技术阅读周刊第十一期

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技术阅读周刊，每周更新。

历史更新

A Comprehensive guide to Spring Boot 3.2 with Java 21, Virtual Threads, Spring Security, PostgreSQL, Flyway, Caching, Micrometer, Opentelemetry, JUnit 5, RabbitMQ, Keycloak Integration, and More! (10/17) | by Jonathan Chevalier | Nov, 2023 | Medium

URL: https://medium.com/@jojoooo/exploring-a-base-spring-boot-application-with-java-21-virtual-thread-spring-security-flyway-c0fde13c1eca#551c

本文讲解了基于最新的 Spring Boot3.2 和 Java 21 所使用到的技术栈

数据库

数据库使用 Postgres15 和 flyway 来管理数据库 schema 的迁移。
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异常处理

Spring6 实现了新的 RFC9457规范，实现以下接口：

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@Slf4j
@ControllerAdvice
@RequiredArgsConstructor
public class GlobalExceptionHandler extends ResponseEntityExceptionHandler {

  // Process @Valid
  @Override
  protected ResponseEntity<Object> handleMethodArgumentNotValid(
      @NonNull final MethodArgumentNotValidException ex,
      @NonNull final HttpHeaders headers,
      @NonNull final HttpStatusCode status,
      @NonNull final WebRequest request) {
    log.info(ex.getMessage(), ex);

    final List<ApiErrorDetails> errors = new ArrayList<>();

    for (final ObjectError err : ex.getBindingResult().getAllErrors()) {
      errors.add(
          ApiErrorDetails.builder()
              .pointer(((FieldError) err).getField())
              .reason(err.getDefaultMessage())
              .build());
    }

    return ResponseEntity.status(BAD_REQUEST)
        .body(this.buildProblemDetail(BAD_REQUEST, "Validation failed.", errors));
  }


  private ProblemDetail buildProblemDetail(
      final HttpStatus status, final String detail, final List<ApiErrorDetails> errors) {
  
    final ProblemDetail problemDetail =
        ProblemDetail.forStatusAndDetail(status, StringUtils.normalizeSpace(detail));
    
    // Adds errors fields on validation errors, following RFC 9457 best practices.
    if (CollectionUtils.isNotEmpty(errors)) {
      problemDetail.setProperty("errors", errors);
    }
  
   
    return problemDetail;
  }
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{
    "type": "about:blank",
    "title": "Bad Request",
    "status": 400,
    "detail": "Validation failed.",
    "instance": "/management/companies",
    "errors": [
        {
            "pointer": "name",
            "reason": "must not be blank"
        },
        {
            "pointer": "slug",
            "reason": "must not be blank"
        }
    ]
}

应用异常

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@Getter
public class RootException extends RuntimeException {

  @Serial private static final long serialVersionUID = 6378336966214073013L;

  private final HttpStatus httpStatus;
  private final List<ApiErrorDetails> errors = new ArrayList<>();

  public RootException(@NonNull final HttpStatus httpStatus) {
    super();
    this.httpStatus = httpStatus;
  }

  public RootException(@NonNull final HttpStatus httpStatus, final String message) {
    super(message);
    this.httpStatus = httpStatus;
  }
}

@ExceptionHandler(RootException.class)
public ResponseEntity<ProblemDetail> rootException(final RootException ex) {
  log.info(ex.getMessage(), ex);
  
  // Uses default message, can be adapted to use ex.getMessage().
  final ProblemDetail problemDetail =
      this.buildProblemDetail(
          ex.getHttpStatus(), API_DEFAULT_REQUEST_FAILED_MESSAGE, ex.getErrors());
  
  return ResponseEntity.status(ex.getHttpStatus()).body(problemDetail);
}

{
    "type": "about:blank",
    "title": "Internal Server Error",
    "status": 500,
    "detail": "Request failed.",
    "instance": "/back-office/hello-world"
}

异常降级

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@ResponseStatus(HttpStatus.INTERNAL_SERVER_ERROR)
@ExceptionHandler(Throwable.class)
public ProblemDetail handleAllExceptions(final Throwable ex, final WebRequest request) {
  log.warn(ex.getMessage(), ex);

  this.slack.notify(format("[API] InternalServerError: %s", ex.getMessage()));

  return this.buildProblemDetail(HttpStatus.INTERNAL_SERVER_ERROR, API_DEFAULT_ERROR_MESSAGE);
}

{
    "type": "about:blank",
    "title": "Internal Server Error",
    "status": 500,
    "detail": "Something went wrong. Please try again later or enter in contact with our service.",
    "instance": "/back-office/hello-world"
}

当有无法处理的异常时，就需要配置一个兜底的异常。

缓存

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<dependency>  
	<groupId>org.springframework.boot</groupId>  
	<artifactId>spring-boot-starter-cache</artifactId>  
</dependency>
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public interface CompanyRepository extends JpaRepository<Company, Long> {

  String CACHE_NAME = "company";

  @NonNull
  @Cacheable(value = CACHE_NAME, key = "{'byId', #id}")
  @Override
  Optional<Company> findById(@NonNull Long id);

