您的位置:首页 > 编程语言 > Java开发

spring-cloud-gateway过滤器实践

2020-04-01 22:32 357 查看

概述

这里是

SpringCloud Gateway
实践的第一篇,主要讲过滤器的相关实现。Spring-Cloud-Gateway 是以
WebFlux
为基础的响应式架构设计, 是异步非阻塞式的,它能够充分利用多核 CPU 的硬件资源去处理大量的并发请求。

本篇将基于 spring-cloud-gateway 简介 基础环境进行改造。

工作原理

Spring-Cloud-Gateway 基于过滤器实现,同 zuul 类似,有prepost两种方式的 filter,分别处理前置逻辑后置逻辑。客户端的请求先经过pre类型的 filter,然后将请求转发到具体的业务服务,收到业务服务的响应之后,再经过post类型的 filter 处理,最后返回响应到客户端。

过滤器执行流程如下,order 越大,优先级越低

接下来我们来验证下

filter
执行顺序。

这里创建 3 个过滤器,分别配置不同的优先级

@Slf4j
public class AFilter implements GlobalFilter {
@Override
public Mono<Void> filter(ServerWebExchange exchange, GatewayFilterChain chain) {
log.info("AFilter前置逻辑");
return chain.filter(exchange).then(Mono.fromRunnable(() -> {
log.info("AFilter后置逻辑");
}));
}
}

@Slf4j
public class BFilter implements GlobalFilter {
@Override
public Mono<Void> filter(ServerWebExchange exchange, GatewayFilterChain chain) {
log.info("BFilter前置逻辑");
return chain.filter(exchange).then(Mono.fromRunnable(() -> {
log.info("BFilter后置逻辑");
}));
}
}

@Slf4j
public class CFilter implements GlobalFilter {

@Override
public Mono<Void> filter(ServerWebExchange exchange, GatewayFilterChain chain) {
log.info("CFilter前置逻辑");
return chain.filter(exchange).then(Mono.fromRunnable(() -> {
log.info("CFilter后置逻辑");
}));
}
}

@Configuration
public class FilterConfig {

@Bean
@Order(-1)
public GlobalFilter a() {
return new AFilter();
}

@Bean
@Order(0)
public GlobalFilter b() {
return new BFilter();
}

@Bean
@Order(1)
public GlobalFilter c() {
return new CFilter();
}
}
curl -X POST -H "Content-Type:application/json" -d '{"name": "admin"}' http://192.168.124.5:2000/p/provider1

curl -X GET -G -d "username=admin" http://192.168.124.5:2000/p/provider1/1

查看网关输出日志

2020-03-29 16:23:22.832  INFO 59326 --- [ctor-http-nio-6] cn.idea360.gateway.filter1.AFilter       : AFilter前置逻辑
2020-03-29 16:23:22.832  INFO 59326 --- [ctor-http-nio-6] cn.idea360.gateway.filter1.BFilter       : BFilter前置逻辑
2020-03-29 16:23:22.832  INFO 59326 --- [ctor-http-nio-6] cn.idea360.gateway.filter1.CFilter       : CFilter前置逻辑

2020-03-29 16:23:22.836  INFO 59326 --- [ctor-http-nio-6] cn.idea360.gateway.filter1.CFilter       : CFilter后置逻辑
2020-03-29 16:23:22.836  INFO 59326 --- [ctor-http-nio-6] cn.idea360.gateway.filter1.BFilter       : BFilter后置逻辑
2020-03-29 16:23:22.836  INFO 59326 --- [ctor-http-nio-6] cn.idea360.gateway.filter1.AFilter       : AFilter后置逻辑

自定义过滤器

现在假设我们要统计某个服务的响应时间,我们可以在代码中

long beginTime = System.currentTimeMillis();
// do something...
long elapsed = System.currentTimeMillis() - beginTime;
log.info("elapsed: {}ms", elapsed);

每次都要这么写是不是很烦?Spring 告诉我们有个东西叫 AOP。但是我们是微服务啊,在每个服务里都写也很烦。这时候就该网关的过滤器登台表演了。

自定义过滤器需要实现

GatewayFilter
Ordered
。其中
GatewayFilter
中的这个方法就是用来实现你的自定义的逻辑的

Mono<Void> filter(ServerWebExchange exchange, GatewayFilterChain chain);

Ordered
中的
int getOrder()
方法是来给过滤器设定优先级别的,值越大则优先级越低。

好了,让我们来撸代码吧.

