Spring Cloud Function provides a new programming model for Spring Boot
applications, abstracting away all of the transport details and
infrastructure, allowing the developer to keep all the familiar tools
and processes, and focus firmly on business logic.
Here's a complete, executable, testable Spring Boot application
(implementing a simple string manipulation):
```
@SpringBootApplication
public class Application {
@Bean
public Function<Flux<String>, Flux<String>> uppercase() {
return flux -> flux.map(value -> value.toUpperCase());
}
public static void main(String[] args) {
SpringApplication.run(Application.class, args);
}
}
```
It's just a Spring Boot application, so it can be built, run and
tested, locally and in a CI build, the same way as any other Spring
Boot application. The `Function` is from `java.util` and `Flux` is a
http://www.reactive-streams.org/[Reactive Streams] `Publisher` from
https://projectreactor.io/[Project Reactor]. The function can be
accessed over HTTP or messaging.
Spring Cloud Function has 4 main features:
1. Wrappers for `@Beans` of type `Function`, `Consumer` and
`Supplier`, exposing them to the outside world as either HTTP
endpoints and/or message stream listeners/publishers with RabbitMQ, Kafka etc.
2. Compiling strings which are Java function bodies into bytecode, and
then turning them into `@Beans` that can be wrapped as above.
3. Deploying a JAR file containing such an application context with an
isolated classloader, so that you can pack them together in a single
JVM.
4. TBD: adapters for AWS Lambda, and possibly other "serverless"
service providers.
== Getting Started
Build from the command line (and "install" the samples):
```
$ ./mvnw clean install
```
(If you like to YOLO add `-DskipTests`.)
Run one of the samples, e.g.
```
$ java -jar spring-cloud-function-samples/spring-cloud-function-sample/target/*.jar
```
This runs the app and exposes its functions over HTTP, so you can
convert a string to uppercase, like this:
```
$ curl -H "Content-Type: text/plain" localhost:8080/uppercase -d Hello
HELLO
```
You can convert multiple strings (a `Flux<String>`) by separating them
with new lines
```
$ curl -H "Content-Type: text/plain" localhost:8080/uppercase -d 'Hello
> World'
HELLOWORLD
```
(You can use `^Q^J` in a terminal to insert a new line in a literal
string like that.)
== Building and Running a Function
The sample `@SpringBootApplication` above has a function that can be
decorated at runtime by Spring Cloud Function to be an HTTP endpoint,
or a Stream processor, for instance with RabbitMQ, Apache Kafka or
JMS.
The `@Beans` can be `Function`, `Consumer` or `Supplier` (all from
`java.util`), and their parametric types can be String or POJO. A
`Function` is exposed as an HTTP POST if `spring-cloud-function-web`
is on the classpath, and as a Spring Cloud Stream `Processor` if
`spring-cloud-function-stream` is on the classpath and a
`spring.cloud.function.stream.endpoint` property is configured in the Spring
environment. A `Consumer` is also exposed as an HTTP POST, or as a Stream
`Sink`. A `Supplier` translates to an HTTP GET, or a Stream `Source`.
Functions can be of `Flux<String>` or `Flux<Pojo>` and Spring Cloud
Function takes care of converting the data to and from the desired
types, as long as it comes in as plain text or (in the case of the
POJO) JSON. TBD: support for `Flux<Message<Pojo>>` and maybe plain
`Pojo` types (Fluxes implied and implemented by the framework).
Functions can be grouped together in a single application, or deployed
one-per-jar. It's up to the developer to choose. An app with multiple
functions can be deployed multiple times in different "personalities",
exposing different functions over different physical transports.
== Deploying a Packaged Function
TBD: describe the deployer app.
== Dynamic Compilation
To run these examples, change into the `scripts` directory:
----
cd scripts
----
Also, start a RabbitMQ server locally (e.g. execute `rabbitmq-server`).
=== Start the Function Registry Service:
----
./function-registry.sh
----
=== Register a Function:
----
./registerFunction.sh -n uppercase -f "f->f.map(s->s.toString().toUpperCase())"
----
=== Run a REST Microservice using that Function:
----
./web.sh -f uppercase -p 9000
curl -H "Content-Type: text/plain" -H "Accept: text/plain" :9000/uppercase -d foo
----
=== Register a Supplier:
----
./registerSupplier.sh -n words -f "()->Flux.just(\"foo\",\"bar\")"
----
=== Run a REST Microservice using that Supplier:
----
./web.sh -s words -p 9001
curl -H "Accept: application/json" :9001/words
----
=== Register a Consumer:
----
./registerConsumer.sh -n print -f "System.out::println"
----
=== Run a REST Microservice using that Consumer:
----
./web.sh -c print -p 9002
curl -X POST -H "Content-Type: text/plain" -d foo :9002/print
----
=== Run Stream Processing Microservices:
First register a streaming words supplier:
----
./registerSupplier.sh -n wordstream -f "()->Flux.intervalMillis(1000).map(i->\"message-\"+i)"
----
Then start the source (supplier), processor (function), and sink (consumer) apps
(in reverse order):
----
./stream.sh -p 9103 -i uppercaseWords -c print
./stream.sh -p 9102 -i words -f uppercase -o uppercaseWords
./stream.sh -p 9101 -s wordstream -o words
----
The output will appear in the console of the sink app (one message per second, converted to uppercase):
----
MESSAGE-0
MESSAGE-1
MESSAGE-2
MESSAGE-3
MESSAGE-4
MESSAGE-5
MESSAGE-6
MESSAGE-7
MESSAGE-8
MESSAGE-9
...
----