  @Cacheable(value = CACHE_NAME, key = "{'bySlug', #slug}")
  Optional<Company> findBySlug(String slug);

  @Caching(
      evict = {
        @CacheEvict(value = CACHE_NAME, key = "{'byId', #entity.id}"),
        @CacheEvict(value = CACHE_NAME, key = "{'bySlug', #entity.slug}"),
      })
  @Override
  <S extends Company> @NonNull S save(@NonNull S entity);

  /*
   * This cache implementation is only valid if the table is not
   * frequently updated since it will clear the cache at every update operation
   * If you want to be more performant you can use something like https://github.com/ms100/cache-as-multi
   * */
  @NonNull
  @CacheEvict(cacheNames = CACHE_NAME, allEntries = true)
  @Override
  <S extends Company> List<S> saveAll(@NonNull Iterable<S> entities);

  @Caching(
      evict = {
        @CacheEvict(value = CACHE_NAME, key = "{'byId', #entity.id}"),
        @CacheEvict(value = CACHE_NAME, key = "{'bySlug', #entity.slug}"),
      })
  @Override
  void delete(@NonNull Company entity);

  /*
   * This cache implementation is only valid if the table is not
   * frequently updated since it will clear the cache at every delete operation
   * If you want to be more performant you can use something like https://github.com/ms100/cache-as-multi
   * */
  @CacheEvict(cacheNames = CACHE_NAME, allEntries = true)
  @Override
  void deleteAll(@NonNull Iterable<? extends Company> entities);
}

Spring 提供了标准的缓存接口，即便是后续需要切换到 Redis，使用的 API 和注解都不会发生改变。

线程

Java21 后支持了虚拟线程，几乎可以无限的实现线程，在 Spring Boot 3.2 需要单独开启。

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spring.threads.virtual.enabled

可观测性

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<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
  <groupId>io.micrometer</groupId>
  <artifactId>micrometer-registry-prometheus</artifactId>
</dependency>
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spring:
  endpoints:
    web:
      exposure:
        include: info, health, prometheus, metrics

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注意在生成环境不要暴露管理 API

Trace

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<dependency>
  <groupId>io.micrometer</groupId>
  <artifactId>micrometer-tracing-bridge-otel</artifactId>
</dependency>
<dependency>
  <groupId>net.ttddyy.observation</groupId>
  <artifactId>datasource-micrometer-spring-boot</artifactId>
  <version>${datasource-micrometer.version}</version>
</dependency>
<dependency>
  <groupId>io.opentelemetry</groupId>
  <artifactId>opentelemetry-exporter-otlp</artifactId>
  <version>${opentelemetry-exporter-otlp.version}</version>
</dependency>

同步请求的时候每个请求都会带上 traceId 和 spanId ，如果是异步请求时候需要配置：spring.reactor.context-propagation=true

如果使用 @Async时：

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@Configuration
public class TaskExecutorConfig {

  /*
   * Override default SimpleAsyncTaskExecutor to provide context propagation in @Async function
   * */
  @Bean
  public TaskExecutor simpleAsyncTaskExecutor() {
    final SimpleAsyncTaskExecutor taskExecutor = new SimpleAsyncTaskExecutor();
    taskExecutor.setTaskDecorator(new ContextPropagatingTaskDecorator());
    return taskExecutor;
  }
}

本地测试时候可以使用 Otel Desktop Viewer

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management:  
  tracing:
    sampling:
      probability: 1
  otlp:
    tracing:
      endpoint: http://localhost:4317

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Rust Vs Go: A Hands-On Comparison

URL: https://www.shuttle.rs/blog/2023/09/27/rust-vs-go-comparison

动手比较 Rust 和 Go

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本文是通过编写一个 web 服务来进行比较的。

  • Go 更加简单易学，同时标准库非常强大，只需要配合 gin+sqlx 这两个第三方库就能实现一个 web 服务
  • Rust也可以快速的构建一个安全的 web 服务，但需要依赖许多第三方库，比如http/JSON/模板引擎/时间处理等
  • 但 Rust 在异常处理方面心智负担更低，代码更容易阅读。
  • 如果是一个初创小团队，使用 Go 的上手难度确实更低；
  • 但如果团队愿意花时间投入到 Rust 中，结合他出色的错误处理，和强大的编译检查，长时间来看会得到更好的效果。

为什么要使用 Go 语言？Go 语言的优势在哪里？ - 知乎

URL: https://www.zhihu.com/question/21409296/answer/1040884859

图文并茂，讲解了 G-M-P 各自之间的关系，以及调度模型。

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  • G: Goroutine，用户创建的协程，图中搬运的砖头。
  • M: Machine，OS 内核的线程的抽象，代表真正执行的资源；对应到就是图中的地鼠，地鼠不能用户直接创建；得是砖头 G 太多，地鼠 M 本身太少，同时还有空闲的小车 P，此时就会从其他地方借一些地鼠 M 过来直到把小车 P 用完为止。
  • P: Processor 处理器，G 只有绑定到 P 才能被调度；P 是图中的小车，由用户设置的 GoMAXPROCS 决定小车的数量。

文章链接：

#Newletters