/**
* 此过滤器功能为计算请求完成时间
*/
public class ElapsedFilter implements GatewayFilter, Ordered {

private static final String ELAPSED_TIME_BEGIN = "elapsedTimeBegin";

@Override
public Mono<Void> filter(ServerWebExchange exchange, GatewayFilterChain chain) {
exchange.getAttributes().put(ELAPSED_TIME_BEGIN, System.currentTimeMillis());
return chain.filter(exchange).then(
Mono.fromRunnable(() -> {
Long startTime = exchange.getAttribute(ELAPSED_TIME_BEGIN);
if (startTime != null) {
System.out.println(exchange.getRequest().getURI().getRawPath() + ": " + (System.currentTimeMillis() - startTime) + "ms");
}
})
);
}

/*
*过滤器存在优先级,order越大,优先级越低
*/
@Override
public int getOrder() {
return Ordered.LOWEST_PRECEDENCE;
}
}

我们在请求刚刚到达时,往

ServerWebExchange
中放入了一个属性
elapsedTimeBegin
,属性值为当时的毫秒级时间戳。然后在请求执行结束后,又从中取出我们之前放进去的那个时间戳,与当前时间的差值即为该请求的耗时。因为这是与业务无关的日志所以将
Ordered
设为
Integer.MAX_VALUE
以降低优先级。

现在再来看我们之前的问题:怎么来区分是 “pre” 还是 “post” 呢?其实就是

chain.filter(exchange)
之前的就是 “pre” 部分,之后的也就是
then
里边的是 “post” 部分。

创建好 Filter 之后我们将它添加到我们的 Filter Chain 里边

@Configuration
public class FilterConfig {

/**
* http://localhost:8100/filter/provider
* @param builder
* @return
*/
@Bean
public RouteLocator customerRouteLocator(RouteLocatorBuilder builder) {
// @formatter:off
// 可以对比application.yml中关于路由转发的配置
return builder.routes()
.route(r -> r.path("/filter/**")
.filters(f -> f.stripPrefix(1)
.filter(new ElapsedFilter()))
.uri("lb://idc-cloud-provider")
.order(0)
.id("filter")
)
.build();
// @formatter:on
}

}

基于全局过滤器实现审计功能

// AdaptCachedBodyGlobalFilter

@Component
public class LogFilter implements GlobalFilter, Ordered {

private Logger log = LoggerFactory.getLogger(LogFilter.class);

private final ObjectMapper objectMapper = new ObjectMapper();
private static final String START_TIME = "startTime";
private static final List<HttpMessageReader<?>> messageReaders = HandlerStrategies.withDefaults().messageReaders();

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

ServerHttpRequest request = exchange.getRequest();
// 请求路径
String path = request.getPath().pathWithinApplication().value();
// 请求schema: http/https
String scheme = request.getURI().getScheme();
// 请求方法
HttpMethod method = request.getMethod();
// 路由服务地址
URI targetUri = exchange.getAttribute(ServerWebExchangeUtils.GATEWAY_REQUEST_URL_ATTR);
// 请求头
HttpHeaders headers = request.getHeaders();
// 设置startTime
exchange.getAttributes().put(START_TIME, System.currentTimeMillis());
// 获取请求地址
InetSocketAddress remoteAddress = request.getRemoteAddress();

MultiValueMap<String, String> formData = null;

AccessRecord accessRecord = new AccessRecord();
accessRecord.setPath(path);
accessRecord.setSchema(scheme);
accessRecord.setMethod(method.name());
accessRecord.setTargetUri(targetUri.toString());
accessRecord.setRemoteAddress(remoteAddress.toString());
accessRecord.setHeaders(headers);

if (method == HttpMethod.GET) {
formData = request.getQueryParams();
accessRecord.setFormData(formData);
writeAccessRecord(accessRecord);
}

if (method == HttpMethod.POST) {
Mono<Void> voidMono = null;
if (headers.getContentType().equals(MediaType.APPLICATION_JSON)) {
// JSON
voidMono = readBody(exchange, chain, accessRecord);
}

if (headers.getContentType().equals(MediaType.APPLICATION_FORM_URLENCODED)) {
// x-www-form-urlencoded
voidMono = readFormData(exchange, chain, accessRecord);
}

if (voidMono != null) {
return voidMono;
}

}

return chain.filter(exchange);
}

private Mono<Void> readFormData(ServerWebExchange exchange, GatewayFilterChain chain, AccessRecord accessRecord) {
return null;
}

private Mono<Void> readBody(ServerWebExchange exchange, GatewayFilterChain chain, AccessRecord accessRecord) {

return DataBufferUtils.join(exchange.getRequest().getBody()).flatMap(dataBuffer -> {

byte[] bytes = new byte[dataBuffer.readableByteCount()];
dataBuffer.read(bytes);
DataBufferUtils.release(dataBuffer);
Flux<DataBuffer> cachedFlux = Flux.defer(() -> {
DataBuffer buffer = exchange.getResponse().bufferFactory().wrap(bytes);
DataBufferUtils.retain(buffer);
return Mono.just(buffer);
});

