spring cloud gateway 二次开发之 处理 reponse报文(解决截断及乱码问题)

因为网关是请求的出入口，防止各调用方及服务方相互之间扯皮，响应报文也需要打出来，而这里有一个问题，如果响应过大的话，Flux会进行截断，这样有2个问题，一个是每次处理都会打一次部分报文，不过这个可以通过doOnComplete()来解决，第二就是达到一定长度出现乱码，后来查看api，有一个合并的方法，问题解决，代码如下

/**
 *  处理响应的 的filter
 * @author huangting
 */
@Component
public class ResponseHandlerFilter implements GlobalFilter, Ordered {
    private static final Logger logger = LoggerFactory.getLogger(ResponseHandlerFilter.class);
    private static final String START_TIME = "startTime";

    @Autowired
    private MetricService metricService;

    @Override
    public Mono filter(ServerWebExchange exchange, GatewayFilterChain chain) {

        ServerHttpRequest request = exchange.getRequest();
        String ip = IpUtil.getRemoteHost(request);

        //执行完成后 进行调用耗时埋点
        exchange.getAttributes().put(START_TIME, System.currentTimeMillis());

        //原始响应类
        ServerHttpResponse originalResponse = exchange.getResponse();
        DataBufferFactory bufferFactory = originalResponse.bufferFactory();
        //重新包装的响应类
        ServerHttpResponseDecorator decoratedResponse = new ServerHttpResponseDecorator(originalResponse) {
            @Override
            public Mono writeWith(Publisher body) {
                Flux fluxBody = Flux.from(body);
                return super.writeWith(fluxBody.buffer().map(dataBuffer -> {
                    //如果响应过大，会进行截断，出现乱码，然后看api DefaultDataBufferFactory有个join方法可以合并所有的流，乱码的问题解决
                    DataBufferFactory dataBufferFactory = new DefaultDataBufferFactory();
                    DataBuffer join = dataBufferFactory.join(dataBuffer);
                    byte[] content = new byte[join.readableByteCount()];
                    join.read(content);
                    //释放掉内存
                    DataBufferUtils.release(join);

                    //打印响应日志
                    logResponse(exchange, new String(content, StandardCharsets.UTF_8));

                    return bufferFactory.wrap(content);
                }));
            }
        };

        return chain.filter(exchange.mutate().response(decoratedResponse).build())
                .then(Mono.fromRunnable(() -> {
                    Long startTime = exchange.getAttribute(START_TIME);
                    if (startTime != null) {
                        Long executeTime = (System.currentTimeMillis() - startTime);
                        //influxDB埋点
                        metricService.pointRequestLatency(ip, request.getURI().getPath(), executeTime);
                    }
                }));
    }


    /**
     * 打印响应报文
     *
     * @param exchange
     */
    public void logResponse(ServerWebExchange exchange, String response) {
        ServerHttpRequest request = exchange.getRequest();
        logger.info("响应报文 URL:{},Method:{},headers:{},response:{}", request.getURI().getPath(), request.getMethod(), exchange.getResponse().getHeaders(), response);
    }


    @Override
    public int getOrder() {
        // -1 is response write filter, must be called before that
        return -3;
    }
}

最近发现一个问题，当接口的调用返回值为空的时候，并不会进入 writeWith 里边的map方法，所以当Flux 进行订阅时，map里的 logResponse 没有执行，所以先定义一个默认的 AtomicReference responseBody 变量，当返回值不为空时，对它进行更新；然后把 logResponse 方法下移，放到 return语句中，这样就能保证打印方法总会被执行，修改后的 filter 方法代码如下

 public Mono filter(ServerWebExchange exchange, GatewayFilterChain chain) {

        ServerHttpRequest request = exchange.getRequest();
        String ip = IpUtil.getRemoteHost(request);

        //执行完成后 进行调用耗时埋点
        exchange.getAttributes().put(START_TIME, System.currentTimeMillis());

        //原始响应类
        ServerHttpResponse originalResponse = exchange.getResponse();
        DataBufferFactory bufferFactory = originalResponse.bufferFactory();

        //初始化一个 默认的 responseBody
        AtomicReference responseBody= new AtomicReference<>("no-responseBody");

        //重新包装的响应类
        ServerHttpResponseDecorator decoratedResponse = new ServerHttpResponseDecorator(originalResponse) {
            @Override
            public Mono writeWith(Publisher body) {
                Flux fluxBody = Flux.from(body);
                return super.writeWith(fluxBody.buffer().map(dataBuffer -> {
                    //如果响应过大，会进行截断，出现乱码，然后看api DefaultDataBufferFactory有个join方法可以合并所有的流，乱码的问题解决
                    DataBufferFactory dataBufferFactory = new DefaultDataBufferFactory();
                    DataBuffer join = dataBufferFactory.join(dataBuffer);
                    byte[] content = new byte[join.readableByteCount()];
                    join.read(content);
                    //释放掉内存
                    DataBufferUtils.release(join);

                    //如果有返回值，将 responseBody 覆盖
                    responseBody.set(new String(content, StandardCharsets.UTF_8));

                    return bufferFactory.wrap(content);
                }));
            }
        };

        return chain.filter(exchange.mutate().response(decoratedResponse).build())
                .then(Mono.fromRunnable(() -> {
                    //打印响应日志
                    logResponse(exchange, responseBody.get());

                    Long startTime = exchange.getAttribute(START_TIME);
                    if (startTime != null) {
                        Long executeTime = (System.currentTimeMillis() - startTime);
                        //influxDB埋点
                        metricService.pointRequestLatency(ip, request.getURI().getPath(), executeTime);
                    }
                }));
    }