Hive基础sql语法(DDL)
前言：
为企业提供做网站、网站建设、网站优化、网络营销推广、竞价托管、品牌运营等营销获客服务。创新互联拥有网络营销运营团队，以丰富的互联网营销经验助力企业精准获客，真正落地解决中小企业营销获客难题，做到“让获客更简单”。自创立至今，成功用技术实力解决了企业“网站建设、网络品牌塑造、网络营销”三大难题，同时降低了营销成本，提高了有效客户转化率，获得了众多企业客户的高度认可！
- 经过前面的学习 我们了解到Hive可以使用关系型数据库来存储元数据，而且Hive提供了比较完整的SQL功能 ，这篇文章主要介绍Hive基本的sql语法。
首先了解下Hive的数据存储结构，抽象图如下：
- 1.Database:Hive中包含了多个数据库，默认的数据库为default，对应于HDFS目录是/user/hadoop/hive/warehouse，可以通过hive.metastore.warehouse.dir参数进行配置（hive-site.xml中配置）
- 2.Table: Hive 中的表又分为内部表和外部表 ,Hive 中的每张表对应于HDFS上的一个目录，HDFS目录为：/user/hadoop/hive/warehouse/[databasename.db]/table
- 3.Partition:分区，每张表中可以加入一个分区或者多个，方便查询，提高效率；并且HDFS上会有对应的分区目录：
/user/hadoop/hive/warehouse/[databasename.db]/table - 4.Bucket(桶)：暂且不讲
DDL操作(Data Definition Language)
参考官方文档： DDL文档
HiveQL DDL statements are documented here, including:
- CREATE DATABASE/SCHEMA, TABLE, VIEW, FUNCTION, INDEX
- DROP DATABASE/SCHEMA, TABLE, VIEW, INDEX
- TRUNCATE TABLE
- ALTER DATABASE/SCHEMA, TABLE, VIEW
- MSCK REPAIR TABLE (or ALTER TABLE RECOVER PARTITIONS)
- SHOW DATABASES/SCHEMAS, TABLES, TBLPROPERTIES, VIEWS, PARTITIONS, FUNCTIONS, INDEX[ES], COLUMNS, CREATE TABLE
- DESCRIBE DATABASE/SCHEMA, table_name, view_name
一.基于数据库的DDL操作
1.创建数据库（Create Database）
- 下面是官网上为我们列出的语法：
Create Database CREATE (DATABASE|SCHEMA) [IF NOT EXISTS] database_name [COMMENT database_comment] [LOCATION hdfs_path] [WITH DBPROPERTIES (property_name=property_value, ...)];IF NOT EXISTS：加上这句话代表判断数据库是否存在，不存在就会创建，存在就不会创建（生产环境建议使用）。
COMMENT：数据库的描述
LOCATION：创建数据库的地址，不加默认在/user/hive/warehouse/路径下
WITH DBPROPERTIES：数据库的属性
hive> CREATE DATABASE hive1;
OK
hive> CREATE DATABASE IF NOT EXISTS hive2
> COMMENT "this is ruoze database"
> WITH DBPROPERTIES ("creator"="ruoze", "date"="2018-08-08");
OK
hive> CREATE DATABASE hive3 LOCATION '/db_hive3';
OK
hive> show databases;
OK
default
hive1
hive2
hive3
# 在HDFS中查看数据库文件夹
[hadoop@hadoop000 ~]$ hadoop fs -ls /user/hive/warehouse
Found 2 items
drwxr-xr-x - hadoop supergroup 0 2018-06-16 15:26 /user/hive/warehouse/hive1.db
drwxr-xr-x - hadoop supergroup 0 2018-06-16 15:28 /user/hive/warehouse/hive2.db
[hadoop@hadoop000 ~]$ hadoop fs -ls /
Found 3 items
drwxr-xr-x - hadoop supergroup 0 2018-06-16 15:29 /db_hive3
drwx-wx-wx - hadoop supergroup 0 2018-06-03 15:57 /tmp
drwxr-xr-x - hadoop supergroup 0 2018-06-03 16:43 /user
# 在RDBMS中查看数据库相关信息
MySQL> select * from hive_meta.dbs\G;
*************************** 1. row ***************************
DB_ID: 1
DESC: Default Hive database
