RabbitMQ tutorial - Remote procedure call (RPC)
Remote procedure call (RPC)
(using Spring AMQP)
Prerequisites
This tutorial assumes RabbitMQ is installed and running on
localhost
on the standard port (5672). In case you
use a different host, port or credentials, connections settings would require
adjusting.
Where to get help
If you're having trouble going through this tutorial you can contact us through GitHub Discussions or RabbitMQ community Discord.
In the second tutorial we learned how to use Work Queues to distribute time-consuming tasks among multiple workers.
But what if we need to run a function on a remote computer and wait for the result? Well, that's a different story. This pattern is commonly known as Remote Procedure Call or RPC.
In this tutorial we're going to use RabbitMQ to build an RPC system: a client and a scalable RPC server. As we don't have any time-consuming tasks that are worth distributing, we're going to create a dummy RPC service that returns Fibonacci numbers.
Client interface
To illustrate how an RPC service could be used we're going to change the names of our profiles from "Sender" and "Receiver" to "Client" and "Server". When we call the server we will get back the fibonacci of the argument we call with.
Integer response = (Integer) template.convertSendAndReceive
(exchange.getName(), "rpc", start++);
System.out.println(" [.] Got '" + response + "'");
A note on RPC
Although RPC is a pretty common pattern in computing, it's often criticised. The problems arise when a programmer is not aware whether a function call is local or if it's a slow RPC. Confusions like that result in an unpredictable system and adds unnecessary complexity to debugging. Instead of simplifying software, misused RPC can result in unmaintainable spaghetti code.
Bearing that in mind, consider the following advice:
- Make sure it's obvious which function call is local and which is remote.
- Document your system. Make the dependencies between components clear.
- Handle error cases. How should the client react when the RPC server is down for a long time?
When in doubt avoid RPC. If you can, you should use an asynchronous pipeline - instead of RPC-like blocking, results are asynchronously pushed to a next computation stage.
Callback queue
In general doing RPC over RabbitMQ is easy. A client sends a request
message and a server replies with a response message. In order to
receive a response we need to send a 'callback' queue address with the
request. Spring AMQP's RabbitTemplate
handles the callback queue for
us when we use the above convertSendAndReceive()
method. There is
no need to do any other setup when using the RabbitTemplate
. For
a thorough explanation please see Request/Reply Message.
Message properties
The AMQP 0-9-1 protocol predefines a set of 14 properties that go with a message. Most of the properties are rarely used, with the exception of the following:
deliveryMode
: Marks a message as persistent (with a value of2
) or transient (any other value). You may remember this property from the second tutorial.contentType
: Used to describe the mime-type of the encoding. For example for the often used JSON encoding it is a good practice to set this property to:application/json
.replyTo
: Commonly used to name a callback queue.correlationId
: Useful to correlate RPC responses with requests.
Correlation Id
Spring AMQP allows you to focus on the message style you're working with and hide the details of message plumbing required to support this style. For example, typically the native client would create a callback queue for every RPC request. That's pretty inefficient so an alternative is to create a single callback queue per client.
That raises a new issue, having received a response in that queue it's
not clear to which request the response belongs. That's when the
correlationId
property is used. Spring AMQP automatically sets
a unique value for every request. In addition it handles the details
of matching the response with the correct correlationID.
One reason that Spring AMQP makes RPC style easier is that sometimes you may want to ignore unknown messages in the callback queue, rather than failing with an error. It's due to a possibility of a race condition on the server side. Although unlikely, it is possible that the RPC server will die just after sending us the answer, but before sending an acknowledgment message for the request. If that happens, the restarted RPC server will process the request again. Spring AMQP client handles the duplicate responses gracefully, and the RPC should ideally be idempotent.
Summary
Our RPC will work like this:
- The
Tut6Config
will setup a newDirectExchange
and a client - The client will leverage the
convertSendAndReceive
method, passing the exchange name, the routingKey, and the message. - The request is sent to an RPC queue
tut.rpc
. - The RPC worker (aka: server) is waiting for requests on that queue.
When a request appears, it performs the task and sends a message with the
result back to the client, using the queue from the
replyTo
field. - The client waits for data on the callback queue. When a message
appears, it checks the
correlationId
property. If it matches the value from the request it returns the response to the application. Again, this is done automagically via theRabbitTemplate
.
