Hive(三)--基本操作

待我称王封你为后i 2022-09-29 05:18 260阅读 0赞

阅读本文章可以带着下面问题：  
1.与传统数据库对比，找出他们的区别  
2.熟练写出增删改查（面试必备）  
  
创建表：  
hive> CREATE TABLE pokes (foo INT, bar STRING);   
 Creates a table called pokes with two columns, the first being an integer and the other a string  
  
创建一个新表，结构与其他一样  
hive> create table new\_table like records;  
  
创建分区表：  
hive> create table logs(ts bigint,line string) partitioned by (dt String,country String);  
  
加载分区表数据：  
hive> load data local inpath '/home/hadoop/input/hive/partitions/file1' into table logs partition (dt='2001-01-01',country='GB');  
  
展示表中有多少分区：  
hive> show partitions logs;  
  
展示所有表：  
hive> SHOW TABLES;  
 lists all the tables  
hive> SHOW TABLES '.\*s';  
  
lists all the table that end with 's'. The pattern matching follows Java regular  
expressions. Check out this link for documentation   
  
显示表的结构信息  
hive> DESCRIBE invites;  
 shows the list of columns  
  
更新表的名称：  
hive> ALTER TABLE source RENAME TO target;  
  
添加新一列  
hive> ALTER TABLE invites ADD COLUMNS (new\_col2 INT COMMENT 'a comment');  
  
删除表：  
hive> DROP TABLE records;  
删除表中数据，但要保持表的结构定义  
hive> dfs -rmr /user/hive/warehouse/records;  
  
从本地文件加载数据：  
hive> LOAD DATA LOCAL INPATH '/home/hadoop/input/ncdc/micro-tab/sample.txt' OVERWRITE INTO TABLE records;  
  
显示所有函数：  
hive> show functions;  
  
查看函数用法：  
hive> describe function substr;  
  
查看数组、map、结构  
hive> select col1\[0\],col2\['b'\],col3.c from complex;  
  
  
内连接：  
hive> SELECT sales.\*, things.\* FROM sales JOIN things ON (sales.id = things.id);  
  
查看hive为某个查询使用多少个MapReduce作业  
hive> Explain SELECT sales.\*, things.\* FROM sales JOIN things ON (sales.id = things.id);  
  
外连接：  
hive> SELECT sales.\*, things.\* FROM sales LEFT OUTER JOIN things ON (sales.id = things.id);  
hive> SELECT sales.\*, things.\* FROM sales RIGHT OUTER JOIN things ON (sales.id = things.id);  
hive> SELECT sales.\*, things.\* FROM sales FULL OUTER JOIN things ON (sales.id = things.id);  
  
in查询：Hive不支持，但可以使用LEFT SEMI JOIN  
hive> SELECT \* FROM things LEFT SEMI JOIN sales ON (sales.id = things.id);  
  
  
Map连接：Hive可以把较小的表放入每个Mapper的内存来执行连接操作  
hive> SELECT /\*+ MAPJOIN(things) \*/ sales.\*, things.\* FROM sales JOIN things ON (sales.id = things.id);  
  
INSERT OVERWRITE TABLE ..SELECT：新表预先存在  
hive> FROM records2  
 > INSERT OVERWRITE TABLE stations\_by\_year SELECT year, COUNT(DISTINCT station) GROUP BY year   
 > INSERT OVERWRITE TABLE records\_by\_year SELECT year, COUNT(1) GROUP BY year  
 > INSERT OVERWRITE TABLE good\_records\_by\_year SELECT year, COUNT(1) WHERE temperature != 9999 AND (quality = 0 OR quality = 1 OR quality = 4 OR quality = 5 OR quality = 9) GROUP BY year;   
  
CREATE TABLE ... AS SELECT：新表表预先不存在  
hive>CREATE TABLE target AS SELECT col1,col2 FROM source;  
  
创建视图：  
hive> CREATE VIEW valid\_records AS SELECT \* FROM records2 WHERE temperature !=9999;  
  
查看视图详细信息：

[Hive][]> DESCRIBE EXTENDED valid\_records;

[Hive]: http://lib.csdn.net/base/hive