spring webflux返回application/stream+json

序

本文主要研究下spring webflux返回application/stream+json的实例

maven

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-webflux</artifactId>
        </dependency>

controller

    /**
     * curl -i localhost:8080/stream
     * @return
     */
    @GetMapping(value = "/stream",produces = MediaType.APPLICATION_STREAM_JSON_VALUE)
    public Flux<Price> priceStream(){
        return Flux.interval(Duration.ofMillis(500))
                .map(l -> new Price(System.currentTimeMillis(),ThreadLocalRandom.current().nextInt(100, 125)))
                .log();
    }

注意这里produces = MediaType.APPLICATION_STREAM_JSON_VALUE
如果不是application/stream+json则调用端无法滚动得到结果，将一直阻塞等待数据流结束或超时。

输出

• 后台输出

2018-02-08 21:36:49.701  INFO 1270 --- [ctor-http-nio-2] reactor.Flux.Map.1                       : onSubscribe(FluxMap.MapSubscriber)
2018-02-08 21:36:49.702  INFO 1270 --- [ctor-http-nio-2] reactor.Flux.Map.1                       : request(1)
2018-02-08 21:36:50.208  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097010208, value=120.0))
2018-02-08 21:36:50.229  INFO 1270 --- [ctor-http-nio-2] reactor.Flux.Map.1                       : request(31)
2018-02-08 21:36:50.708  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097010708, value=124.0))
2018-02-08 21:36:51.208  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097011208, value=119.0))
2018-02-08 21:36:51.707  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097011707, value=120.0))
2018-02-08 21:36:52.207  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097012207, value=109.0))
2018-02-08 21:36:52.707  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097012707, value=101.0))
2018-02-08 21:36:53.208  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097013208, value=114.0))
2018-02-08 21:36:53.707  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097013707, value=113.0))
2018-02-08 21:36:54.206  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097014206, value=105.0))
2018-02-08 21:36:54.708  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097014708, value=103.0))
2018-02-08 21:36:55.208  INFO 1270 --- [     parallel-2] reactor.Flux.Map.1                       : onNext(Price(timestamp=1518097015207, value=123.0))
2018-02-08 21:36:55.212  INFO 1270 --- [ctor-http-nio-2] reactor.Flux.Map.1                       : cancel()

• 调用端输出

curl -i localhost:8080/stream
HTTP/1.1 200 OK
transfer-encoding: chunked
Content-Type: application/stream+json;charset=UTF-8

{"timestamp":1518097010208,"value":120.0}
{"timestamp":1518097010708,"value":124.0}
{"timestamp":1518097011208,"value":119.0}
{"timestamp":1518097011707,"value":120.0}
{"timestamp":1518097012207,"value":109.0}
{"timestamp":1518097012707,"value":101.0}
{"timestamp":1518097013208,"value":114.0}
{"timestamp":1518097013707,"value":113.0}
{"timestamp":1518097014206,"value":105.0}
^C

可以看到由于使用了application/stream+json，返回的transfer-encoding是chunked，因此调用端可以做到滚动输出。

分页

使用了webflux之后，可能好奇之前的分页调用怎么办。reactive-streams是把数据当做数据流来用的，因此spring data reactive并不支持返回Page，但是调用参数可以传Pageable参数

public interface StocDao extends ReactiveCrudRepository<Stock, String> {

    Flux<Stock> findByName(String name,Pageable pageable);
}

注意这里返回Flux<Stock>，而不是Page<Stock>
也就是相当于丢失了total count

小结

对于webflux返回的Flux的流数据，需要配合返回MediaType.APPLICATION_STREAM_JSON_VALUE，同时调用端也需要能够支持这种mediaType(WebClient支持)，这样才能启到reactive streams的效果。

doc

• Serving large datasets with Spring WebFlux
• mongo.reactive.repositories.usage
• Is there any way to implement pagination in spring webflux and spring data reactive