// 重写请求体,因为请求体数据只能被消费一次
ServerHttpRequest mutatedRequest = new ServerHttpRequestDecorator(exchange.getRequest()) {
@Override
public Flux<DataBuffer> getBody() {
return cachedFlux;
}
};

ServerWebExchange mutatedExchange = exchange.mutate().request(mutatedRequest).build();

return ServerRequest.create(mutatedExchange, messageReaders)
.bodyToMono(String.class)
.doOnNext(objectValue -> {
accessRecord.setBody(objectValue);
writeAccessRecord(accessRecord);
}).then(chain.filter(mutatedExchange));
});
}

@Override
public int getOrder() {
return Ordered.LOWEST_PRECEDENCE;
}

/**
* TODO 异步日志
* @param accessRecord
*/
private void writeAccessRecord(AccessRecord accessRecord) {

log.info("\n\n start------------------------------------------------- \n " +
"请求路径:{}\n " +
"scheme:{}\n " +
"请求方法:{}\n " +
"目标服务:{}\n " +
"请求头:{}\n " +
"远程IP地址:{}\n " +
"表单参数:{}\n " +
"请求体:{}\n " +
"end------------------------------------------------- \n ",
accessRecord.getPath(), accessRecord.getSchema(), accessRecord.getMethod(), accessRecord.getTargetUri(), accessRecord.getHeaders(), accessRecord.getRemoteAddress(), accessRecord.getFormData(), accessRecord.getBody());
}
}
curl -X POST -H "Content-Type:application/json" -d '{"name": "admin"}' http://192.168.124.5:2000/p/provider1

curl -X GET -G -d "username=admin" http://192.168.124.5:2000/p/provider1/1

输出结果

start-------------------------------------------------
请求路径:/provider1
scheme:http
请求方法:POST
目标服务:http://192.168.124.5:2001/provider1
请求头:[Content-Type:"application/json", User-Agent:"PostmanRuntime/7.22.0", Accept:"*/*", Cache-Control:"no-cache", Postman-Token:"2a4ce04d-8449-411d-abd8-247d20421dc2", Host:"192.168.124.5:2000", Accept-Encoding:"gzip, deflate, br", Content-Length:"16", Connection:"keep-alive"]
远程IP地址:/192.168.124.5:49969
表单参数:null
请求体:{"name":"admin"}
end-------------------------------------------------

接下来,我们来配置日志,方便日志系统提取日志。SpringBoot 默认的日志为 logback。

<?xml version="1.0" encoding="UTF-8"?>
<configuration>

<property name="LOGS" value="/Users/cuishiying/Documents/spring-cloud-learning/logs" />

<appender name="Console" class="ch.qos.logback.core.ConsoleAppender">
<layout class="ch.qos.logback.classic.PatternLayout">
<Pattern>
%black(%d{ISO8601}) %highlight(%-5level) [%blue(%t)] %yellow(%C{1.}): %msg%n%throwable
</Pattern>
</layout>
</appender>

<appender name="RollingFile" class="ch.qos.logback.core.rolling.RollingFileAppender">
<file>${LOGS}/spring-boot-logger.log</file>
<encoder
class="ch.qos.logback.classic.encoder.PatternLayoutEncoder">
<Pattern>%d %p %C{1.} [%t] %m%n</Pattern>
</encoder>

<rollingPolicy
class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">
<!-- rollover daily and when the file reaches 10 MegaBytes -->
<fileNamePattern>${LOGS}/archived/spring-boot-logger-%d{yyyy-MM-dd}.%i.log
</fileNamePattern>
<timeBasedFileNamingAndTriggeringPolicy
class="ch.qos.logback.core.rolling.SizeAndTimeBasedFNATP">
<maxFileSize>10MB</maxFileSize>
</timeBasedFileNamingAndTriggeringPolicy>
</rollingPolicy>
</appender>

<!-- LOG everything at INFO level -->
<root level="info">
<!--<appender-ref ref="RollingFile" />-->
<appender-ref ref="Console" />
</root>

<!-- LOG "cn.idea360*" at TRACE level additivity:是否向上级loger传递打印信息。默认是true-->
<logger name="cn.idea360.gateway" level="info" additivity="false">
<appender-ref ref="RollingFile" />
<appender-ref ref="Console" />
</logger>

</configuration>

这样 console 和日志目录下就都有日志了。

自定义过滤器工厂

如果你看过静态路由的配置,你应该对如下配置有印象。

filters:
- StripPrefix=1
- AddResponseHeader=X-Response-Default-Foo, Default-Bar

StripPrefix
AddResponseHeader
这两个实际上是两个过滤器工厂(GatewayFilterFactory),用这种配置的方式更灵活方便。

