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