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关于mysql:技术分享-MySQL-SHELL-是如何操作关系表的

jiezi

作者：杨涛涛

资深数据库专家，专研 MySQL 十余年。善于 MySQL、PostgreSQL、MongoDB 等开源数据库相干的备份复原、SQL 调优、监控运维、高可用架构设计等。目前任职于爱可生，为各大运营商及银行金融企业提供 MySQL 相干技术支持、MySQL 相干课程培训等工作。

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前言

我之前有一篇介绍在 MySQL SHELL 环境中如何对文档类数据进行操作，然而 MySQL SHELL 性能很多，除了能够操作文档类数据，也能够对关系表进行各种 DDL,DML 等操作。这里我就用几个简略例子来示范下如何用 MySQL SHELL 操作关系表。

此处援用的数据库示例基于官网的 SAMPLE DATABASE：WORLD，表构造以及数据能够自行下载。

MySQL SHELL 对关系型数据库的操作波及到三个组件：

  1. MySQL：传统 mysql，操作比较简单，除了写法有些差别外，基本上等同于 SQL 操作。
  2. MySQL X：基于 X DEV 协定操作 mysql，其中蕴含很多类，除了能够操作文档数据，也能够操作关系表。
  3. SHELL：蕴含了以上两个组件，能够随便切换，重点在于如何抉择连贯协定。

咱们来顺次看看各个组件对关系表的罕用检索形式。

第一：mysql 组件

连贯数据库：mysql.get_session 或者 mysql.get_classic_session

能够用如下传统拼串形式连贯数据库：

MySQL  Py > connection_url="mysql://root:root@localhost/world?socket=(/var/lib/mysql/official/mysql.sock)"
MySQL  Py > ytt_cn1 = mysql.get_session(connection_url);
MySQL  Py > ytt_cn1
<ClassicSession:root@localhost>

也能够用字典的形式连贯数据库：

MySQL  Py > connection_url={"schema":"world","user":"root","password":"root","socket":"/var/lib/mysql/official/mysql.sock"}
MySQL  Py > ytt_cn1=mysql.get_session(connection_url);
MySQL  Py > ytt_cn1
<ClassicSession:root@/var%2Flib%2Fmysql%2Fofficial%2Fmysql.sock>

接下来能够用 ClassicSession 类提供的各种办法来对关系表进行相干操作，所有的操作都能够间接用函数 run_sql 来执行：

对表 city 查问：

MySQL  Py > ytt_cn1.run_sql("table city limit 1")
+----+-------+-------------+----------+------------+
| ID | Name  | CountryCode | District | Population |
+----+-------+-------------+----------+------------+
|  1 | Kabul | AFG         | Kabol    |    1780000 |
+----+-------+-------------+----------+------------+
1 row in set (0.0005 sec)

对表 city 插入：

MySQL  Py > ytt_cn1.run_sql("insert into city(name,countrycode,population,district) values ('test','CHN',1000000,'dd')")
Query OK, 1 row affected (0.0079 sec)
MySQL  Py > ytt_cn1.run_sql("select * from city where name ='test'")
+------+------+-------------+----------+------------+
| ID   | Name | CountryCode | District | Population |
+------+------+-------------+----------+------------+
| 4097 | test | CHN         | dd       |    1000000 |
+------+------+-------------+----------+------------+
1 row in set (0.0032 sec)

对表 city 更新：

MySQL  Py > ytt_cn1.run_sql("update city set name='who know ?'where id=4097")
Query OK, 1 row affected (0.0894 sec)

Rows matched: 1  Changed: 1  Warnings: 0
MySQL  Py > ytt_cn1.run_sql("select * from city where id=4097")
+------+------------+-------------+----------+------------+
| ID   | Name       | CountryCode | District | Population |
+------+------------+-------------+----------+------------+
| 4097 | who know ? | CHN         | dd       |    1000000 |
+------+------------+-------------+----------+------------+
1 row in set (0.0005 sec)

对表 city 删除：

MySQL  Py > ytt_cn1.run_sql("delete from city where id=4097")
Query OK, 1 row affected (0.0739 sec)
MySQL  Py > ytt_cn1.run_sql("select * from city where id=4097")
Empty set (0.0004 sec)

开启一个事务块:

MySQL  Py > ytt_cn1.start_transaction();
Query OK, 0 rows affected (0.0003 sec)
MySQL  Py > ytt_cn1.run_sql("delete from city where id =1")
Query OK, 1 row affected (0.0006 sec)
MySQL  Py > ytt_cn1.rollback();
Query OK, 0 rows affected (0.2070 sec)
MySQL  Py > ytt_cn1.run_sql("select * from city where id = 1")
+----+-------+-------------+----------+------------+
| ID | Name  | CountryCode | District | Population |
+----+-------+-------------+----------+------------+
|  1 | Kabul | AFG         | Kabol    |    1780000 |
+----+-------+-------------+----------+------------+
1 row in set (0.0004 sec)

