Hive面試題（3）：如何用sqoop將hive中分區表的分區字段導入到MySQL中

問題分析：

1. hive中分區表其底層就是HDFS中的多個目錄下的單個文件，hive導出數據本質是將HDFS中的文件導出
2. hive中的分區表，因為分區字段（靜態分區）不在文件中，所以在sqoop導出的時候，無法將分區字段進行直接導出

思路：在hive中創建一個臨時表，將分區表復制過去后分區字段轉換為普通字段，然后再用sqoop將tmp表導出即實現需求
步湊如下：

1.創建目標表（分區表）

hive> CREATE TABLE `dept_partition`(                     
`deptno` int,                                    
`dname` string,                                  
`loc` string)                                    
PARTITIONED BY (`month` string) row format delimited fields terminated by '\t';

1.1查看表結構

hive> show create table dept_partition;

+----------------------------------------------------+--+
|                   createtab_stmt                   |
+----------------------------------------------------+--+
| CREATE TABLE `dept_partition`(                     |
|   `deptno` int,                                    |
|   `dname` string,                                  |
|   `loc` string)                                    |
| PARTITIONED BY (                                   |
|   `month` string)

2.導入數據

hive> load data inpath '/user/hive/hive_db/data/dept.txt' into table dept_partition;

10    ACCOUNTING    1700
20    RESEARCH    1800
30    SALES    1900
40    OPERATIONS    1700

3.查詢表dept_partition

hive> select * from dept_partition;

+------------------------+-----------------------+---------------------+-----------------------+--+
| dept_partition.deptno  | dept_partition.dname  | dept_partition.loc  | dept_partition.month  |
+------------------------+-----------------------+---------------------+-----------------------+--+
| 10                     | ACCOUNTING            | 1700                | 2019-10-19            |
| 20                     | RESEARCH              | 1800                | 2019-10-19            |
| 30                     | SALES                 | 1900                | 2019-10-19            |
| 40                     | OPERATIONS            | 1700                | 2019-10-19            |
| 10                     | ACCOUNTING            | 1700                | 2019-10-20            |
| 20                     | RESEARCH              | 1800                | 2019-10-20            |
| 30                     | SALES                 | 1900                | 2019-10-20            |
| 40                     | OPERATIONS            | 1700                | 2019-10-20            |
+------------------------+-----------------------+---------------------+-----------------------+--+

4.創建臨時表 tmp_dept_partition

hive> create table tmp_dept_partition as select * from dept_partition;

5.查詢臨時表

hive> select * from tmp_dept_partition;

+----------------------------+---------------------------+-------------------------+---------------------------+--+
| tmp_dept_partition.deptno  | tmp_dept_partition.dname  | tmp_dept_partition.loc  | tmp_dept_partition.month  |
+----------------------------+---------------------------+-------------------------+---------------------------+--+
| 10                         | ACCOUNTING                | 1700                    | 2019-10-19                |
| 20                         | RESEARCH                  | 1800                    | 2019-10-19                |
| 30                         | SALES                     | 1900                    | 2019-10-19                |
| 40                         | OPERATIONS                | 1700                    | 2019-10-19                |
| 10                         | ACCOUNTING                | 1700                    | 2019-10-20                |
| 20                         | RESEARCH                  | 1800                    | 2019-10-20                |
| 30                         | SALES                     | 1900                    | 2019-10-20                |
| 40                         | OPERATIONS                | 1700                    | 2019-10-20                |
+----------------------------+---------------------------+-------------------------+---------------------------+--+

6.查看表結構(這個時候分區表已經轉換為非分區表了)

hive> show create table tmp_dept_partition;

+----------------------------------------------------+--+
|                   createtab_stmt                   |
+----------------------------------------------------+--+
| CREATE TABLE `tmp_dept_partition`(                 |
|   `deptno` int,                                    |
|   `dname` string,                                  |
|   `loc` string,                                    |
|   `month` string)

7.MySQL中建表 dept_partition

mysql> drop table if exists dept_partition;
create table dept_partition(
`deptno` int,        
`dname` varchar(20),      
`loc` varchar(20),               
`month` varchar(50))

8.使用sqoop導入到MySQL

bin/sqoop export \
--connect jdbc:mysql://hadoop01:3306/partitionTb \
--username root \
--password 123456 \
--table dept_partition \
--num-mappers 1 \
--export-dir /user/hive/warehouse/hive_db.db/tmp_dept_partition \
--input-fields-terminated-by "\001"

9.Mysql查詢驗證是否成功導出

mysql> select * from dept_partition;

+--------+------------+------+------------+
| deptno | dname      | loc  | month      |
+--------+------------+------+------------+
|     10 | ACCOUNTING | 1700 | 2019-10-19 |
|     20 | RESEARCH   | 1800 | 2019-10-19 |
|     30 | SALES      | 1900 | 2019-10-19 |
|     40 | OPERATIONS | 1700 | 2019-10-19 |
|     10 | ACCOUNTING | 1700 | 2019-10-20 |
|     20 | RESEARCH   | 1800 | 2019-10-20 |
|     30 | SALES      | 1900 | 2019-10-20 |
|     40 | OPERATIONS | 1700 | 2019-10-20 |
+--------+------------+------+------------+