MySQL数据库 Load Data 多种用法
目录
MySQL Load Data 的多种用法
一、LOAD 基本背景
二、LOAD 基础参数
三、LOAD 示例数据及示例表结构
四、LOAD 场景示例
五、LOAD 总结
MySQL Load Data 的多种用法 一、LOAD 基本背景二、LOAD 基础参数我们在数据库运维过程中难免会涉及到需要对文本数据进行处理，并导入到数据库中，本文整理了一些导入导出时常见的场景进行示例演示。
文章后续示例均使用以下命令导出的 csv 格式样例数据(以 , 逗号做分隔符，以 " 双引号作为界定符)
-- 导出基础参数
select * into outfile '/data/mysql/3306/tmp/employees.txt'
character set utf8mb4
fields terminated by ','
enclosed by '"'
lines terminated by '\n'
from employees.employees limit 10;
-- 导入基础参数
load data infile '/data/mysql/3306/tmp/employees.txt'
replace into table demo.emp
character set utf8mb4
fields terminated by ','
enclosed by '"'
lines terminated by '\n'
...
三、LOAD 示例数据及示例表结构
以下为示例数据，表结构及对应关系信息
-- 导出的文件数据内容
[root@10-186-61-162 tmp]# cat employees.txt
"10001","1953-09-02","Georgi","Facello","M","1986-06-26"
"10002","1964-06-02","Bezalel","Simmel","F","1985-11-21"
"10003","1959-12-03","Parto","Bamford","M","1986-08-28"
"10004","1954-05-01","Chirstian","Koblick","M","1986-12-01"
"10005","1955-01-21","Kyoichi","Maliniak","M","1989-09-12"
"10006","1953-04-20","Anneke","Preusig","F","1989-06-02"
"10007","1957-05-23","Tzvetan","Zielinski","F","1989-02-10"
"10008","1958-02-19","Saniya","Kalloufi","M","1994-09-15"
"10009","1952-04-19","Sumant","Peac","F","1985-02-18"
"10010","1963-06-01","Duangkaew","Piveteau","F","1989-08-24"
-- 示例表结构
SQL > desc demo.emp;
+-------------+---------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------------+---------------+------+-----+---------+-------+
| emp_no | int | NO | PRI | NULL | |
| birth_date | date | NO | | NULL | |
| first_name | varchar(16) | NO | | NULL | |
| last_name | varchar(16) | NO | | NULL | |
| fullname | varchar(32) | YES | | NULL | | -- 表新增字段,导出数据文件中不存在
| gender | enum('M','F') | NO | | NULL | |
| hire_date | date | NO | | NULL | |
| modify_date | datetime | YES | | NULL | | -- 表新增字段,导出数据文件中不存在
| delete_flag | char(1) | YES | | NULL | | -- 表新增字段,导出数据文件中不存在
+-------------+---------------+------+-----+---------+-------+
-- 导出的数据与字段对应关系
emp_no birth_date first_name last_name gender hire_date
"10001" "1953-09-02" "Georgi" "Facello" "M" "1986-06-26"
"10002" "1964-06-02" "Bezalel" "Simmel" "F" "1985-11-21"
"10003" "1959-12-03" "Parto" "Bamford" "M" "1986-08-28"
"10004" "1954-05-01" "Chirstian" "Koblick" "M" "1986-12-01"
"10005" "1955-01-21" "Kyoichi" "Maliniak" "M" "1989-09-12"
"10006" "1953-04-20" "Anneke" "Preusig" "F" "1989-06-02"
"10007" "1957-05-23" "Tzvetan" "Zielinski" "F" "1989-02-10"
"10008" "1958-02-19" "Saniya" "Kalloufi" "M" "1994-09-15"
"10009" "1952-04-19" "Sumant" "Peac" "F" "1985-02-18"
"10010" "1963-06-01" "Duangkaew" "Piveteau" "F" "1989-08-24"
四、LOAD 场景示例
场景1. LOAD 文件中的字段比数据表中的字段多
只需要文本文件中部分数据导入到数据表中
-- 临时创建2个字段的表结构
SQL > create table emp_tmp select emp_no,hire_date from emp;