DB_LOCATION_URI: hdfs://hadoop000:9000/user/hive/warehouse
NAME: default
OWNER_NAME: public
OWNER_TYPE: ROLE
*************************** 2. row ***************************
DB_ID: 6
DESC: NULL
DB_LOCATION_URI: hdfs://hadoop000:9000/user/hive/warehouse/hive1.db
NAME: hive1
OWNER_NAME: hadoop
OWNER_TYPE: USER
*************************** 3. row ***************************
DB_ID: 7
DESC: this is ruoze database
DB_LOCATION_URI: hdfs://hadoop000:9000/user/hive/warehouse/hive2.db
NAME: hive2
OWNER_NAME: hadoop
OWNER_TYPE: USER
*************************** 4. row ***************************
DB_ID: 8
DESC: NULL
DB_LOCATION_URI: hdfs://hadoop000:9000/db_hive3
NAME: hive3
OWNER_NAME: hadoop
OWNER_TYPE: USER
4 rows in set (0.00 sec)2.查询数据库（Show Databases）
- 下面是官网上为我们列出的语法：
SHOW (DATABASES|SCHEMAS) [LIKE 'identifier_with_wildcards'];hive> show databases;
OK
default
hive1
hive2
hive3
Time taken: 0.047 seconds, Fetched: 4 row(s)
hive> show databases like 'hive1';
OK
hive1
Time taken: 0.035 seconds, Fetched: 1 row(s)
hive> show databases like 'hive*';
OK
hive1
hive2
hive3
Time taken: 0.037 seconds, Fetched: 3 row(s)3.查询数据库信息（Describe Database）
- 下面是官网上为我们列出的语法：
DESCRIBE DATABASE [EXTENDED] db_name;
--describe 可简写为descDESCRIBE DATABASE db_name：查看数据库的描述信息和文件目录位置路径信息；
EXTENDED：加上数据库键值对的属性信息。
hive> desc database hive1;
OK
hive1 hdfs://192.168.6.217:9000/user/hive/warehouse/hive1.db hadoop USER
Time taken: 0.039 seconds, Fetched: 1 row(s)
hive> desc database hive2;
OK
hive2 this is ruoze database hdfs://192.168.6.217:9000/user/hive/warehouse/hive2.db hadoop USER
Time taken: 0.041 seconds, Fetched: 1 row(s)
hive> desc database hive3;
OK
hive3 hdfs://192.168.6.217:9000/db_hive3 hadoop USER
Time taken: 0.046 seconds, Fetched: 1 row(s)
hive> desc database extended hive2;
OK
hive2 this is ruoze database hdfs://192.168.6.217:9000/user/hive/warehouse/hive2.db hadoop USER {date=2018-08-08, creator=ruoze}
Time taken: 0.031 seconds, Fetched: 1 row(s)4.删除数据库（Drop Database）
- 下面是官网上为我们列出的语法：
DROP (DATABASE|SCHEMA) [IF EXISTS] database_name [RESTRICT|CASCADE];RESTRICT：默认是restrict，如果该数据库还有表存在则报错；
CASCADE：级联删除数据库(当数据库还有表时，级联删除表后再删除数据库) --生产尽量不用。
hive> drop database test;
OK
Time taken: 0.094 seconds5.修改数据库信息（Alter Database）
- 下面是官网上为我们列出的语法：
ALTER (DATABASE|SCHEMA) database_name SET DBPROPERTIES (property_name=property_value, ...); -- (Note: SCHEMA added in Hive 0.14.0)
ALTER (DATABASE|SCHEMA) database_name SET OWNER [USER|ROLE] user_or_role;
