Hive Hsql 常用命令

简介

Hive是基于Hadoop的一个数据仓库工具，可以将结构化的数据文件映射为一张数据库表，并提供简单的sql查询功能，可以将sql语句转换为MapReduce任务进行运行。 其优点是学习成本低，可以通过类SQL语句快速实现简单的MapReduce统计。以下介绍常用的Hive的类SQL语句。

创建表：

hive>create table tablename(id int,name string,password string);

创建表时指定分隔符

hive> create table tablename(name string,password string)row format delimited fields terminated by ‘,’;
(指定源数据的分隔符为"逗号")

加载表

hive> load data inpath ‘/user/hadoop/output7/part-r-00000’ into table tablename;

创建一个新表，结构与某表一样

hive> create table table02 like table01;

创建分区表

hive> create table tablename(id int,line string) partitioned by (dt string,country string);

显示表里有多少条记录(count 数大于50的有多少条记录)

hive>select count(*) from tablename where count>50;

排序用法order by (查询count 数大于50并排序)

select * from tablename where count > 50 order by count;

显示表中有多少分区

hive> show partitions tablename;

显示所有表

hive> show tables;

显示所有与t开头的表

hive> show tables ‘t*’;

显示表的结构信息

hive> describe tablename;

修改表名字

hive> alter table table01 rename to table02;

在原表上新添加一列

hive> alter table tablename add columns(new_col2 int comment ‘a commment’);

hive> alter table tablename add columns(new_col3 int);

删除表

hive> drop table tablename;

从本地文件加载数据：

hive> LOAD DATA LOCAL INPATH ‘/home/hadoop/input/sample.txt’ OVERWRITE INTO TABLE records;

加载分区表

hive> load data inpath ‘/user/hive/warehouse/part-r-00000’ overwrite into table clickstream_log PARTITION(dt = ‘2018-11-30’);

显示所有函数

hive> show functions;

查看函数的用法

hive> describe function substr;

查看数组、map、结构

hive> select col1[0],col2[‘b’],col3.c from complex;

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;