MySQL建表转化为Hive建表

建一张维表

CREATE TABLE dim_ddl_convert (
 source VARCHAR (100) NOT NULL,
 data_type1 VARCHAR (100) NOT NULL,
 target VARCHAR (100) NOT NULL,
 data_type2 VARCHAR (100),
 update_time VARCHAR (26),
 PRIMARY KEY (source, data_type1, target)
) ENGINE = INNODB DEFAULT CHARSET = utf8 COMMENT = '数据库表结构转换';

插入MySQL数据类型与Hive数据类型的映射关系（Hive 0.11.0）

INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'tinyint', 'hive', 'tinyint', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'smallint', 'hive', 'smallint', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'mediumint', 'hive', 'int', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'int', 'hive', 'int', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'bigint', 'hive', 'bigint', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'float', 'hive', 'float', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'double', 'hive', 'double', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'numeric', 'hive', 'decimal', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'decimal', 'hive', 'decimal', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'char', 'hive', 'string', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'varchar', 'hive', 'string', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'text', 'hive', 'string', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'binary', 'hive', 'binary', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'varbinary', 'hive', 'varbinary', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'time', 'hive', 'string', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'date', 'hive', 'string', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'datetime', 'hive', 'string', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'timestamp', 'hive', 'string', '2020-03-14 00:00:00');
INSERT INTO dim_ddl_convert (source, data_type1, target, data_type2, update_time) VALUES ('mysql', 'json', 'hive', 'map<string,string>', '2020-03-14 00:00:00');

打开SQL查询工具，执行以下查询

set session group_concat_max_len = 102400;
select
 a.table_name,
 b.table_comment,
 concat(
     'drop table if exists ',a.table_name,';'
     'create table if not exists ',a.table_name,' (',
     group_concat(
         concat(
             a.column_name,' ',c.data_type2," comment '",column_comment,"'"
         )
         order by
             a.table_name,
             a.ordinal_position
     ),
     ") comment '",b.table_comment,"'",
     "row format delimited fields terminated by '\\t' stored as textfile;"
 ) as col_name
from
 (
     select
         table_schema,
         table_name,
         column_name,
         ordinal_position,
         data_type,
         column_comment
     from
         information_schema.columns
     where
         table_schema = 'test_dp'
     and table_name = 'ods_cdn_url_akamai_bk'
 ) as a
left join information_schema.tables as b 
on a.table_name = b.table_name and a.table_schema = b.table_schema
left join (
 select
     *
 from
     dim_ddl_convert
 where
     source = 'mysql'
 and target = 'hive'
) as c on a.data_type = c.data_type1
group by
 a.table_name,
 b.table_comment;