我们就将之前的那个

ElapsedFilter
改造一下,让它能接收一个
boolean
类型的参数,来决定是否将请求参数也打印出来。

public class ElapsedGatewayFilterFactory extends AbstractGatewayFilterFactory<ElapsedGatewayFilterFactory.Config> {

private static final Log log = LogFactory.getLog(GatewayFilter.class);
private static final String ELAPSED_TIME_BEGIN = "elapsedTimeBegin";
private static final String KEY = "withParams";

public List<String> shortcutFieldOrder() {
return Arrays.asList(KEY);
}

public ElapsedGatewayFilterFactory() {
super(Config.class);
}
public GatewayFilter apply(Config config) {
return (exchange, chain) -> {
exchange.getAttributes().put(ELAPSED_TIME_BEGIN, System.currentTimeMillis());
return chain.filter(exchange).then(
Mono.fromRunnable(() -> {
Long startTime = exchange.getAttribute(ELAPSED_TIME_BEGIN);
if (startTime != null) {
StringBuilder sb = new StringBuilder(exchange.getRequest().getURI().getRawPath())
.append(": ")
.append(System.currentTimeMillis() - startTime)
.append("ms");
if (config.isWithParams()) {
sb.append(" params:").append(exchange.getRequest().getQueryParams());
}
log.info(sb.toString());
}
})
);
};
}

public static class Config {

private boolean withParams;

public boolean isWithParams() {
return withParams;
}

public void setWithParams(boolean withParams) {
this.withParams = withParams;
}

}
}

过滤器工厂的顶级接口是

GatewayFilterFactory
,我们可以直接继承它的两个抽象类来简化开发
AbstractGatewayFilterFactory
AbstractNameValueGatewayFilterFactory
,这两个抽象类的区别就是前者接收一个参数(像
StripPrefix
和我们创建的这种),后者接收两个参数(像
AddResponseHeader
)。

GatewayFilter apply(Config config)
方法内部实际上是创建了一个
GatewayFilter
的匿名类,具体实现和之前的几乎一样,就不解释了。

静态内部类

Config
就是为了接收那个
boolean
类型的参数服务的,里边的变量名可以随意写,但是要重写
List shortcutFieldOrder()
这个方法。

这里注意一下,一定要调用一下父类的构造器把

Config
类型传过去,否则会报
ClassCastException

public ElapsedGatewayFilterFactory() {
super(Config.class);
}

工厂类我们有了,再把它注册到 Spring 当中

@Bean
public ElapsedGatewayFilterFactory elapsedGatewayFilterFactory() {
return new ElapsedGatewayFilterFactory();
}

然后添加配置(主要改动在

default-filters
配置)

server:
port: 2000
spring:
application:
name: idc-gateway
redis:
host: localhost
port: 6379
timeout: 6000ms  # 连接超时时长(毫秒)
jedis:
pool:
max-active: 1000  # 连接池最大连接数(使用负值表示没有限制)
max-wait: -1ms      # 连接池最大阻塞等待时间(使用负值表示没有限制)
max-idle: 10      # 连接池中的最大空闲连接
min-idle: 5       # 连接池中的最小空闲连接
cloud:
consul:
host: localhost
port: 8500
gateway:
discovery:
locator:
enabled: true
# 修改在这里。gateway可以通过开启以下配置来打开根据服务的serviceId来匹配路由,默认是大写
default-filters:
- Elapsed=true
routes:
- id: provider  # 路由 ID,保持唯一
uri: lb://idc-provider1 # uri指目标服务地址,lb代表从注册中心获取服务
predicates: # 路由条件。Predicate 接受一个输入参数,返回一个布尔值结果。该接口包含多种默认方法来将 Predicate 组合成其他复杂的逻辑(比如:与,或,非)
- Path=/p/**
filters:
- StripPrefix=1 # 过滤器StripPrefix,作用是去掉请求路径的最前面n个部分截取掉。StripPrefix=1就代表截取路径的个数为1,比如前端过来请求/test/good/1/view,匹配成功后,路由到后端的请求路径就会变成http://localhost:8888/good/1/view

结语

本文到此结束。关于

Webflux
的学习刚入门,觉得可以像
Rxjava
那样在
onNext
中拿到异步数据,然而在
post
获取 body 中没生效。经测试可知
getBody
获得的数据输出为 null,而自己通过
Flux.create
创建的数据可以在订阅者中获取到。此处还有待研究,希望抛砖引玉,大家有研究出来的不吝赐教。同时,希望大家关注公众号【当我遇上你】。

参考

内容来自用户分享和网络整理,不保证内容的准确性,如有侵权内容,可联系管理员处理 点击这里给我发消息
标签: