Programming Model
This section describes Spring Cloud Stream’s programming model. Spring Cloud Stream provides a number of predefined annotations for declaring bound input and output channels as well as how to listen to channels.
Declaring and Binding Channels
Triggering Binding Via @EnableBinding
You can turn a Spring application into a Spring Cloud Stream application by applying the @EnableBinding
annotation to one of the application’s configuration classes. The @EnableBinding
annotation itself is meta-annotated with @Configuration
and triggers the configuration of Spring Cloud Stream infrastructure:
...
@Import(...)
@Configuration
@EnableIntegration
public @interface EnableBinding {
...
Class<?>[] value() default {};
}
The @EnableBinding
annotation can take as parameters one or more interface classes that contain methods which represent bindable components (typically message channels).
Note | In Spring Cloud Stream 1.0, the only supported bindable components are the Spring Messaging MessageChannel and its extensions SubscribableChannel and PollableChannel . Future versions should extend this support to other types of components, using the same mechanism. In this documentation, we will continue to refer to channels. |
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@Input
and @Output
A Spring Cloud Stream application can have an arbitrary number of input and output channels defined in an interface as @Input
and @Output
methods:
public interface Barista {
@Input
SubscribableChannel orders();
@Output
MessageChannel hotDrinks();
@Output
MessageChannel coldDrinks();
}
Using this interface as a parameter to @EnableBinding
will trigger the creation of three bound channels named orders
, hotDrinks
, and coldDrinks
, respectively.
@EnableBinding(Barista.class)
public class CafeConfiguration {
...
}
Customizing Channel Names
Using the @Input
and @Output
annotations, you can specify a customized channel name for the channel, as shown in the following example:
public interface Barista {
...
@Input("inboundOrders")
SubscribableChannel orders();
}
In this example, the created bound channel will be named inboundOrders
.
Source
, Sink
, and Processor
For easy addressing of the most common use cases, which involve either an input channel, an output channel, or both, Spring Cloud Stream provides three predefined interfaces out of the box.
Source
can be used for an application which has a single outbound channel.
public interface Source {
String OUTPUT = "output";
@Output(Source.OUTPUT)
MessageChannel output();
}
Sink
can be used for an application which has a single inbound channel.
public interface Sink {
String INPUT = "input";
@Input(Sink.INPUT)
SubscribableChannel input();
}
Processor
can be used for an application which has both an inbound channel and an outbound channel.
public interface Processor extends Source, Sink {
}
Spring Cloud Stream provides no special handling for any of these interfaces; they are only provided out of the box.
Accessing Bound Channels
Injecting the Bound Interfaces
For each bound interface, Spring Cloud Stream will generate a bean that implements the interface. Invoking a @Input
-annotated or @Output
-annotated method of one of these beans will return the relevant bound channel.
The bean in the following example sends a message on the output channel when its hello
method is invoked. It invokes output()
on the injected Source
bean to retrieve the target channel.
@Component
public class SendingBean {
private Source source;
@Autowired
public SendingBean(Source source) {
this.source = source;
}
public void sayHello(String name) {
source.output().send(MessageBuilder.withPayload(name).build());
}
}
Injecting Channels Directly
Bound channels can be also injected directly:
@Component
public class SendingBean {
private MessageChannel output;
@Autowired
public SendingBean(MessageChannel output) {
this.output = output;
}
public void sayHello(String name) {
output.send(MessageBuilder.withPayload(name).build());
}
}
If the name of the channel is customized on the declaring annotation, that name should be used instead of the method name. Given the following declaration:
public interface CustomSource {
...
@Output("customOutput")
MessageChannel output();
}
The channel will be injected as shown in the following example:
@Component
public class SendingBean {
private MessageChannel output;
@Autowired
public SendingBean(@Qualifier("customOutput") MessageChannel output) {
this.output = output;
}
public void sayHello(String name) {
this.output.send(MessageBuilder.withPayload(name).build());
}
}
Producing and Consuming Messages
You can write a Spring Cloud Stream application using either Spring Integration annotations or Spring Cloud Stream’s @StreamListener
annotation. The @StreamListener
annotation is modeled after other Spring Messaging annotations (such as @MessageMapping
, @JmsListener
, @RabbitListener
, etc.) but adds content type management and type coercion features.
Native Spring Integration Support
Because Spring Cloud Stream is based on Spring Integration, Stream completely inherits Integration’s foundation and infrastructure as well as the component itself. For example, you can attach the output channel of a Source
to a MessageSource
:
@EnableBinding(Source.class)
public class TimerSource {
@Value("${format}")
private String format;
@Bean
@InboundChannelAdapter(value = Source.OUTPUT, poller = @Poller(fixedDelay = "${fixedDelay}", maxMessagesPerPoll = "1"))
public MessageSource<String> timerMessageSource() {
return () -> new GenericMessage<>(new SimpleDateFormat(format).format(new Date()));
}
}
Or you can use a processor’s channels in a transformer:
@EnableBinding(Processor.class)
public class TransformProcessor {
@Transformer(inputChannel = Processor.INPUT, outputChannel = Processor.OUTPUT)
public Object transform(String message) {
return message.toUpperCase();
}
}
Spring Integration Error Channel Support
Spring Cloud Stream supports publishing error messages received by the Spring Integration global error channel. Error messages sent to the errorChannel
can be published to a specific destination at the broker by configuring a binding for the outbound target named error
. For example, to publish error messages to a broker destination named "myErrors", provide the following property: spring.cloud.stream.bindings.error.destination=myErrors
Using @StreamListener for Automatic Content Type Handling
Complementary to its Spring Integration support, Spring Cloud Stream provides its own @StreamListener
annotation, modeled after other Spring Messaging annotations (e.g. @MessageMapping
, @JmsListener
, @RabbitListener
, etc.). The @StreamListener
annotation provides a simpler model for handling inbound messages, especially when dealing with use cases that involve content type management and type coercion.
Spring Cloud Stream provides an extensible MessageConverter
mechanism for handling data conversion by bound channels and for, in this case, dispatching to methods annotated with @StreamListener
. The following is an example of an application which processes external Vote
events:
@EnableBinding(Sink.class)
public class VoteHandler {
@Autowired
VotingService votingService;
@StreamListener(Sink.INPUT)
public void handle(Vote vote) {
votingService.record(vote);
}
}
The distinction between @StreamListener
and a Spring Integration @ServiceActivator
is seen when considering an inbound Message
that has a String
payload and a contentType
header of application/json
. In the case of @StreamListener
, the MessageConverter
mechanism will use the contentType
header to parse the String
payload into a Vote
object.
As with other Spring Messaging methods, method arguments can be annotated with @Payload
, @Headers
and @Header
.
Note | For methods which return data, you must use the @SendTo annotation to specify the output binding destination for data returned by the method: |
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Using @StreamListener for dispatching messages to multiple methods
Since version 1.2, Spring Cloud Stream supports dispatching messages to multiple @StreamListener
methods registered on an input channel, based on a condition.
In order to be eligible to support conditional dispatching, a method must satisfy the follow conditions:
it must not return a value
it must be an individual message handling method (reactive API methods are not supported)
The condition is specified via a SpEL expression in the condition
attribute of the annotation and is evaluated for each message. All the handlers that match the condition will be invoked in the same thread and no assumption must be made about the order in which the invocations take place.
An example of using @StreamListener
with dispatching conditions can be seen below. In this example, all the messages bearing a header type
with the value foo
will be dispatched to the receiveFoo
method, and all the messages bearing a header type
with the value bar
will be dispatched to the receiveBar
method.
@EnableBinding(Sink.class)
@EnableAutoConfiguration
public static class TestPojoWithAnnotatedArguments {
@StreamListener(target = Sink.INPUT, condition = "headers['type']=='foo'")
public void receiveFoo(@Payload FooPojo fooPojo) {
// handle the message
}
@StreamListener(target = Sink.INPUT, condition = "headers['type']=='bar'")
public void receiveBar(@Payload BarPojo barPojo) {
// handle the message
}
}
Note | Dispatching via @StreamListener conditions is only supported for handlers of individual messages, and not for reactive programming support (described below). |
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Reactive Programming Support
Spring Cloud Stream also supports the use of reactive APIs where incoming and outgoing data is handled as continuous data flows. Support for reactive APIs is available via the spring-cloud-stream-reactive
, which needs to be added explicitly to your project.
The programming model with reactive APIs is declarative, where instead of specifying how each individual message should be handled, you can use operators that describe functional transformations from inbound to outbound data flows.
Spring Cloud Stream supports the following reactive APIs:
Reactor
RxJava 1.x
In the future, it is intended to support a more generic model based on Reactive Streams.
The reactive programming model is also using the @StreamListener
annotation for setting up reactive handlers. The differences are that:
the
@StreamListener
annotation must not specify an input or output, as they are provided as arguments and return values from the method;the arguments of the method must be annotated with
@Input
and@Output
indicating which input or output will the incoming and respectively outgoing data flows connect to;the return value of the method, if any, will be annotated with
@Output
, indicating the input where data shall be sent.
