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mysql高級查詢表,如何用sqoop將hive分區表信息導入到mysql命令

錢多多2年前30瀏覽0評論
mysql高級查詢表,如何用sqoop將hive分區表信息導入到mysql命令?

問題分析:

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

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:

文章目錄

1.創建目標表(分區表)

1.1查看表結構

2.導入數據

3.查詢表dept_partition

4.創建臨時表 tmp_dept_partition

5.查詢臨時表

6.查看表結構(這個時候分區表已經轉換為非分區表了)

7.mysql中建表 dept_partition

8.使用sqoop導入到MySQL

8.Mysql查詢驗證是否成功導出

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';

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1.1查看表結構

hive> show create table dept_partition;

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+----------------------------------------------------+--+

createtab_stmt

+----------------------------------------------------+--+

CREATE TABLE `dept_partition`(

`deptno` int,

`dname` string,

`loc` string)

PARTITIONED BY (

`month` string)

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2.導入數據

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

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10 ACCOUNTING 1700

20 RESEARCH 1800

30 SALES 1900

40 OPERATIONS 1700

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3.查詢表dept_partition

hive> select * from dept_partition;

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+------------------------+-----------------------+---------------------+-----------------------+--+

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

+------------------------+-----------------------+---------------------+-----------------------+--+

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4.創建臨時表 tmp_dept_partition

hive> create table tmp_dept_partition as select * from dept_partition;

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5.查詢臨時表

hive> select * from tmp_dept_partition;

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+----------------------------+---------------------------+-------------------------+---------------------------+--+

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

+----------------------------+---------------------------+-------------------------+---------------------------+--+

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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;

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+----------------------------------------------------+--+

createtab_stmt

+----------------------------------------------------+--+

CREATE TABLE `tmp_dept_partition`(

`deptno` int,

`dname` string,

`loc` string,

`month` string)

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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))

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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"

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8.Mysql查詢驗證是否成功導出

mysql> select * from dept_partition;

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+--------+------------+------+------------+

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

+---