CPS core sends the data updated event to Kafka synchronously which increases the Data node API response time. To avoid the impact, the cps-core notification feature will process the events asynchronously using spring async.
Spring async method is well documented and more details can be found at https://spring.io/guides/gs/async-method/
In the proposed implementation, we need to
Enable async processing
@EnableAsync
public class AsyncConfig {
...
} |
Define the thread pool which will execute the async method. The thread pool setup properties are configurable.
@ConfigurationProperties("notification.async-executor")
@Validated
public class AsyncConfig {
@Min(0)
private int corePoolSize = 2;
@Min(2)
private int maxPoolSize = 10;
@Min(0)
private int queueCapacity = 2147483647;
private boolean waitForTasksToCompleteOnShutdown = true;
private String threadNamePrefix = "Async-";
@Bean("notificationExecutor")
public TaskExecutor getThreadAsyncExecutorForNotification() {
final ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
executor.setCorePoolSize(corePoolSize);
executor.setMaxPoolSize(maxPoolSize);
executor.setQueueCapacity(queueCapacity);
executor.setWaitForTasksToCompleteOnShutdown(waitForTasksToCompleteOnShutdown);
executor.setThreadNamePrefix(threadNamePrefix);
return executor;
}
} |
notification:
async-executor:
core-pool-size: 2
max-pool-size: 10
queue-capacity: 500
wait-for-tasks-to-complete-on-shutdown: true
thread-name-prefix: Async- |
Mark the method async and mention the thread-pool name
@Async("notificationExecutor")
public Future<Void> processDataUpdatedEvent(final String dataspaceName, final String anchorName) {
...
} |