Note | Reactive programming support requires Java 1.8. |
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Note | As of Spring Cloud Stream 1.1.1 and later (starting with release train Brooklyn.SR2), reactive programming support requires the use of Reactor 3.0.4.RELEASE and higher. Earlier Reactor versions (including 3.0.1.RELEASE, 3.0.2.RELEASE and 3.0.3.RELEASE) are not supported. spring-cloud-stream-reactive will transitively retrieve the proper version, but it is possible for the project structure to manage the version of the io.projectreactor:reactor-core to an earlier release, especially when using Maven. This is the case for projects generated via Spring Initializr with Spring Boot 1.x, which will override the Reactor version to 2.0.8.RELEASE . In such cases you must ensure that the proper version of the artifact is released. This can be simply achieved by adding a direct dependency on io.projectreactor:reactor-core with a version of 3.0.4.RELEASE or later to your project. |
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Note | The use of term reactive is currently referring to the reactive APIs being used and not to the execution model being reactive (i.e. the bound endpoints are still using a 'push' rather than 'pull' model). While some backpressure support is provided by the use of Reactor, we do intend on the long run to support entirely reactive pipelines by the use of native reactive clients for the connected middleware. |
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Reactor-based handlers
A Reactor based handler can have the following argument types:
For arguments annotated with
@Input
, it supports the Reactor typeFlux
. The parameterization of the inbound Flux follows the same rules as in the case of individual message handling: it can be the entireMessage
, a POJO which can be theMessage
payload, or a POJO which is the result of a transformation based on theMessage
content-type header. Multiple inputs are provided;For arguments annotated with
Output
, it supports the typeFluxSender
which connects aFlux
produced by the method with an output. Generally speaking, specifying outputs as arguments is only recommended when the method can have multiple outputs;
A Reactor based handler supports a return type of Flux
, case in which it must be annotated with @Output
. We recommend using the return value of the method when a single output flux is available.
Here is an example of a simple Reactor-based Processor.
@EnableBinding(Processor.class)
@EnableAutoConfiguration
public static class UppercaseTransformer {
@StreamListener
@Output(Processor.OUTPUT)
public Flux<String> receive(@Input(Processor.INPUT) Flux<String> input) {
return input.map(s -> s.toUpperCase());
}
}
The same processor using output arguments looks like this:
@EnableBinding(Processor.class)
@EnableAutoConfiguration
public static class UppercaseTransformer {
@StreamListener
public void receive(@Input(Processor.INPUT) Flux<String> input,
@Output(Processor.OUTPUT) FluxSender output) {
output.send(input.map(s -> s.toUpperCase()));
}
}
RxJava 1.x support
RxJava 1.x handlers follow the same rules as Reactor-based one, but will use Observable
and ObservableSender
arguments and return types.
So the first example above will become:
@EnableBinding(Processor.class)
@EnableAutoConfiguration
public static class UppercaseTransformer {
@StreamListener
@Output(Processor.OUTPUT)
public Observable<String> receive(@Input(Processor.INPUT) Observable<String> input) {
return input.map(s -> s.toUpperCase());
}
}
The second example above will become:
@EnableBinding(Processor.class)
@EnableAutoConfiguration
public static class UppercaseTransformer {
@StreamListener
public void receive(@Input(Processor.INPUT) Observable<String> input,
@Output(Processor.OUTPUT) ObservableSender output) {
output.send(input.map(s -> s.toUpperCase()));
}
}
Aggregation
Spring Cloud Stream provides support for aggregating multiple applications together, connecting their input and output channels directly and avoiding the additional cost of exchanging messages via a broker. As of version 1.0 of Spring Cloud Stream, aggregation is supported only for the following types of applications:
sources - applications with a single output channel named
output
, typically having a single binding of the typeorg.springframework.cloud.stream.messaging.Source
sinks - applications with a single input channel named
input
, typically having a single binding of the typeorg.springframework.cloud.stream.messaging.Sink
processors - applications with a single input channel named
input
and a single output channel namedoutput
, typically having a single binding of the typeorg.springframework.cloud.stream.messaging.Processor
.
They can be aggregated together by creating a sequence of interconnected applications, in which the output channel of an element in the sequence is connected to the input channel of the next element, if it exists. A sequence can start with either a source or a processor, it can contain an arbitrary number of processors and must end with either a processor or a sink.