-- (Note: Hive 0.13.0 and later; SCHEMA added in Hive 0.14.0)
ALTER (DATABASE|SCHEMA) database_name SET LOCATION hdfs_path;
-- (Note: Hive 2.2.1, 2.4.0 and later)（Note：表示对于版本进行的修改）
hive> alter database hive2 set dbproperties ("update"="jepson");
OK
Time taken: 0.094 seconds
hive> alter database hive2 set owner user hive;
OK
Time taken: 0.072 seconds
# 修改前
hive> desc database extended hive2;
OK
hive2 this is ruoze database hdfs://192.168.6.217:9000/user/hive/warehouse/hive2.db hadoop USER {date=2018-08-08, creator=ruoze}
Time taken: 0.031 seconds, Fetched: 1 row(s)
# 修改后
hive> desc database extended hive2;
OK
hive2 this is ruoze database hdfs://192.168.6.217:9000/user/hive/warehouse/hive2.db hive USER {update=jepson, date=2018-08-08, creator=ruoze}
Time taken: 0.034 seconds, Fetched: 1 row(s)6.切换数据库（Use Database）
- 下面是官网上为我们列出的语法：
USE database_name;hive> use hive1;
OK
Time taken: 0.044 seconds
hive> use default;
OK
Time taken: 0.047 seconds二.基于表的DDL操作
1.创建表（Create Table）
- 下面是官网上为我们列出的语法：
CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name -- (Note: TEMPORARY available in Hive 0.14.0 and later)
[(col_name data_type [COMMENT col_comment], ... [constraint_specification])]
[COMMENT table_comment]
[PARTITIONED BY (col_name data_type [COMMENT col_comment], ...)]
[CLUSTERED BY (col_name, col_name, ...) [SORTED BY (col_name [ASC|DESC], ...)] INTO num_buckets BUCKETS]
[SKEWED BY (col_name, col_name, ...) -- (Note: Available in Hive 0.10.0 and later)]
ON ((col_value, col_value, ...), (col_value, col_value, ...), ...)
[STORED AS DIRECTORIES]
[
[ROW FORMAT row_format]
[STORED AS file_format]
| STORED BY 'storage.handler.class.name' [WITH SERDEPROPERTIES (...)] -- (Note: Available in Hive 0.6.0 and later)
]
[LOCATION hdfs_path]
[TBLPROPERTIES (property_name=property_value, ...)] -- (Note: Available in Hive 0.6.0 and later)
[AS select_statement]; -- (Note: Available in Hive 0.5.0 and later; not supported for external tables)- Hive从0.14.0开始提供创建临时表的功能，表只对当前session有效，session退出后，表自动删除。
语法：
CREATE TEMPORARY TABLE ...注意点：
- 如果创建的临时表表名已存在，那么当前session引用到该表名时实际用的是临时表，只有drop或rename临时表名才能使用原始表；
- 临时表限制：不支持分区字段和创建索引。
hive> use default;
OK
Time taken: 0.047 seconds
hive> CREATE TEMPORARY TABLE temporary_table (
> id int,
> name string);
OK
Time taken: 0.242 seconds
hive> show tables;
OK
temporary_table
Time taken: 0.044 seconds, Fetched: 1 row(s)
# 退出重新进
hive> use default;
OK
Time taken: 1.054 seconds
hive> show tables;
