Sharding JDBC如何分庫分表？看完你就會了

Sharding JDBC的操作分為配置使用、讀寫分離、分庫分表以及應用等，今天我們主要來了解一下關于分庫分表的操作，如果你對此感興趣的話，那我們就開始吧。
環境準備
pom.xml
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>2.1.3.RELEASE</version></parent>
<properties>
<java.version>1.8</java.version>
<sharding.version>3.1.0</sharding.version></properties>
<dependencies>
<dependency>
<groupId>io.shardingsphere</groupId>
<artifactId>sharding-jdbc-core</artifactId>
<version>${sharding.version}</version>
</dependency>

<dependency>
    <groupId>io.shardingsphere</groupId>
    <artifactId>sharding-jdbc-spring-boot-starter</artifactId>
    <version>${sharding.version}</version>
</dependency>

<dependency>
    <groupId>com.alibaba</groupId>
    <artifactId>druid</artifactId>
    <version>1.1.10</version>
</dependency>

<dependency>
    <groupId>org.mybatis</groupId>
    <artifactId>mybatis</artifactId>
    <version>3.4.5</version>
</dependency>

<dependency>
    <groupId>org.mybatis.spring.boot</groupId>
    <artifactId>mybatis-spring-boot-starter</artifactId>
    <version>1.3.1</version>
</dependency>

<dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
    <version>5.1.46</version>
</dependency>

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter</artifactId>
</dependency>

<dependency>
    <groupId>org.projectlombok</groupId>
    <artifactId>lombok</artifactId>
</dependency>

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-test</artifactId>
    <scope>test</scope>
</dependency></dependencies>

<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins></build>
domain
// 建立domain@Setter@Getter@ToString@NoArgsConstructor@AllArgsConstructorpublic class Employee {
private Long id;
private String name;}
配置類
@SpringBootApplication@MapperScan("cn.wolfcode.sharding.mapper")public class ShardingApplication { }
分庫分表
案例模型
把數據分別存放在兩臺服務器的兩個數據庫中表，通過分片算法來決定當前的數據存放在哪個數據庫的哪個表中，由于一個連接池只能連接一個特定的數據庫，所以這里需要創建多個連接池對象
建表
-- 分別在2臺服務器中建立數據庫sharding，并且建表employee_0和employee_1CREATE TABLE employee_0 (
id bigint(20) PRIMARY KEY AUTO_INCREMENT,
name varchar(255) DEFAULT NULL) ENGINE=InnoDB DEFAULT CHARSET=utf8;-- ###################################CREATE TABLE employee_1 (
id bigint(20) PRIMARY KEY AUTO_INCREMENT,
name varchar(255) DEFAULT NULL) ENGINE=InnoDB DEFAULT CHARSET=utf8;
application.properties

定義連接池

sharding.jdbc.datasource.names=db0,db1

格式sharding.jdbc.datasource.連接池名.xxx:設置4要素信息

sharding.jdbc.datasource.db0.type=com.alibaba.druid.pool.DruidDataSource
sharding.jdbc.datasource.db0.driver-class-name=com.mysql.jdbc.Driver
sharding.jdbc.datasource.db0.url=jdbc:mysql://db0Ip:port/sharing
sharding.jdbc.datasource.db0.username=xxx
sharding.jdbc.datasource.db0.password=xxx

sharding.jdbc.datasource.db1.type=com.alibaba.druid.pool.DruidDataSource
sharding.jdbc.datasource.db1.driver-class-name=com.mysql.jdbc.Driver
sharding.jdbc.datasource.db1.url=jdbc:mysql://db1Ip:port/sharing
sharding.jdbc.datasource.db1.username=xxx
sharding.jdbc.datasource.db1.password=xxx

設置分庫規則

sharding.jdbc.config.sharding.default-database-strategy.inline.sharding-column：分庫列

sharding.jdbc.config.sharding.default-database-strategy.inline.algorithm-expression：分庫算法

sharding.jdbc.config.sharding.default-database-strategy.inline.sharding-column=id
sharding.jdbc.config.sharding.default-database-strategy.inline.algorithm-expression=db$->{id % 2}

綁定邏輯表

sharding.jdbc.config.sharding.binding-tables=employee

設置分表規則

sharding.jdbc.config.sharding.tables.邏輯表.actual-data-nodes：邏輯表對應的真實表

sharding.jdbc.config.sharding.tables.邏輯表.table-strategy.inline.sharding-column：分表列

sharding.jdbc.config.sharding.tables.邏輯表.table-strategy.inline.algorithm-expression：分表算法

sharding.jdbc.config.sharding.tables.邏輯表.key-generator-column-name：主鍵列

sharding.jdbc.config.sharding.tables.employee.actual-data-nodes=db$->{0..1}.employee$->{0..1}
sharding.jdbc.config.sharding.tables.employee.table-strategy.inline.sharding-column=id
sharding.jdbc.config.sharding.tables.employee.table-strategy.inline.algorithm-expression=employee$->{id % 2}
sharding.jdbc.config.sharding.tables.employee.key-generator-column-name=id

打印日志

sharding.jdbc.config.props.sql.show=true
mapper
/**

• 這里寫的employee表是上面所配置的邏輯表

• 底層會根據分片規則，把我們寫的邏輯表改寫為數據庫中的真實表
  /@Mapperpublic interface EmployeeMapper {
  @Select("select from employee")
  List<Employee> selectAll();

  @Insert("insert into employee (name) values (#{name})")
  void inser(Employee entity);}
  測試
  @RunWith(SpringRunner.class)@SpringBootTest(classes=ShardingApplication.class)public class ShardingApplicationTests {

  @Autowired
  private EmployeeMapper employeeMapper;

  @Test
  public void save() {
  for (int i = 0; i < 10; i++) {
  Employee employee = new Employee();
  employee.setName("xx"+i);
  employeeMapper.inser(employee);
  }
  }

  @Test
  public void list() {
  employeeMapper.selectAll().forEach(System.out::println);
  }}
  優缺點
  ?拆分后單表數據量比較小,單表大數據被拆分,解決了單表大數據訪問問題
  ?分表以什么切分如果弄的不好,導致多次查詢,而且有時候要跨庫操作,甚至導致join無法使用,對排序分組等有性能影響
  ?之前的原子操作被拆分成多個操作,事務處理變得復雜
  ?多個DB維護成本增加

看完這些操作后不妨自己去試試，實踐才能檢驗真知，如果遇到了問題，也可以及時向我詢問，我也會盡我所力幫助你。