SQL > desc emp_tmp;
+-----------+------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-----------+------+------+-----+---------+-------+
| emp_no | int | NO | | NULL | |
| hire_date | date | NO | | NULL | |
+-----------+------+------+-----+---------+-------+
-- 导入数据语句
load data infile '/data/mysql/3306/tmp/employees.txt'
replace into table demo.emp_tmp
character set utf8mb4
fields terminated by ','
enclosed by '"'
lines terminated by '\n'
(@C1,@C2,@C3,@C4,@C5,@C6) -- 该部分对应employees.txt文件中6列数据
-- 只对导出数据中指定的2个列与表中字段做匹配,mapping关系指定的顺序不影响导入结果
set hire_date=@C6,
emp_no=@C1;
-- 导入数据结果示例
SQL > select * from emp_tmp;
+--------+------------+
| emp_no | hire_date |
+--------+------------+
| 10001 | 1986-06-26 |
| 10002 | 1985-11-21 |
| 10003 | 1986-08-28 |
| 10004 | 1986-12-01 |
| 10005 | 1989-09-12 |
| 10006 | 1989-06-02 |
| 10007 | 1989-02-10 |
| 10008 | 1994-09-15 |
| 10009 | 1985-02-18 |
| 10010 | 1989-08-24 |
+--------+------------+
10 rows in set (0.0016 sec)
场景 2. LOAD 文件中的字段比数据表中的字段少
表字段不仅包含文本文件中所有数据,还包含了额外的字段
-- 导入数据语句
load data infile '/data/mysql/3306/tmp/employees.txt'
replace into table demo.emp
character set utf8mb4
fields terminated by ','
enclosed by '"'
lines terminated by '\n'
(@C1,@C2,@C3,@C4,@C5,@C6) -- 该部分对应employees.txt文件中6列数据
-- 将文件中的字段与表中字段做mapping对应,表中多出的字段不做处理
set emp_no=@C1,
birth_date=@C2,
first_name=@C3,
last_name=@C4,
gender=@C5,
hire_date=@C6;
场景3. LOAD 生成自定义字段数据
从场景 2 的验证可以看到，emp 表中新增的字段
fullname,modify_date,delete_flag字段在导入时并未做处理，被置为了 NULL 值，如果需要对其进行处理，可在 LOAD 时通过MySQL支持的函数或给定固定值自行定义数据，对于文件中存在的字段也可做函数处理，结合导入导出，实现简单的 ETL 功能，如下所示：
-- 导入数据语句
load data infile '/data/mysql/3306/tmp/employees.txt'
replace into table demo.emp
character set utf8mb4
fields terminated by ','
enclosed by '"'
lines terminated by '\n'
(@C1,@C2,@C3,@C4,@C5,@C6) -- 该部分对应employees.txt文件中6列数据
-- 以下部分明确对表中字段与数据文件中的字段做Mapping关系,不存在的数据通过函数处理生成(也可设置为固定值)
set emp_no=@C1,
birth_date=@C2,
first_name=upper(@C3), -- 将导入的数据转为大写
last_name=lower(@C4), -- 将导入的数据转为小写
fullname=concat(first_name,' ',last_name), -- 对first_name和last_name做拼接
gender=@C5,
hire_date=@C6 ,
modify_date=now(), -- 生成当前时间数据
delete_flag=if(hire_date<'1988-01-01','Y','N'); -- 对需要生成的值基于某一列做条件运算
场景4. LOAD 定长数据
定长数据的特点如下所示，可以使用函数取出字符串中固定长度来生成指定列数据
SQL > select
c1 as sample_data,
substr(c1,1,3) as c1,
substr(c1,4,3) as c2,
substr(c1,7,2) as c3,
substr(c1,9,5) as c4,
substr(c1,14,3) as c5,
substr(c1,17,3) as c6 from t1
*************************** 1. row ***************************
sample_data: ABC余振兴CDMySQLEFG数据库
c1: ABC
c2: 余振兴
c3: CD
c4: MySQL
c5: EFG
c6: 数据库
定长数据导入需要明确每列数据占用的字符个数，以下直接使用 rpad 对现有的表数据填充空格的方式生成定长数据用作示例使用
-- 生成定长数据
SQL > select
concat(rpad(emp_no,10,' '),
rpad(birth_date,19,' '),
rpad(first_name,14,' '),
rpad(last_name,16,' '),
