How to achieve read-write separation, Spring Boot project, the database is MySQL, and the persistence layer uses MyBatis.
In fact, it is very simple to implement this. First think about a question:
In a high-concurrency scenario, everything about the database What optimization methods are there?
The following implementation methods are commonly used: read-write separation, caching, master-slave architecture cluster, sub-database and sub-table, etc.
In Internet applications, most of the scenarios involve more reading and less writing. Two libraries are set up, the main library and the reading library.
The main library is responsible for writing, and the slave library is mainly responsible for reading. A reading library cluster can be established to reduce read and write conflicts and relieve database load by isolating the read and write functions on the data source. , the purpose of protecting the database. In actual use, any part involving writing is directly switched to the main library, and the reading part is directly switched to the reading library. This is a typical read-write separation technology.
This article will focus on the separation of reading and writing and explore how to achieve it.
Limitations of master-slave synchronization: This is divided into master database and slave database. The master database and slave database maintain the same database structure. The master database Responsible for writing. When writing data, the data will be automatically synchronized to the slave database. The slave database is responsible for reading. When a read request comes, the data is read directly from the reading database, and the master database will automatically copy the data to the slave database. However, this blog does not introduce this part of the configuration knowledge, because it is more focused on operation and maintenance work.
There is a problem involved here:
The delay problem of master-slave replication. When writing to the main database, a read request suddenly comes, and the data is still there. Without complete synchronization, there will be situations where the read requested data cannot be read or the data read is less than the original value. The simplest specific solution is to temporarily point the read request to the main library, but at the same time it also loses part of the meaning of master-slave separation. That is to say, in the strict sense of data consistency scenarios, read-write separation is not completely suitable. Pay attention to the timeliness of updates as a shortcoming of the use of read-write separation.
Okay, this part is just for understanding. Next, let’s look at how to achieve read and write separation through Java code:
Note: This project needs to introduce the following dependencies: Spring Boot, spring-aop, spring-jdbc, aspectjweaver, etc.
Program Yuan: Only 30 days, what should I do? Prepare?
We need to configure the master-slave database, master-slave Database configuration is generally written in the configuration file. Through the @ConfigurationProperties annotation, the properties in the configuration file (generally named: application.Properties
) can be mapped to specific class properties, so that the written values can be read and injected into the specific code configuration. , in accordance with the principle that custom is greater than agreement, we all mark the main library as master and the slave library as slave.
This project uses Alibaba's druid database connection pool and uses the build builder mode to create DataSource objects. DataSource is the data source abstracted at the code level. Then you need to configure sessionFactory, sqlTemplate, transaction manager, etc.
/** * 主从配置 */ @Configuration @MapperScan(basePackages = "com.wyq.mysqlreadwriteseparate.mapper", sqlSessionTemplateRef = "sqlTemplate") public class DataSourceConfig { /** * 主库 */ @Bean @ConfigurationProperties(prefix = "spring.datasource.master") public DataSource master() { return DruidDataSourceBuilder.create().build(); } /** * 从库 */ @Bean @ConfigurationProperties(prefix = "spring.datasource.slave") public DataSource slaver() { return DruidDataSourceBuilder.create().build(); } /** * 实例化数据源路由 */ @Bean public DataSourceRouter dynamicDB(@Qualifier("master") DataSource masterDataSource, @Autowired(required = false) @Qualifier("slaver") DataSource slaveDataSource) { DataSourceRouter dynamicDataSource = new DataSourceRouter(); Map<Object, Object> targetDataSources = new HashMap<>(); targetDataSources.put(DataSourceEnum.MASTER.getDataSourceName(), masterDataSource); if (slaveDataSource != null) { targetDataSources.put(DataSourceEnum.SLAVE.getDataSourceName(), slaveDataSource); } dynamicDataSource.setTargetDataSources(targetDataSources); dynamicDataSource.setDefaultTargetDataSource(masterDataSource); return dynamicDataSource; } /** * 配置sessionFactory * @param dynamicDataSource * @return * @throws Exception */ @Bean public SqlSessionFactory sessionFactory(@Qualifier("dynamicDB") DataSource dynamicDataSource) throws Exception { SqlSessionFactoryBean bean = new SqlSessionFactoryBean(); bean.setMapperLocations( new PathMatchingResourcePatternResolver().getResources("classpath*:mapper/*Mapper.xml")); bean.setDataSource(dynamicDataSource); return bean.getObject(); } /** * 创建sqlTemplate * @param sqlSessionFactory * @return */ @Bean public SqlSessionTemplate sqlTemplate(@Qualifier("sessionFactory") SqlSessionFactory sqlSessionFactory) { return new SqlSessionTemplate(sqlSessionFactory); } /** * 事务配置 * * @param dynamicDataSource * @return */ @Bean(name = "dataSourceTx") public DataSourceTransactionManager dataSourceTransactionManager(@Qualifier("dynamicDB") DataSource dynamicDataSource) { DataSourceTransactionManager dataSourceTransactionManager = new DataSourceTransactionManager(); dataSourceTransactionManager.setDataSource(dynamicDataSource); return dataSourceTransactionManager; } }
Routing is very important in master-slave separation, basically The core of read-write switching. Spring provides AbstractRoutingDataSource
to select the current data source according to user-defined rules. Its function is to set the data source used before executing the query, implement dynamic routing data source, and execute it before each database query operation. The abstract method determineCurrentLookupKey()
determines which data source to use.
