See https://github.com/SpinGo/op-rabbit for the main documentation.
This fork switches from Akka to Apache Pekko (releases v3 and above)
Releases for v2 were for Akka. Akka will no longer be supported by this project.
Op-Rabbit is available on Maven Central.
val opRabbitVersion = "3.0.0"
libraryDependencies ++= Seq(
"com.github.pjfanning" %% "op-rabbit-core" % opRabbitVersion,
"com.github.pjfanning" %% "op-rabbit-play-json" % opRabbitVersion,
"com.github.pjfanning" %% "op-rabbit-json4s" % opRabbitVersion,
"com.github.pjfanning" %% "op-rabbit-airbrake" % opRabbitVersion,
"com.github.pjfanning" %% "op-rabbit-pekko-stream" % opRabbitVersion
)
op-rabbit-core
- Implements basic patterns for serialization and message processing.
op-rabbit-play-json
- Easily use Play Json formats to publish or consume messages; automatically sets RabbitMQ message headers to indicate content type.
op-rabbit-json4s
- Easily use Json4s to serialization messages; automatically sets RabbitMQ message headers to indicate content type.
op-rabbit-airbrake
- Report consumer exceptions to airbrake, using the Airbrake Java library.
op-rabbit-pekko-stream
- Process or publish messages using pekko-stream.
Set up RabbitMQ connection information in application.conf
:
op-rabbit {
topic-exchange-name = "amq.topic"
channel-dispatcher = "op-rabbit.default-channel-dispatcher"
default-channel-dispatcher {
# Dispatcher is the name of the event-based dispatcher
type = Dispatcher
# What kind of ExecutionService to use
executor = "fork-join-executor"
# Configuration for the fork join pool
fork-join-executor {
# Min number of threads to cap factor-based parallelism number to
parallelism-min = 2
# Parallelism (threads) ... ceil(available processors * factor)
parallelism-factor = 2.0
# Max number of threads to cap factor-based parallelism number to
parallelism-max = 4
}
# Throughput defines the maximum number of messages to be
# processed per actor before the thread jumps to the next actor.
# Set to 1 for as fair as possible.
throughput = 100
}
connection {
virtual-host = "/"
hosts = ["127.0.0.1"]
username = "guest"
password = "guest"
port = 5672
ssl = false
connection-timeout = 3s
}
}
Note that hosts is an array; Connection attempts will be made to hosts
in that order, with a default timeout of 3s
. This way you can
specify addresses of your rabbitMQ cluster, and if one of the
instances goes down, your application will automatically reconnect to
another member of the cluster.
topic-exchange-name
is the default topic exchange to use; this can
be overriden by passing exchange = "my-topic"
to
TopicBinding
or
Message.topic.
Boot up the RabbitMQ control actor:
import com.github.pjfanning.op_rabbit.RabbitControl
import org.apache.pekko.actor.{ActorSystem, Props}
implicit val actorSystem = ActorSystem("such-system")
val rabbitControl = actorSystem.actorOf(Props[RabbitControl])
(this example uses op-rabbit-play-json
)
import com.github.pjfanning.op_rabbit.PlayJsonSupport._
import com.github.pjfanning.op_rabbit._
import play.api.libs.json._
import scala.concurrent.ExecutionContext.Implicits.global
case class Person(name: String, age: Int)
// setup play-json serializer
implicit val personFormat = Json.format[Person]
implicit val recoveryStrategy = RecoveryStrategy.none
val subscriptionRef = Subscription.run(rabbitControl) {
import Directives._
// A qos of 3 will cause up to 3 concurrent messages to be processed at any given time.
channel(qos = 3) {
consume(topic(queue("such-message-queue"), List("some-topic.#"))) {
(body(as[Person]) & routingKey) { (person, key) =>
/* do work; this body is executed in a separate thread, as
provided by the implicit execution context */
println(s"""A person named '${person.name}' with age
${person.age} was received over '${key}'.""")
ack
}
}
}
}
Now, test the consumer by sending a message:
subscriptionRef.initialized.foreach { _ =>
rabbitControl ! Message.topic(
Person("Your name here", 33), "some-topic.cool")
}
Stop the consumer:
subscriptionRef.close()
Note, if your call generates an additional future, you can pass it to ack, and message will be acked based off the Future success, and nacked with Failure (such that the configured RecoveryStrategy if the Future fails):
// ...
(body(as[Person]) & routingKey) { (person, key) =>
/* do work; this body is executed in a separate thread, as
provided by the implicit execution context */
val result: Future[Unit] = myApi.methodCall(person)
ack(result)
}
// ...
If the queue already exists and doesn't match the expected configuration, topic subscription will fail. To bind to an externally configured queue use Queue.passive
:
channel(qos = 3) {
consume(Queue.passive("very-exist-queue")) { ...
It is also possible to optionally create the queue if it doesn't exist, by providing a QueueDefinition
instead of a String
:
channel(qos = 3) {
consume(Queue.passive(topic(queue("wow-maybe-queue"), List("some-topic.#")))) { ...
As seen in the example above, you can extract headers in addition to the message body, using op-rabbit's Directives. You can use multiple declaratives via multiple nested functions, as follows:
import com.github.pjfanning.op_rabbit.properties._
// Nested directives
// ...
body(as[Person]) { person =>
optionalProperty(ReplyTo) { replyTo =>
// do work
ack
}
}
// ...
Or, you can combine directives using &
to form a compound directive, as follows:
// Compound directive
// ...
(body(as[Person]) & optionalProperty(ReplyTo)) { (person, replyTo) =>
// do work
ack
}
// ...
See the documentation on Directives for more details.
The following methods are available on a SubscriptionRef which will allow control over the subscription.