rpad(gender,2,' '),
rpad(hire_date,19,' ')) as fixed_length_data
from employees.employees limit 10;
+----------------------------------------------------------------------------------+
| fixed_length_data |
+----------------------------------------------------------------------------------+
| 10001 1953-09-02 Georgi Facello M 1986-06-26 |
| 10002 1964-06-02 Bezalel Simmel F 1985-11-21 |
| 10003 1959-12-03 Parto Bamford M 1986-08-28 |
| 10004 1954-05-01 Chirstian Koblick M 1986-12-01 |
| 10005 1955-01-21 Kyoichi Maliniak M 1989-09-12 |
| 10006 1953-04-20 Anneke Preusig F 1989-06-02 |
| 10007 1957-05-23 Tzvetan Zielinski F 1989-02-10 |
| 10008 1958-02-19 Saniya Kalloufi M 1994-09-15 |
| 10009 1952-04-19 Sumant Peac F 1985-02-18 |
| 10010 1963-06-01 Duangkaew Piveteau F 1989-08-24 |
+----------------------------------------------------------------------------------+
-- 导出定长数据
select
concat(rpad(emp_no,10,' '),
rpad(birth_date,19,' '),
rpad(first_name,14,' '),
rpad(last_name,16,' '),
rpad(gender,2,' '),
rpad(hire_date,19,' ')) as fixed_length_data
into outfile '/data/mysql/3306/tmp/employees_fixed.txt'
character set utf8mb4
lines terminated by '\n'
from employees.employees limit 10;
-- 导出数据示例
[root@10-186-61-162 tmp]# cat employees_fixed.txt
10001 1953-09-02 Georgi Facello M 1986-06-26
10002 1964-06-02 Bezalel Simmel F 1985-11-21
10003 1959-12-03 Parto Bamford M 1986-08-28
10004 1954-05-01 Chirstian Koblick M 1986-12-01
10005 1955-01-21 Kyoichi Maliniak M 1989-09-12
10006 1953-04-20 Anneke Preusig F 1989-06-02
10007 1957-05-23 Tzvetan Zielinski F 1989-02-10
10008 1958-02-19 Saniya Kalloufi M 1994-09-15
10009 1952-04-19 Sumant Peac F 1985-02-18
10010 1963-06-01 Duangkaew Piveteau F 1989-08-24
-- 导入定长数据
load data infile '/data/mysql/3306/tmp/employees_fixed.txt'
replace into table demo.emp
character set utf8mb4
fields terminated by ','
enclosed by '"'
lines terminated by '\n'
(@row) -- 对一行数据定义为一个整体
set emp_no = trim(substr(@row,1,10)),-- 使用substr取前10个字符,并去除头尾空格数据
birth_date = trim(substr(@row,11,19)),-- 后续字段以此类推
first_name = trim(substr(@row,30,14)),
last_name = trim(substr(@row,44,16)),
fullname = concat(first_name,' ',last_name), -- 对first_name和last_name做拼接
gender = trim(substr(@row,60,2)),
hire_date = trim(substr(@row,62,19)),
modify_date = now(),
delete_flag = if(hire_date<'1988-01-01','Y','N'); -- 对需要生成的值基于某一列做条件运算
1.默认情况下导入的顺序以文本文件 列-从左到右，行-从上到下 的顺序导入
2.如果表结构和文本数据不一致，建议将文本文件中的各列依次顺序编号并与表中字段建立 mapping 关系，以防数据导入到错误的字段
3.对于待导入的文本文件较大的场景，建议将文件 按行拆分 为多个小文件，如用 split 拆分
4.对文件导入后建议执行以下语句验证导入的数据是否有 Warning,ERROR 以及导入的数据量
GET DIAGNOSTICS @p1=NUMBER,@p2=ROW_COUNT;
select @p1 AS ERROR_COUNT,@p2 as ROW_COUNT;
5.文本文件数据与表结构存在过大的差异或数据需要做清洗转换，建议还是用专业的 ETL 工具或先粗略导入 MySQL 中再进行加工转换处理
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