本文介绍了如何使用@Async注解来完成异步操作,从而加快执行速度
配置
@EnableAsync, asyncExecutor bean
Appliction.java
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@EnableAsync
public class {
@Bean
public MappingJackson2HttpMessageConverter mappingJackson2HttpMessageConverter() {
return BuildflowUtil.getJsonConverter();
}
@Bean
@Autowired
public LibraryApiService libraryApiService(RestTemplateBuilder builder){
return new LibraryApiService(builder);
}
public static void main(String[] args) {
SpringApplication.run(Application.class, args);
}
@Bean
public Executor asyncExecutor() {
ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
executor.setCorePoolSize(4);
executor.setMaxPoolSize(4);
executor.setQueueCapacity(500);
executor.setThreadNamePrefix("Fetch podlist-");
executor.initialize();
return executor;
}
}
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使用
在需要异步执行的函数上添加 @Async注解, 并使得该函数返回 CompletableFuture:
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@Async
public CompletableFuture<List<MsaRecordVo>> getMsaRecord(EnvironmentDto environment, List<ReleaseMsaDto> msaDtos, String refUrl, int envNum) {
......
return CompletableFuture.completedFuture(msaRecordVos);
}
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将所有异步执行的函数添加到一个CompletableFutur的list中:
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List<CompletableFuture<List<MsaRecordVo>>> futures = new LinkedList<>();
......
futures.add(environmentService.getMsaRecord(environment, msaDtos, releaseRepositoryUrl, environmentNumber));
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待所有异步操作结束后, 合并结果
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CompletableFuture<Void> allDoneFuture = CompletableFuture.allOf(futures.toArray(new CompletableFuture[futures.size()]));
List<List<MsaRecordVo>> results = allDoneFuture.thenApply(
v -> futures
.stream()
.map(CompletableFuture::join)
.collect(Collectors.toList())
).get();
msaRecordVos = results.stream().flatMap(x->x.stream()).collect(toList());
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