日志痛点:
请求参数散落在各处?
响应数据无法统一记录?
日志与业务代码严重耦合?
解决方案: 一个Filter同时拦截请求和响应,实现日志采集自动化!
1. 过滤器设计亮点
✅ 请求参数捕获:GET/POST参数统一解析
✅ 响应结果截取:支持JSON/XML等文本响应
✅ 零代码侵入:不修改业务代码即可植入监控
✅ JDK1.8完美兼容:无任何新特性依赖
1. 过滤器核心代码(可直接复制)
import org.springframework.web.filter.OncePerRequestFilter;
import javax.servlet.FilterChain;
import javax.servlet.ServletException;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import java.io.IOException;
public class RequestResponseLogFilter extends OncePerRequestFilter {
@Override
protected void doFilterInternal(HttpServletRequest request,
HttpServletResponse response,
FilterChain filterChain)
throws ServletException, IOException {
// 包装请求响应对象
ContentCachingRequestWrapper wrappedRequest =
new ContentCachingRequestWrapper(request);
ContentCachingResponseWrapper wrappedResponse =
new ContentCachingResponseWrapper(response);
try {
// 执行后续过滤器链
filterChain.doFilter(wrappedRequest, wrappedResponse);
// 记录日志(核心逻辑)
logRequest(wrappedRequest);
logResponse(wrappedResponse);
} finally {
// 必须执行响应回写
wrappedResponse.copyBodyToResponse();
}
}
// 请求日志方法
private void logRequest(ContentCachingRequestWrapper request) {
String method = request.getMethod();
String url = request.getRequestURL().toString();
String params = getRequestParams(request);
System.out.printf("[请求] %s %s | 参数=%s%n", method, url, params);
}
// 响应日志方法
private void logResponse(ContentCachingResponseWrapper response) throws IOException {
int status = response.getStatus();
String body = getResponseBody(response);
System.out.printf("[响应] 状态码=%d | 内容=%s%n", status, body);
}
// 获取请求参数工具方法
private String getRequestParams(ContentCachingRequestWrapper request) {
try {
if ("GET".equalsIgnoreCase(request.getMethod())) {
return request.getQueryString();
} else {
byte[] body = request.getContentAsByteArray();
return new String(body, request.getCharacterEncoding());
}
} catch (Exception e) {
return "[参数解析失败]";
}
}
// 获取响应内容工具方法
private String getResponseBody(ContentCachingResponseWrapper response) throws IOException {
byte[] content = response.getContentAsByteArray();
return new String(content, response.getCharacterEncoding());
}
@Override
public void init(FilterConfig filterConfig) {}
@Override
public void destroy() {}
}
xml
<!-- 核心包装类 -->
<dependency>
<groupId>org.apache.tomcat</groupId>
<artifactId>tomcat-catalina</artifactId>
<version>9.0.65</version>
</dependency>
xml
<filter>
<filter-name>RequestResponseLogFilter</filter-name>
<filter-class>com.example.RequestResponseLogFilter</filter-class>
</filter>
<filter-mapping>
<filter-name>RequestResponseLogFilter</filter-name>
<url-pattern>/*</url-pattern> <!-- 拦截所有请求 -->
<dispatcher>REQUEST</dispatcher>
</filter-mapping>
@Bean
public FilterRegistrationBean<RequestResponseLogFilter> logFilter(){
FilterRegistrationBean<RequestResponseLogFilter> registrationBean = new FilterRegistrationBean<>();
registrationBean.setFilter(new RequestResponseLogFilter());
registrationBean.addUrlPatterns("/*");
return registrationBean;
}
[REQUEST] POST http://api/user/login | 参数=username=admin&password=123456 | 时间=Wed Oct 05 14:30:00 CST 2023
[RESPONSE] 状态码=200 | 响应内容={"code":0,"msg":"登录成功"} | 耗时=120ms
// 在构造方法中设置最大缓存
new ContentCachingRequestWrapper(request, 1024 * 1024); // 1MB
request.setCharacterEncoding("UTF-8");
response.setCharacterEncoding("UTF-8");
params.replaceAll("password=\\w+", "password=***");
CompletableFuture.runAsync(() -> log.info(logContent));
<Connector port="8443" protocol="org.apache.coyote.http11.Http11NioProtocol"
SSLEnabled="true" scheme="https" secure="true"/>
sql
-- 日志分析SQL示例
SELECT
request_uri,
COUNT(*) as total,
AVG(response_time) as avg_time
FROM access_log
WHERE status >= 500
GROUP BY request_uri;
** 总结:**一个优秀的Filter就像「数字监控摄像头」,默默记录系统运行轨迹。通过本文的方案,你可以:
1️⃣ 统一管理所有请求响应日志
2️⃣ 零成本实现全链路追踪
3️⃣ 灵活扩展监控维度
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