OK
Time taken: 0.559 seconds- Hive上有两种类型的表，一种是Managed Table(默认的)，另一种是External Table（加上EXTERNAL关键字）。它俩的主要区别在于：当我们drop表时，Managed Table会同时删去data（存储在HDFS上）和meta data（存储在MySQL），而External Table只会删meta data。
hive> use default;
OK
Time taken: 1.054 seconds
hive> show tables;
OK
Time taken: 0.559 seconds
# 创建内部表和外部表
hive> create table managed_table(
> id int,
> name string
> );
OK
Time taken: 0.677 seconds
hive> create external table external_table(
> id int,
> name string
> );
OK
Time taken: 0.146 seconds
hive> show tables;
OK
external_table
managed_table
Time taken: 0.05 seconds, Fetched: 2 row(s)
# HDFS中查看
[hadoop@hadoop000 ~]$ hadoop fs -ls /user/hive/warehouse
Found 4 items
drwxr-xr-x - hadoop supergroup 0 2018-06-16 16:40 /user/hive/warehouse/external_table
drwxr-xr-x - hadoop supergroup 0 2018-06-16 15:26 /user/hive/warehouse/hive1.db
drwxr-xr-x - hadoop supergroup 0 2018-06-16 15:28 /user/hive/warehouse/hive2.db
drwxr-xr-x - hadoop supergroup 0 2018-06-16 16:39 /user/hive/warehouse/managed_table
# MySQL中查看
mysql> select * from hive_meta.tbls\G;
*************************** 1. row ***************************
TBL_ID: 11
CREATE_TIME: 1529138399
DB_ID: 1
LAST_ACCESS_TIME: 0
OWNER: hadoop
RETENTION: 0
SD_ID: 11
TBL_NAME: managed_table
TBL_TYPE: MANAGED_TABLE
VIEW_EXPANDED_TEXT: NULL
VIEW_ORIGINAL_TEXT: NULL
*************************** 2. row ***************************
TBL_ID: 12
CREATE_TIME: 1529138409
DB_ID: 1
LAST_ACCESS_TIME: 0
OWNER: hadoop
RETENTION: 0
SD_ID: 12
TBL_NAME: external_table
TBL_TYPE: EXTERNAL_TABLE
VIEW_EXPANDED_TEXT: NULL
VIEW_ORIGINAL_TEXT: NULL
2 rows in set (0.00 sec)
# 删除内部表和外部表
hive> drop table managed_table;
OK
Time taken: 1.143 seconds
hive> drop table external_table;
OK
Time taken: 0.265 seconds
# 再次查看
[hadoop@hadoop000 ~]$ hadoop fs -ls /user/hive/warehouse
Found 3 items
drwxr-xr-x - hadoop supergroup 0 2018-06-16 16:40 /user/hive/warehouse/external_table
drwxr-xr-x - hadoop supergroup 0 2018-06-16 15:26 /user/hive/warehouse/hive1.db
drwxr-xr-x - hadoop supergroup 0 2018-06-16 15:28 /user/hive/warehouse/hive2.db
mysql> select * from hive_meta.tbls\G;
Empty set (0.00 sec)
ERROR:
No query specifiedCOMMENT：注释 可以给字段和表加注释
先看看官网对于ROW FORMAT的描述
: DELIMITED
[FIELDS TERMINATED BY char [ESCAPED BY char]] [COLLECTION ITEMS TERMINATED BY char]
[MAP KEYS TERMINATED BY char]
[LINES TERMINATED BY char]
[NULL DEFINED AS char]
-- (Note: Available in Hive 0.13 and later)
