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.
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 |
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 { ... }
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
.
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.
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(body).build()); } }
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(body).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 { @Autowired private MessageChannel output; @Autowired @Qualifier("customOutput") public SendingBean(MessageChannel output) { this.output = output; } public void sayHello(String name) { customOutput.send(MessageBuilder.withPayload(body).build()); } }
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.
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.toUpper(); } }
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 @EnableBinding(Processor.class) public class TransformProcessor { @Autowired VotingService votingService; @StreamListener(Processor.INPUT) @SendTo(Processor.OUTPUT) public VoteResult handle(Vote vote) { return votingService.record(vote); } } |
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:
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:
@StreamListener
annotation must not specify an input or output, as they are provided as arguments and return values from the method;@Input
and @Output
indicating which input or output will the incoming and respectively outgoing data flows connect to;@Output
, indicating the input where data shall be sent.Note | |
---|---|
Reactive programming support requires Java 1.8. |
Note | |
---|---|
Reactive programming support requires the use of Reactor 3.0.0 and higher. |
Note | |
---|---|
The use of term |
A Reactor based handler can have the following argument types:
@Input
, it supports the Reactor type Flux
.
The parameterization of the inbound Flux follows the same rules as in the case of individual message handling: it can be the entire Message
, a POJO which can be the Message
payload, or a POJO which is the result of a transformation based on the Message
content-type header. Multiple inputs are provided;Output
, it supports the type FluxSender
which connects a Flux
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 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())); } }
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:
output
, typically having a single binding of the type org.springframework.cloud.stream.messaging.Source
input
, typically having a single binding of the type org.springframework.cloud.stream.messaging.Sink
input
and a single output channel named output
, typically having a single binding of the type org.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:
input
channel of the aggregate and will be bound accordinglyoutput
channel of the aggregate and will be bound accordinglyAggregation 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.
@SpringBootApplication @EnableBinding(Sink.class) public class SinkApplication { private static Logger logger = LoggerFactory.getLogger(SinkModuleDefinition.class); @ServiceActivator(inputChannel=Sink.INPUT) public void loggerSink(Object payload) { logger.info("Received: " + payload); } }
@SpringBootApplication @EnableBinding(Processor.class) public class ProcessorApplication { @Transformer public String loggerSink(String payload) { return payload.toUpperCase(); } }
@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:
@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.