When I run my app using akka 2.1.2, it fails with the following exception:
Event Handler specified in config can't be loaded [com.despegar.hasp.impl.DummyLogEventHandler] due to [a06c8d75-0f07-40db-883a-16dc2914934bakka.event.Logging$LoggerInitializationException: Logger log1-DummyLogEventHandler did not respond with LoggerInitialized, sent instead [TIMEOUT]
DummyLogEventHandler is defined as:
class DummyLogEventHandler extends Actor { def receive = { case InitializeLogger(_) => sender ! LoggerInitialized case Error(cause, logSource, logClass, message) => case Warning(logSource, logClass, message) => case Info(logSource, logClass, message) => case Debug(logSource, logClass, message) => }
}
My configuration has the following lines:
event-handlers = ["my.app.DummyLogEventHandler"] event-handler-startup-timeout = 15s
But I've also tried with the default logger:
event-handlers = []
and with slf4j (my app is using the logback backend and logging works ok):
event-handlers = ["akka.event.slf4j.Slf4jEventHandler"]
Neither of those event-handlers nor incrementing the timeout to 60 seconds have worked so far. Moreover, the timeout is thrown sporadically. When I ran a test suite, the exception is thrown in different tests every time.
Can you help me find a solution?
Thanks,
Alex.
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All the actors share a single Mailbox that they get their messages from.
It is assumed that all actors using the same instance of this dispatcher can process all messages that have been sent to one of the actors; i.e. the actors belong to a pool of actors, and to the client there is no guarantee about which actor instance actually processes a given message.
Sharability: Actors of the same type only
Hi Roland,If I comment out the dispatcher section in my configuration, the timeout exception is not thrown any more.What's odd is that I only changed the dispatcher type to BalacingDispatcher and the default parallelism factor from 3 to 4:
- default-dispatcher {
- type = "BalancingDispatcher"
- executor = "fork-join-executor"
- fork-join-executor {
- parallelism-min = 8
- parallelism-factor = 3.0
- parallelism-max = 64
- }
- }
Thanks,Alex.