| SERDE serde_name [WITH SERDEPROPERTIES (property_name=property_value, property_name=property_value, ...)]先看看官网给我们的解释：用户在建表的时候可以自定义 SerDe 或者使用自带的 SerDe。如果没有指定 ROW FORMAT 或者 ROW FORMAT DELIMITED，将会使用自带的 SerDe。在建表的时候，用户还需要为表指定列，用户在指定表的列的同时也会指定自定义的 SerDe，Hive 通过 SerDe 确定表的具体的列的数据。
那么问题又来了上面这句话又是什么意思呢？
让我们来一起看看到底是神马东东：
DELIMITED：分隔符（可以自定义分隔符）；
FIELDS TERMINATED BY char:每个字段之间使用的分割；
例：-FIELDS TERMINATED BY '\n' 字段之间的分隔符为\n;
COLLECTION ITEMS TERMINATED BY char:集合中元素与元素（array）之间使用的分隔符（collection单例集合的跟接口）；
MAP KEYS TERMINATED BY char：字段是K-V形式指定的分隔符；
LINES TERMINATED BY char：每条数据之间由换行符分割（默认[ \n ]）。- 一般情况下LINES TERMINATED BY char我们就使用默认的换行符\n，只需要指定FIELDS TERMINATED BY char。
hive> CREATE TABLE hive_test
> (id int comment 'this is id', name string comment 'this is name' )
> comment 'this is hive_test'
> ROW FORMAT DELIMITED
> FIELDS TERMINATED BY '\t' ;
OK
Time taken: 0.174 seconds
#为了后面的测试我们创建一张emp表 并导入一些数据
hive> create table emp
> (empno int, ename string, job string, mgr int, hiredate string, salary double, comm double, deptno int)
> ROW FORMAT DELIMITED
> FIELDS TERMINATED BY '\t' ;
OK
Time taken: 0.651 seconds
hive> LOAD DATA LOCAL INPATH '/home/hadoop/emp.txt' OVERWRITE INTO TABLE emp;
Loading data to table default.emp
Table default.emp stats: [numFiles=1, numRows=0, totalSize=886, rawDataSize=0]
OK
Time taken: 1.848 seconds- 创建表（拷贝表结构及数据，并且会运行MapReduce作业）
# 复制整张表
hive> create table emp2 as select * from emp;
Query ID = hadoop_20180616171313_fbc318e8-bc70-4b63-84fa-3acd94e4ec3e
Total jobs = 3
...
OK
Time taken: 23.279 seconds
hive> select * from emp2;
OK
7369 SMITH CLERK 7902 1980-12-17 800.0 NULL 20
7499 ALLEN SALESMAN 7698 1981-2-20 1600.0 300.0 30
7521 WARD SALESMAN 7698 1981-2-22 1250.0 500.0 30
7566 JONES MANAGER 7839 1981-4-2 2975.0 NULL 20
7654 MARTIN SALESMAN 7698 1981-9-28 1250.0 1400.0 30
7698 BLAKE MANAGER 7839 1981-5-1 2850.0 NULL 30
7782 CLARK MANAGER 7839 1981-6-9 2450.0 NULL 10
7788 SCOTT ANALYST 7566 1987-4-19 3000.0 NULL 20
7839 KING PRESIDENT NULL 1981-11-17 5000.0 NULL 10
7844 TURNER SALESMAN 7698 1981-9-8 1500.0 0.0 30
7876 ADAMS CLERK 7788 1987-5-23 1100.0 NULL 20
7900 JAMES CLERK 7698 1981-12-3 950.0 NULL 30
7902 FORD ANALYST 7566 1981-12-3 3000.0 NULL 20
7934 MILLER CLERK 7782 1982-1-23 1300.0 NULL 10
Time taken: 0.138 seconds, Fetched: 14 row(s)
#复制表中的一些字段
hive> create table emp3 as select empno,ename from emp;
Query ID = hadoop_20180616171313_fbc318e8-bc70-4b63-84fa-3acd94e4ec3e
Total jobs = 3
...