敞开连贯：

MySQL  Py > ytt_cn1.close();
MySQL  Py > ytt_cn1
<ClassicSession:disconnected>

第二：mysqlx 组件

MySQL X 组件蕴含了很多类，上面我来举几个罕用的例子：

仍然是先连贯数据库 world：X 协定端口 33060 或者 X SOCKET（用 mysqlx.get_session 办法）。

MySQL  Py > connection_urlx="mysqlx://root:root@localhost/world?socket=(/var/lib/mysql/official/mysqlx.sock)"
MySQL  Py > ytt_cnx1=mysqlx.get_session(connection_urlx);

比方找出人口小于 800 的城市并且列出对应的国家名字：

SQL：select a.id,a.name,b.name country_name, a.population from city a join country b on (a.countrycode = b.code and a.population < 800);
SQLRESULT 类：相似于 mysql 游标用法 
MySQL  Py > sql1="select a.id,a.name,b.name country_name, a.population from city a join country b on (a.countrycode = b.code and a.population < 800)"
MySQL  Py > sql_result1=ytt_cnx1.run_sql(sql1)

获取前两行：默认不带字段名 

MySQL  Py > sql_result1.fetch_one()
[
    62,
    "The Valley",
    "Anguilla",
    595
]
MySQL  Py > sql_result1.fetch_one()
[
    1791,
    "Flying Fish Cove",
    "Christmas Island",
    700
]

获取带字段名的记录：

MySQL  Py > sql_result1.fetch_one_object();
{"country_name": "Cocos (Keeling) Islands", 
    "id": 2316, 
    "name": "Bantam", 
    "population": 503
}

一次性获取残余的行：

MySQL  Py > sql_result1.fetch_all()
[
    [
        2317,
        "West Island",
        "Cocos (Keeling) Islands",
        167
    ], 
    [
        2728,
        "Yaren",
        "Nauru",
        559
    ], 
    [
        2805,
        "Alofi",
        "Niue",
        682
    ], 
    [
        2912,
        "Adamstown",
        "Pitcairn",
        42
    ], 
    [
        3333,
        "Fakaofo",
        "Tokelau",
        300
    ], 
    [
        3538,
        "Città del Vaticano",
        "Holy See (Vatican City State)",
        455
    ]
]
SqlExecute 类：相似于 prepare 语句用法

比方把之前的人口判断条件替换为绑定变量（？或者变量 (:a)），这样能够不便多个条件一起查问。

MySQL  Py > sql2="select a.id,a.name,b.name country_name, a.population from city a join country b on (a.countrycode = b.code and a.population < ?)"
MySQL  Py > sql_result2=ytt_cnx1.sql(sql2);

给定两个不同的人口条件：

MySQL  Py > a=800
MySQL  Py > b=500

绑定变量执行后果：

MySQL  Py > sql_result2.bind(a)
+------+--------------------+-------------------------------+------------+
| id   | name               | country_name                  | population |
+------+--------------------+-------------------------------+------------+
|   62 | The Valley         | Anguilla                      |        595 |
| 1791 | Flying Fish Cove   | Christmas Island              |        700 |
| 2316 | Bantam             | Cocos (Keeling) Islands       |        503 |
| 2317 | West Island        | Cocos (Keeling) Islands       |        167 |
| 2728 | Yaren              | Nauru                         |        559 |
| 2805 | Alofi              | Niue                          |        682 |
| 2912 | Adamstown          | Pitcairn                      |         42 |
| 3333 | Fakaofo            | Tokelau                       |        300 |
| 3538 | Città del Vaticano | Holy See (Vatican City State) |        455 |
+------+--------------------+-------------------------------+------------+
9 rows in set (0.0022 sec)
MySQL  Py > sql_result2.bind(b)
+------+--------------------+-------------------------------+------------+
| id   | name               | country_name                  | population |
+------+--------------------+-------------------------------+------------+
| 2317 | West Island        | Cocos (Keeling) Islands       |        167 |
| 2912 | Adamstown          | Pitcairn                      |         42 |
| 3333 | Fakaofo            | Tokelau                       |        300 |
| 3538 | Città del Vaticano | Holy See (Vatican City State) |        455 |
+------+--------------------+-------------------------------+------------+
4 rows in set (0.0023 sec)
Table 类：获取以后连贯数据库下单张表，能够对这张表进行任何 DML 操作。（获取 Table 类之前，得先获取 Schema 类）
MySQL  Py > ytt_schema1=ytt_cnx1.get_schema('world')

MySQL  Py > ytt_tbname1=ytt_schema1.get_table('city');

查找人口少于 800 的记录：

MySQL  Py > ytt_tbname1.select().where("population<800")
+------+--------------------+-------------+-------------+------------+
| ID   | Name               | CountryCode | District    | Population |
+------+--------------------+-------------+-------------+------------+
|   62 | The Valley         | AIA         | –           |        595 |
| 1791 | Flying Fish Cove   | CXR         | –           |        700 |
| 2316 | Bantam             | CCK         | Home Island |        503 |
| 2317 | West Island        | CCK         | West Island |        167 |
| 2728 | Yaren              | NRU         | –           |        559 |
| 2805 | Alofi              | NIU         | –           |        682 |
| 2912 | Adamstown          | PCN         | –           |         42 |
| 3333 | Fakaofo            | TKL         | Fakaofo     |        300 |
| 3538 | Città del Vaticano | VAT         | –           |        455 |
+------+--------------------+-------------+-------------+------------+
9 rows in set (0.0024 sec)