In order to have a global data source manager, we need to introduce the DataSourceContextHolder database context manager, which can be understood as a global variable and can be accessed at any time (see detailed introduction below). Its main function is Save the current data source.
public class DataSourceRouter extends AbstractRoutingDataSource { /** * 最终的determineCurrentLookupKey返回的是从DataSourceContextHolder中拿到的,因此在动态切换数据源的时候注解 * 应该给DataSourceContextHolder设值 * * @return */ @Override protected Object determineCurrentLookupKey() { return DataSourceContextHolder.get(); } }
数据源上下文保存器,便于程序中可以随时取到当前的数据源,它主要利用 ThreadLocal 封装,因为 ThreadLocal 是线程隔离的,天然具有线程安全的优势。这里暴露了 set 和 get、clear 方法,set 方法用于赋值当前的数据源名,get 方法用于获取当前的数据源名称,clear 方法用于清除 ThreadLocal 中的内容,因为 ThreadLocal 的 key 是 weakReference 是有内存泄漏风险的,通过 remove 方法防止内存泄漏。
/** * 利用ThreadLocal封装的保存数据源上线的上下文context */ public class DataSourceContextHolder { private static final ThreadLocal<String> context = new ThreadLocal<>(); /** * 赋值 * * @param datasourceType */ public static void set(String datasourceType) { context.set(datasourceType); } /** * 获取值 * @return */ public static String get() { return context.get(); } public static void clear() { context.remove(); } }
首先我们来定义一个@DataSourceSwitcher
注解,拥有两个属性
① 当前的数据源② 是否清除当前的数据源,并且只能放在方法上,(不可以放在类上,也没必要放在类上,因为我们在进行数据源切换的时候肯定是方法操作),该注解的主要作用就是进行数据源的切换,在 dao 层进行操作数据库的时候,可以在方法上注明表示的是当前使用哪个数据源。
@DataSourceSwitcher
注解的定义:
@Retention(RetentionPolicy.RUNTIME) @Target(ElementType.METHOD) @Documented public @interface DataSourceSwitcher { /** * 默认数据源 * @return */ DataSourceEnum value() default DataSourceEnum.MASTER; /** * 清除 * @return */ boolean clear() default true; }
DataSourceAop
配置:
为了赋予@DataSourceSwitcher
注解能够切换数据源的能力,我们需要使用 AOP,然后使用@Aroud
注解找到方法上有@DataSourceSwitcher.class
的方法,然后取注解上配置的数据源的值,设置到 DataSourceContextHolder
中,就实现了将当前方法上配置的数据源注入到全局作用域当中。
@Slf4j @Aspect @Order(value = 1) @Component public class DataSourceContextAop { @Around("@annotation(com.wyq.mysqlreadwriteseparate.annotation.DataSourceSwitcher)") public Object setDynamicDataSource(ProceedingJoinPoint pjp) throws Throwable { boolean clear = false; try { Method method = this.getMethod(pjp); DataSourceSwitcher dataSourceSwitcher = method.getAnnotation(DataSourceSwitcher.class); clear = dataSourceSwitcher.clear(); DataSourceContextHolder.set(dataSourceSwitcher.value().getDataSourceName()); log.info("数据源切换至:{}", dataSourceSwitcher.value().getDataSourceName()); return pjp.proceed(); } finally { if (clear) { DataSourceContextHolder.clear(); } } } private Method getMethod(JoinPoint pjp) { MethodSignature signature = (MethodSignature) pjp.getSignature(); return signature.getMethod(); } }
在配置好了读写分离之后,就可以在代码中使用了,一般而言我们使用在 service 层或者 dao 层,在需要查询的方法上添加@DataSourceSwitcher(DataSourceEnum.SLAVE)
,它表示该方法下所有的操作都走的是读库。在需要 update 或者 insert 的时候使用@DataSourceSwitcher(DataSourceEnum.MASTER)
表示接下来将会走写库。
其实还有一种更为自动的写法,可以根据方法的前缀来配置 AOP 自动切换数据源,比如 update、insert、fresh 等前缀的方法名一律自动设置为写库。select、get、query 等前缀的方法名一律配置为读库,这是一种更为自动的配置写法。缺点就是方法名需要按照 aop 配置的严格来定义,否则就会失效。
@Service public class OrderService { @Resource private OrderMapper orderMapper; /** * 读操作 * * @param orderId * @return */ @DataSourceSwitcher(DataSourceEnum.SLAVE) public List<Order> getOrder(String orderId) { return orderMapper.listOrders(orderId); } /** * 写操作 * * @param orderId * @return */ @DataSourceSwitcher(DataSourceEnum.MASTER) public List<Order> insertOrder(Long orderId) { Order order = new Order(); order.setOrderId(orderId); return orderMapper.saveOrder(order); } }
还是画张图来简单总结一下:
This article introduces how to achieve database read-write separation. Note that the core point of read-write separation is data routing. You need to inherit AbstractRoutingDataSource
and overwrite its determineCurrentLookupKey. ()
method. At the same time, you need to pay attention to the global context manager DataSourceContextHolder
, which is the main class that saves the data source context and is also the data source value found in the routing method. It is equivalent to a transfer station for data sources, and combined with the bottom layer of jdbc-Template to create and manage data sources, transactions, etc., our database read-write separation is perfectly realized.
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