OK
Time taken: 16.143 seconds
hive> select * from emp3;
OK
7369 SMITH
7499 ALLEN
7521 WARD
7566 JONES
7654 MARTIN
7698 BLAKE
7782 CLARK
7788 SCOTT
7839 KING
7844 TURNER
7876 ADAMS
7900 JAMES
7902 FORD
7934 MILLER
Time taken: 0.159 seconds, Fetched: 14 row(s)# Create Table Like 只拷贝表结构
hive> create table emp_like like emp;
OK
Time taken: 0.195 seconds
hive> select * from emp_like;
OK
Time taken: 0.131 seconds2.展示表 （Show Table与Show Create Table）
- 下面是官网上为我们列出的语法：
SHOW TABLES [IN database_name] ['identifier_with_wildcards'];
SHOW CREATE TABLE ([db_name.]table_name|view_name);hive> show tables;
OK
emp
emp2
emp3
emp_like
hive_test
Time taken: 0.042 seconds, Fetched: 5 row(s)
hive> show tables 'emp*';
OK
emp
emp2
emp3
emp_like
Time taken: 0.053 seconds, Fetched: 4 row(s)
hive> show create table emp;
OK
CREATE TABLE `emp`(
`empno` int,
`ename` string,
`job` string,
`mgr` int,
`hiredate` string,
`salary` double,
`comm` double,
`deptno` int)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
STORED AS INPUTFORMAT
'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION
'hdfs://192.168.6.217:9000/user/hive/warehouse/emp'
TBLPROPERTIES (
'COLUMN_STATS_ACCURATE'='true',
'numFiles'='1',
'numRows'='0',
'rawDataSize'='0',
'totalSize'='657',
'transient_lastDdlTime'='1529140756')
Time taken: 0.245 seconds, Fetched: 24 row(s)3.查询表信息（Describe Table）
- 下面是官网上为我们列出的语法：
DESCRIBE [EXTENDED|FORMATTED]
table_name[.col_name ( [.field_name] | [.'$elem$'] | [.'$key$'] | [.'$value$'] )* ];
-- (Note: Hive 1.x.x and 0.x.x only. See "Hive 2.0+: New Syntax" below)desc formatted table_name; 比较常用
hive> desc emp;
OK
empno int
ename string
job string
mgr int
hiredate string
salary double
comm double
deptno int
Time taken: 0.213 seconds, Fetched: 8 row(s)
hive> desc formatted emp;
OK
# col_name data_type comment
empno int
ename string
job string
mgr int
hiredate string
salary double
comm double
deptno int
# Detailed Table Information
Database: default
Owner: hadoop
CreateTime: Sat Jun 16 17:13:05 CST 2018
LastAccessTime: UNKNOWN
Protect Mode: None
Retention: 0
Location: hdfs://192.168.6.217:9000/user/hive/warehouse/emp
Table Type: MANAGED_TABLE
Table Parameters:
COLUMN_STATS_ACCURATE true
numFiles 1
numRows 0
rawDataSize 0
totalSize 657
transient_lastDdlTime 1529140756
# Storage Information
SerDe Library: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
InputFormat: org.apache.hadoop.mapred.TextInputFormat
OutputFormat: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
Compressed: No
Num Buckets: -1
Bucket Columns: []
Sort Columns: []
Storage Desc Params:
field.delim \t
serialization.format \t
Time taken: 0.214 seconds, Fetched: 39 row(s)
hive> desc EXTENDED emp;
OK
empno int
ename string
job string
mgr int
hiredate string
salary double
comm double
deptno int
Detailed Table Information Table(tableName:emp, dbName:default, owner:hadoop, createTime:1529140385, lastAccessTime:0, retention:0, sd:StorageDescriptor(cols:[FieldSchema(name:empno, type:int, comment:null), FieldSchema(name:ename, type:string, comment:null), FieldSchema(name:job, type:string, comment:null), FieldSchema(name:mgr, type:int, comment:null), FieldSchema(name:hiredate, type:string, comment:null), FieldSchema(name:salary, type:double, comment:null), FieldSchema(name:comm, type:double, comment:null), FieldSchema(name:deptno, type:int, comment:null)], location:hdfs://192.168.6.217:9000/user/hive/warehouse/emp, inputFormat:org.apache.hadoop.mapred.TextInputFormat, outputFormat:org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat, compressed:false, numBuckets:-1, serdeInfo:SerDeInfo(name:null, serializationLib:org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe, parameters:{serialization.format= , field.delim=
