 string);
元数据存储 将文件中的数据加载到表中 hive> LOAD DATA LOCAL INPATH './examples/files/kv1.txt' OVERWRITE INTO TABLE pokes; 
加载本地数据，同时给定分区信息 hive> LOAD DATA LOCAL INPATH './examples/files/kv2.txt' OVERWRITE INTO TABLE invites PARTITION (ds='2008-08-15'); 
加载DFS数据 ，同时给定分区信息 hive> LOAD DATA INPATH '/user/myname/kv2.txt' OVERWRITE INTO TABLE invites PARTITION (ds='2008-08-15'); 
The above command will load data from an HDFS file/directory to the table. 
Note that loading data from HDFS will result in moving the file/directory. 
As a result, the operation is almost instantaneous. 
SQL 操作 按先件查询 hive> SELECT a.foo FROM invites a WHERE a.ds='<DATE>'; 
将查询数据输出至目录 hive> INSERT OVERWRITE DIRECTORY '/tmp/hdfs_out' SELECT a.* FROM invites a WHERE a.ds='<DATE>'; 
将查询结果输出至本地目录 hive> INSERT OVERWRITE LOCAL DIRECTORY '/tmp/local_out' SELECT a.* FROM pokes a; 
选择所有列到本地目录 hive> INSERT OVERWRITE TABLE events SELECT a.* FROM profiles a; 
                     hive> INSERT OVERWRITE TABLE events SELECT a.* FROM profiles a WHERE a.key < 100; hive> INSERT OVERWRITE LOCAL DIRECTORY '/tmp/reg_3' SELECT a.* FROM events a; hive> INSERT OVERWRITE DIRECTORY '/tmp/reg_4' select a.invites, a.pokes FROM profiles a; hive> INSERT OVERWRITE DIRECTORY '/tmp/reg_5' SELECT COUNT(1) FROM invites a WHERE a.ds='<DATE>'; hive> INSERT OVERWRITE DIRECTORY '/tmp/reg_5' SELECT a.foo, a.bar FROM invites a; hive> INSERT OVERWRITE LOCAL DIRECTORY '/tmp/sum' SELECT SUM(a.pc) FROM pc1 a; 
将一个表的统计结果插入另一个表中 hive> FROM invites a INSERT OVERWRITE TABLE events SELECT a.bar, count(1) WHERE a.foo > 0 GROUP BY a.bar; 
                                hive> INSERT OVERWRITE TABLE events SELECT a.bar, count(1) FROM invites a WHERE a.foo > 0 GROUP BY a.bar; JOIN hive> FROM pokes t1 JOIN invites t2 ON (t1.bar = t2.bar) INSERT OVERWRITE TABLE events SELECT t1.bar, t1.foo, t2.foo; 
将多表数据插入到同一表中 FROM src INSERT OVERWRITE TABLE dest1 SELECT src.* WHERE src.key < 100 INSERT OVERWRITE TABLE dest2 SELECT src.key, src.value WHERE src.key >= 100 and src.key < 200 INSERT OVERWRITE TABLE dest3 PARTITION(ds='2008-04-08', hr='12') SELECT src.key WHERE src.key >= 200 and src.key < 300 INSERT OVERWRITE LOCAL DIRECTORY '/tmp/dest4.out' SELECT src.value WHERE src.key >= 300; 
将文件流直接插入文件 hive> FROM invites a INSERT OVERWRITE TABLE events SELECT TRANSFORM(a.foo, a.bar) AS (oof, rab) USING '/bin/cat' WHERE a.ds > '2008-08-09'; This streams the data in the map phase through the script /bin/cat (like hadoop streaming). Similarly - streaming can be used on the reduce side (please see the Hive Tutorial or examples) 

----建表----
---t_user_bill_03-----
create table t_user_bill_03(org_id int,user string,IMSI string,IMEI string,apn int,url_id int,top_id int,cnt_code string, 
bill_cycle string, access_counts double,access_duration double, uplink_bytes double,downlink_bytes double,total_bytes double ) 
partitioned by (class string)  ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' ;