Depending on the nature of the starting and ending element, the sequence may have one or more bindable channels, as follows:
if the sequence starts with a source and ends with a sink, all communication between the applications is direct and no channels will be bound
if the sequence starts with a processor, then its input channel will become the
input
channel of the aggregate and will be bound accordinglyif the sequence ends with a processor, then its output channel will become the
output
channel of the aggregate and will be bound accordingly
Aggregation is performed using the AggregateApplicationBuilder
utility class, as in the following example. Let’s consider a project in which we have source, processor and a sink, which may be defined in the project, or may be contained in one of the project’s dependencies.
Note | Each component (source, sink or processor) in an aggregate application must be provided in a separate package if the configuration classes use @SpringBootApplication . This is required to avoid cross-talk between applications, due to the classpath scanning performed by @SpringBootApplication on the configuration classes inside the same package. In the example below, it can be seen that the Source, Processor and Sink application classes are grouped in separate packages. A possible alternative is to provide the source, sink or processor configuration in a separate @Configuration class, avoid the use of @SpringBootApplication /@ComponentScan and use those for aggregation. |
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package com.app.mysink;
@SpringBootApplication
@EnableBinding(Sink.class)
public class SinkApplication {
private static Logger logger = LoggerFactory.getLogger(SinkApplication.class);
@ServiceActivator(inputChannel=Sink.INPUT)
public void loggerSink(Object payload) {
logger.info("Received: " + payload);
}
}
package com.app.myprocessor;
@SpringBootApplication
@EnableBinding(Processor.class)
public class ProcessorApplication {
@Transformer
public String loggerSink(String payload) {
return payload.toUpperCase();
}
}
package com.app.mysource;
@SpringBootApplication
@EnableBinding(Source.class)
public class SourceApplication {
@Bean
@InboundChannelAdapter(value = Source.OUTPUT)
public String timerMessageSource() {
return new SimpleDateFormat().format(new Date());
}
}
Each configuration can be used for running a separate component, but in this case they can be aggregated together as follows:
package com.app;
@SpringBootApplication
public class SampleAggregateApplication {
public static void main(String[] args) {
new AggregateApplicationBuilder()
.from(SourceApplication.class).args("--fixedDelay=5000")
.via(ProcessorApplication.class)
.to(SinkApplication.class).args("--debug=true").run(args);
}
}
The starting component of the sequence is provided as argument to the from()
method. The ending component of the sequence is provided as argument to the to()
method. Intermediate processors are provided as argument to the via()
method. Multiple processors of the same type can be chained together (e.g. for pipelining transformations with different configurations). For each component, the builder can provide runtime arguments for Spring Boot configuration.
Configuring aggregate application
Spring Cloud Stream supports passing properties for the individual applications inside the aggregate application using 'namespace' as prefix.
The namespace can be set for applications as follows:
@SpringBootApplication
public class SampleAggregateApplication {
public static void main(String[] args) {
new AggregateApplicationBuilder()
.from(SourceApplication.class).namespace("source").args("--fixedDelay=5000")
.via(ProcessorApplication.class).namespace("processor1")
.to(SinkApplication.class).namespace("sink").args("--debug=true").run(args);
}
}
Once the 'namespace' is set for the individual applications, the application properties with the namespace
as prefix can be passed to the aggregate application using any supported property source (commandline, environment properties etc.,)
For instance, to override the default fixedDelay
and debug
properties of 'source' and 'sink' applications:
java -jar target/MyAggregateApplication-0.0.1-SNAPSHOT.jar --source.fixedDelay=10000 --sink.debug=false
Configuring binding service properties for non self contained aggregate application
The non self-contained aggregate application is bound to external broker via either or both the inbound/outbound components (typically, message channels) of the aggregate application while the applications inside the aggregate application are directly bound. For example: a source application’s output and a processor application’s input are directly bound while the processor’s output channel is bound to an external destination at the broker. When passing the binding service properties for non-self contained aggregate application, it is required to pass the binding service properties to the aggregate application instead of setting them as 'args' to individual child application. For instance,
@SpringBootApplication
public class SampleAggregateApplication {
public static void main(String[] args) {
new AggregateApplicationBuilder()
.from(SourceApplication.class).namespace("source").args("--fixedDelay=5000")
.via(ProcessorApplication.class).namespace("processor1").args("--debug=true").run(args);
}
}
The binding properties like --spring.cloud.stream.bindings.output.destination=processor-output
need to be specified as one of the external configuration properties (cmdline arg etc.,).