还能够持续排序以及限度记录数输入：

MySQL  Py > ytt_tbname1.select().where("population<800").order_by("population desc").limit(3)
+------+------------------+-------------+----------+------------+
| ID   | Name             | CountryCode | District | Population |
+------+------------------+-------------+----------+------------+
| 1791 | Flying Fish Cove | CXR         | –        |        700 |
| 2805 | Alofi            | NIU         | –        |        682 |
|   62 | The Valley       | AIA         | –        |        595 |
+------+------------------+-------------+----------+------------+
3 rows in set (0.0024 sec)
Table 类蕴含几个子类：TableSelect、TableInsert、TableUpdate、TableDelete。

TableSelect：保留查问后果

之前查找人口小于 800 的记录后果即为 TableSelect，能够基于此类来后续操作 

MySQL  Py > tbselect1=ytt_tbname1.select().where("population<800")

只拿出局部字段：

MySQL  Py > tbselect1.select("[id,name]").order_by("population desc").limit(2);
+----------------------------+
| JSON_ARRAY(`id`,`name`)    |
+----------------------------+
| [1791, "Flying Fish Cove"] |
| [2805, "Alofi"]            |
+----------------------------+
2 rows in set (0.0031 sec)

TableInsert：执行插入语句

插入一行：

MySQL  Py > ytt_tbname1.count()
4081
MySQL  Py > tbinsert1=ytt_tbname1.insert(["name","population","countrycode","district"]).values('test',1000000,'CHN','dd');
MySQL  Py > tbinsert1.execute();
Query OK, 1 item affected (0.0054 sec)
MySQL  Py > ytt_tbname1.count()
4082

插入多行：有两种办法

多 VALUES 模式：

MySQL  Py > tbinsert1=ytt_tbname1.insert(["name","population","countrycode","district"]).values('test',1000000,'CHN','dd').values('test',1000000,'CHN','dd');
MySQL  Py > tbinsert1.execute()
Query OK, 2 items affected (0.0325 sec)

Records: 2  Duplicates: 0  Warnings: 0
MySQL  Py > 

MySQL  Py > ytt_tbname1.count()
4084

屡次执行或者蕴含在事务块里：

MySQL  Py > ytt_cnx1.start_transaction();
Query OK, 0 rows affected (0.0004 sec)
MySQL  Py > tbinsert1=ytt_tbname1.insert(["name","population","countrycode","district"]).values('test',1000000,'CHN','dd');
MySQL  Py > tbinsert1
Query OK, 1 item affected (0.0008 sec)
MySQL  Py > tbinsert1
Query OK, 1 item affected (0.0006 sec)
MySQL  Py > tbinsert1
Query OK, 1 item affected (0.0008 sec)
MySQL  Py > tbinsert1
Query OK, 1 item affected (0.0006 sec)
MySQL  Py > ytt_cnx1.commit();
Query OK, 0 rows affected (0.2737 sec)
MySQL  Py > ytt_tbname1.count()
4088

TableUpdate：执行更新语句 

MySQL  Py > tbupdate1=ytt_tbname1.update().set('district','nothing').where("name='test'")
MySQL  Py > tbupdate1
Query OK, 0 items affected (0.0048 sec)

Rows matched: 9  Changed: 9  Warnings: 0

TableDelete：执行删除语句 

MySQL  Py > tbdelete1=ytt_tbname1.delete().where("district='nothing'");
MySQL  Py > tbdelete1
Query OK, 9 items affected (0.0112 sec)
MySQL  Py > ytt_tbname1.count()
4079

第三：SHELL 组件

SHELL 组件能够在 MySQL 和 MySQL X 间随便切换，并且连贯后，蕴含了一个默认数据库类“db”，db 等价于 ytt_cnx1.get_current_schema()，

MySQL  Py > ytt_cnx_shell1=shell.connect(connection_urlx)
Creating an X protocol session to 'root@localhost/world'
Fetching schema names for autocompletion... Press ^C to stop.
Your MySQL connection id is 10 (X protocol)
Server version: 8.0.23 MySQL Community Server - GPL
Default schema `world` accessible through db

仍然还是操作表 city，

MySQL  localhost+ ssl  world  Py > ytt_tbname2=db.get_table("city")
MySQL  localhost+ ssl  world  Py > ytt_tbname2
<Table:city>

之后的操作和之前 mysqlx 的一样。

MySQL  localhost+ ssl  world  Py > ytt_tbname2.select(['id','name']).where("population<800").order_by("id desc").limit(3);
+------+--------------------+
| id   | name               |
+------+--------------------+
| 3538 | Città del Vaticano |
| 3333 | Fakaofo            |
| 2912 | Adamstown          |
+------+--------------------+
3 rows in set (0.0011 sec)

所以如果用 MySQL SHELL 来操作 mysql 关系表，举荐用 SHELL 组件的形式，非常灵活。

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