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https://daidawang.github.ioA technical blog featuring deep dives into the Spring Framework, including Spring Boot lifecycle, BeanFactory, ApplicationContext, and AOP. The content also covers distributed system theories such as CAP and BASE, distributed ID generation (Snowflake), LBS spatial queries for administrative region parsing, and guides on Node.js and Hexo deployment.
Spring Boot's MVC auto-configuration is driven by four primary configuration classes:
ServletWebServerFactoryAutoConfiguration: Configures the embedded Tomcat server factory.DispatcherServletAutoConfiguration: Configures the DispatcherServlet.WebMvcAutoConfiguration: Configures various WebMVC components.ErrorMvcAutoConfiguration: Configures MVC error handling.Spring uses BeanDefinition to encapsulate the basic information required to create a Bean. The general workflow for adding a Bean to the container is:
BeanDefinitionReader (e.g., XmlBeanDefinitionReader) or ClassPathBeanDefinitionScanner (which powers @ComponentScan) to read configuration/annotations and generate a BeanDefinition.BeanDefinition into a BeanDefinitionRegistry.BeanDefinition from the registry to instantiate the Bean.SingletonBeanRegistry (the first level of the three-level cache) to avoid repeated creation.The AnnotationAwareAspectJAutoProxyCreator is a Bean Post Processor responsible for two primary tasks in Spring AOP:
@Aspect annotations) into low-level aspects (Advisors).ProxyFactory based on the identified aspect information.It operates during the Bean lifecycle, allowing extensions either before dependency injection or after Bean initialization.
ClassPathXmlApplicationContext is a Spring container implementation that reads XML configuration files from the classpath to initialize and manage beans.TCC is a distributed transaction pattern that ensures eventual consistency by splitting a business operation into three phases: Try, Confirm, and Cancel.
Advantages:
Disadvantages:
BASE is a pragmatic approach to the CAP theorem, prioritizing availability over strong consistency to achieve eventual consistency based on business needs.
Seata is a distributed transaction framework utilizing three primary roles:
Supported Modes:
The CAP theorem states that a distributed system can only satisfy two out of three requirements: Consistency, Availability, and Partition Tolerance. Since Partition Tolerance is essential for distributed systems, the choice is typically between CP and AP.
Trade-off Scenarios:
ConfigurableApplicationContext extends ApplicationContext, which in turn extends BeanFactory. BeanFactory is the core Spring IoC container providing basic bean management. ApplicationContext is an extension of BeanFactory that adds enterprise-specific functionality. In most implementations, ApplicationContext contains a BeanFactory as a member variable, and calls to context.getBean() are delegated to the underlying BeanFactory.In Spring AOP, @Aspect represents a high-level aspect definition, while Advisor is the low-level representation used at runtime. Spring converts high-level aspect annotations into low-level Advisors. The common high-level notification annotations include:
@Before: Pre-processing@AfterReturning: Post-processing after successful return@AfterThrowing: Processing after an exception is thrown@After: Final processing (regardless of outcome)@Around: Full wrap-around processingorder-service), add the following dependencies to your pom.xml. Note that the seata-spring-boot-starter is explicitly versioned to avoid using the older version (1.3.0) bundled with the Spring Cloud Alibaba starter.<!-- seata -->
<dependency>
<groupId>com.alibaba.cloud</groupId>
<artifactId>spring-cloud-starter-alibaba-seata</artifactId>
<exclusions>
<!-- Exclude lower version 1.3.0 -->
<exclusion>
<artifactId>seata-spring-boot-starter</artifactId>
<groupId>io.seata</groupId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>io.seata</groupId>
<artifactId>seata-spring-boot-starter</artifactId>
<!-- Use version 1.4.2 -->
<version>${seata.version}</version>
</dependency>