Time taken: 0.21 seconds, Fetched: 10 row(s)4.修改表（Alter Table）
- 下面是官网上为我们列出的语法：
ALTER TABLE table_name RENAME TO new_table_name;
ALTER TABLE table_name SET TBLPROPERTIES table_properties;
table_properties:
: (property_name = property_value, property_name = property_value, ... )
ALTER TABLE table_name SET TBLPROPERTIES ('comment' = new_comment);
...hive> alter table hive_test rename to new_hive_test;
OK
Time taken: 0.262 seconds
hive> ALTER TABLE table_name SET TBLPROPERTIES ("creator"="ruoze", "date"="2018-06-16");
FAILED: SemanticException [Error 10001]: Table not found default.table_name
hive> ALTER TABLE new_hive_test SET TBLPROPERTIES ("creator"="ruoze", "date"="2018-06-16");
OK
Time taken: 0.246 seconds
hive> ALTER TABLE new_hive_test SET TBLPROPERTIES ('comment' = 'This is new_hive_test Table');
# 再次查看表
hive> desc formatted new_hive_test;
OK
# col_name data_type comment
id int this is id
name string this is name
# Detailed Table Information
Database: default
Owner: hadoop
CreateTime: Sat Jun 16 17:09:19 CST 2018
LastAccessTime: UNKNOWN
Protect Mode: None
Retention: 0
Location: hdfs://192.168.6.217:9000/user/hive/warehouse/new_hive_test
Table Type: MANAGED_TABLE
Table Parameters:
COLUMN_STATS_ACCURATE false
comment This is new_hive_test Table
creator ruoze
date 2018-06-16
last_modified_by hadoop
last_modified_time 1529143021
numFiles 0
numRows -1
rawDataSize -1
totalSize 0
transient_lastDdlTime 1529143021
# Storage Information
SerDe Library: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
InputFormat: org.apache.hadoop.mapred.TextInputFormat
OutputFormat: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
Compressed: No
Num Buckets: -1
Bucket Columns: []
Sort Columns: []
Storage Desc Params:
field.delim \t
serialization.format \t
Time taken: 0.188 seconds, Fetched: 38 row(s)5.截断表（Truncate Table）
- 下面是官网上为我们列出的语法：
TRUNCATE TABLE table_name [PARTITION partition_spec]; partition_spec: : (partition_column = partition_col_value, partition_column = partition_col_value, ...)Truncate Table用处不多
hive> select * from emp3; OK 7369 SMITH 7499 ALLEN 7521 WARD 7566 JONES 7654 MARTIN 7698 BLAKE 7782 CLARK 7788 SCOTT 7839 KING 7844 TURNER 7876 ADAMS 7900 JAMES 7902 FORD 7934 MILLER Time taken: 0.148 seconds, Fetched: 14 row(s) hive> truncate table emp3; OK Time taken: 0.241 seconds hive> select * from emp3; OK Time taken: 0.12 seconds6.删除表（Drop Table）
- 下面是官网上为我们列出的语法：
DROP TABLE [IF EXISTS] table_name [PURGE]; -- (Note: PURGE available in Hive 0.14.0 and later)1.指定PURGE后，数据不会放到回收箱，会直接删除。
2.DROP TABLE删除此表的元数据和数据。如果配置了垃圾箱（并且未指定PURGE），则实际将数据移至.Trash / Current目录。元数据完全丢失。
3.删除EXTERNAL表时，表中的数据不会从文件系统中删除。hive> drop table emp3; OK Time taken: 0.866 seconds hive> show tables; OK emp emp2 emp_like new_hive_test Time taken: 0.036 seconds, Fetched: 4 row(s)参考：https://blog.csdn.net/yu0_zhang0/article/details/78976021
关于表的DDL操作还有很多，有关分区表的操作还没详解 后面会单独写一篇分区表
名称栏目：Hive基础sql语法(DDL)
浏览地址：http://myzitong.com/article/giidgp.html