/* stop receiving new messages from RabbitMQ immediately; shut down
consumer and channel as soon as pending messages are completed. A
grace period of 30 seconds is given, after which the subscription
forcefully shuts down. (Default of 5 minutes used if duration not
provided) */
subscription.close(30 seconds)
/* Shut down the subscription immediately; don't wait for messages to
finish processing. */
subscription.abort()
/* Future[Unit] which completes once the provided binding has been
applied (IE: queue has been created and topic bindings
configured). Useful if you need to assert you don't send a message
before a message queue is created in which to place it. */
subscription.initialized
// Future[Unit] which completes when the subscription is closed.
subscription.closed
A recovery strategy defines how a subscription should handle exceptions and must be provided. Should it redeliver them a limited number of times? Or, should it drop them? Several pre-defined recovery strategies with their corresponding documentation are defined in the RecoveryStrategy companion object.
implicit val recoveryStrategy = RecoveryStrategy.nack()
rabbitControl ! Message.topic(
Person(name = "Mike How", age = 33),
routingKey = "some-topic.very-interest")
rabbitControl ! Message.queue(
Person(name = "Ivanah Tinkle", age = 25),
queue = "such-message-queue")
By default:
-
Messages will be queued up until a connection is available
-
Messages are monitored via publisherConfirms; if a connection is lost before RabbitMQ confirms receipt of the message, then the message is published again. This means that the message may be delivered twice, the default opinion being that
at-least-once
is better thanat-most-once
. You can use UnconfirmedMessage if you'd likeat-most-once
delivery, instead. -
If you would like to be notified of confirmation, use the ask pattern:
import org.apache.pekko.pattern.ask import org.apache.pekko.util.Timeout import scala.concurrent.duration._ implicit val timeout = Timeout(5 seconds) val received = ( rabbitControl ? Message.queue( Person(name = "Ivanah Tinkle", age = 25), queue = "such-message-queue") ).mapTo[ConfirmResponse]
(this example uses op-rabbit-play-json
and op-rabbit-pekko-streams
)
import Directives._
implicit val recoveryStrategy = RecoveryStrategy.drop()
RabbitSource(
rabbitControl,
channel(qos = 3),
consume(queue(
"such-queue",
durable = true,
exclusive = false,
autoDelete = false)),
body(as[Person])). // marshalling is automatically hooked up using implicits
runForeach { person =>
greet(person)
} // after each successful iteration the message is acknowledged.
Note: RabbitSource
yields an
AckedSource,
which can be combined with an
AckedFlow
and an
AckedSink
(such as
MessagePublisherSink
). You
can convert an acked stream into a normal stream by calling
AckedStream.acked
; once messages flow passed the acked
component,
they are considered acknowledged, and acknowledgement tracking is no
longer a concern (and thus, you are free to use the pekko-stream
library in its entirety).
When using the DSL as described in the consumer setup
section, recovery strategies are triggered if fail
is called or if a failed future is passed to ack
. For streams, we have to do
something a little different.
To trigger the specified recovery strategy when using op-rabbit-pekko-stream
and its acked
components, an exception should be thrown within the acked
part of the graph. However, the default exception-handling behavior in
pekko-stream
is stopping the graph, which in op-rabbit
's case would mean
stopping the consumer and preventing further messages from being processed.
To explicitly allow the graph to continue running, a ResumingDecider supervision
strategy should be declared. (To learn more about supervision strategies please
refer to the Pekko Streams docs).
implicit val system = ActorSystem()
private val rabbitControl = system.actorOf(Props[RabbitControl], name = "op-rabbit")
// We define an ActorMaterializer with a resumingDecider supervision strategy,
// which prevents the graph from stopping when an exception is thrown.
implicit val materializer = ActorMaterializer(
ActorMaterializerSettings(system)
.withSupervisionStrategy(Supervision.resumingDecider: Decider)
)
// As a recovery strategy, let's suppose we want all nacked messages to go to
// an existing queue called "failed-events"
implicit private val recoveryStrategy = RecoveryStrategy.abandonedQueue(
7.days,
abandonQueueName = (_: String) => "failed-events"
)
private val src = RabbitSource(
rabbitControl,
channel(qos = 3),
consume(Queue("events")),
body(as[String])
)
// This may throw an exception, in which case the defined recovery strategy
// will be triggered and our flow will continue thanks to the resumingDecider.
private val flow = AckedFlow[String].map(_.toInt)
private val sink = AckedSink.foreach[Int](println)
src.via(flow).to(sink).run
It's important to know when your consumers fail. Out of the box,
op-rabbit
ships with support for logging to slf4j
(and therefore
syslog), and also airbrake
via op-rabbit-airbrake
. Without any
additional signal provided by you, slf4j will be used, making error
visibility a default.
You can report errors to multiple sources by combining error logging
strategies; for example, if you'd like to report to both slf4j
and
to airbrake
, import / set the following implicit RabbitErrorLogging
in the scope where your consumer is instantiated:
import com.github.pjfanning.op_rabbit.{Slf4jLogger, AirbrakeLogger}
implicit val rabbitErrorLogging = Slf4jLogger + AirbrakeLogger.fromConfig
Implementing your own error reporting strategy is simple; here's the source code for the slf4jLogger:
object Slf4jLogger extends RabbitErrorLogging {
def apply(
name: String,
message: String,
exception: Throwable,
consumerTag: String,
envelope: Envelope,
properties: BasicProperties,
body: Array[Byte]): Unit = {
val logger = LoggerFactory.getLogger(name)
logger.error(s"${message}. Body=${bodyAsString(body, properties)}. Envelope=${envelope}", exception)
}
}
Op-Rabbit was created by Tim Harper
This library builds upon the Pekko RabbitMQ client.