Putting it all together
The Fibonacci task is a @RabbitListener
and is defined as:
public int fib(int n) {
return n == 0 ? 0 : n == 1 ? 1 : (fib(n - 1) + fib(n - 2));
}
We declare our Fibonacci function. It assumes only valid positive integer input. (Don't expect this one to work for big numbers, and it's probably the slowest recursive implementation possible).
The code for our Tut6Config
class looks like this:
import org.springframework.amqp.core.Binding;
import org.springframework.amqp.core.BindingBuilder;
import org.springframework.amqp.core.DirectExchange;
import org.springframework.amqp.core.Queue;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.context.annotation.Profile;
@Profile({"tut6","rpc"})
@Configuration
public class Tut6Config {
@Profile("client")
private static class ClientConfig {
@Bean
public DirectExchange exchange() {
return new DirectExchange("tut.rpc");
}
@Bean
public Tut6Client client() {
return new Tut6Client();
}
}
@Profile("server")
private static class ServerConfig {
@Bean
public Queue queue() {
return new Queue("tut.rpc.requests");
}
@Bean
public DirectExchange exchange() {
return new DirectExchange("tut.rpc");
}
@Bean
public Binding binding(DirectExchange exchange,
Queue queue) {
return BindingBuilder.bind(queue)
.to(exchange)
.with("rpc");
}
@Bean
public Tut6Server server() {
return new Tut6Server();
}
}
}
It sets up our profiles as tut6
or rpc
. It also setups a client
profile
with 2 beans: the DirectExchange
we are using and the Tut6Client
itself.
We also configure the server
profile with 3 beans, the tut.rpc.requests
queue, the DirectExchange
, which matches the client's exchange, and the binding
from the queue to the exchange with the rpc
routing-key.
The server code is rather straightforward:
- As usual we start annotating our receiver method with a
@RabbitListener
and defining the queue it's listening on. - Our Fibonacci method calls fib() with the payload parameter and returns the result
The code for our RPC server Tut6Server.java:
package org.springframework.amqp.tutorials.tut6;
import org.springframework.amqp.rabbit.annotation.RabbitListener;
public class Tut6Server {
@RabbitListener(queues = "tut.rpc.requests")
// @SendTo("tut.rpc.replies") used when the
// client doesn't set replyTo.
public int fibonacci(int n) {
System.out.println(" [x] Received request for " + n);
int result = fib(n);
System.out.println(" [.] Returned " + result);
return result;
}
public int fib(int n) {
return n == 0 ? 0 : n == 1 ? 1 : (fib(n - 1) + fib(n - 2));
}
}
The client code Tut6Client is as easy as the server:
- We autowire the
RabbitTemplate
and theDirectExchange
bean as defined in theTut6Config
. - We invoke
template.convertSendAndReceive
with the parameters exchange name, routing key and message. - We print the result
Making the client request is simple:
import org.springframework.amqp.core.DirectExchange;
import org.springframework.amqp.rabbit.core.RabbitTemplate;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.scheduling.annotation.Scheduled;
public class Tut6Client {
@Autowired
private RabbitTemplate template;
@Autowired
private DirectExchange exchange;
int start = 0;
@Scheduled(fixedDelay = 1000, initialDelay = 500)
public void send() {
System.out.println(" [x] Requesting fib(" + start + ")");
Integer response = (Integer) template.convertSendAndReceive
(exchange.getName(), "rpc", start++);
System.out.println(" [.] Got '" + response + "'");
}
}
Using the project setup as defined in tutorial one with start.spring.io and Spring Initializr, the preparing of the runtime is the same as in the other tutorials:
./mvnw clean package
We can start the server with:
java -jar target/rabbitmq-tutorials.jar \
--spring.profiles.active=rpc,server \
--tutorial.client.duration=60000
To request a fibonacci number run the client:
java -jar target/rabbitmq-tutorials.jar \
--spring.profiles.active=rpc,client
The design presented here is not the only possible implementation of a RPC service, but it has some important advantages:
- If the RPC server is too slow, you can scale up by just running
another one. Try running a second
RPCServer
in a new console. - On the client side, the RPC requires sending and
receiving only one message with one method. No synchronous calls
like
queueDeclare
are required. As a result the RPC client needs only one network round trip for a single RPC request.
Our code is still pretty simplistic and doesn't try to solve more complex (but important) problems, like:
- How should the client react if there are no servers running?
- Should a client have some kind of timeout for the RPC?
- If the server malfunctions and raises an exception, should it be forwarded to the client?
- Protecting against invalid incoming messages (eg checking bounds, type) before processing.
If you want to experiment, you may find the management UI useful for viewing the queues.