Asynchrone HTTP-Programmierung mit Play Framework

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1. Übersicht

Oft müssen unsere Webdienste andere Webdienste verwenden, um ihre Arbeit zu erledigen. Es kann schwierig sein, Benutzeranforderungen zu bearbeiten, während die Antwortzeit niedrig gehalten wird. Ein langsamer externer Service kann unsere Antwortzeit verlängern und dazu führen, dass unser System Anforderungen mit mehr Ressourcen stapelt. Hier kann ein nicht blockierender Ansatz sehr hilfreich sein

In diesem Tutorial werden mehrere asynchrone Anforderungen an einen Dienst aus einer Play Framework-Anwendung ausgelöst. Durch die Nutzung der nicht blockierenden HTTP-Funktion von Java können wir externe Ressourcen reibungslos abfragen, ohne unsere eigene Hauptlogik zu beeinträchtigen.

In unserem Beispiel untersuchen wir die Play WebService Library.

2. Die Play WebService (WS) -Bibliothek

WS ist eine leistungsstarke Bibliothek, die asynchrone HTTP-Aufrufe mit Java Action bereitstellt .

Mit dieser Bibliothek sendet unser Code diese Anforderungen und fährt fort, ohne zu blockieren. Um das Ergebnis der Anfrage zu verarbeiten, stellen wir eine konsumierende Funktion bereit, dh eine Implementierung der Consumer- Schnittstelle.

Dieses Muster weist einige Ähnlichkeiten mit der JavaScript-Implementierung von Rückrufen, Versprechungen und dem asynchronen / wartenden Muster auf.

Erstellen wir einen einfachen Consumer , der einige der Antwortdaten protokolliert:

ws.url(url) .thenAccept(r -> log.debug("Thread#" + Thread.currentThread().getId() + " Request complete: Response code = " + r.getStatus() + " | Response: " + r.getBody() + " | Current Time:" + System.currentTimeMillis()))

Unser Verbraucher meldet sich lediglich in diesem Beispiel an. Der Verbraucher kann jedoch alles tun, was wir mit dem Ergebnis tun müssen, z. B. das Ergebnis in einer Datenbank speichern.

Wenn wir uns die Implementierung der Bibliothek genauer ansehen , können wir feststellen, dass WS den AsyncHttpClient von Java umschließt und konfiguriert , der Teil des Standard-JDK ist und nicht von Play abhängt.

3. Bereiten Sie ein Beispielprojekt vor

Um mit dem Framework zu experimentieren, erstellen wir einige Komponententests, um Anforderungen zu starten. Wir erstellen eine Skelett-Webanwendung, um sie zu beantworten, und verwenden das WS-Framework, um HTTP-Anforderungen zu stellen.

3.1. Die Skeleton-Webanwendung

Zunächst erstellen wir das erste Projekt mit dem Befehl sbt new :

sbt new playframework/play-java-seed.g8

Im neuen Ordner bearbeiten wir dann die Datei build.sbt und fügen die Abhängigkeit der WS-Bibliothek hinzu:

libraryDependencies += javaWs

Jetzt können wir den Server mit dem Befehl sbt run starten :

$ sbt run ... --- (Running the application, auto-reloading is enabled) --- [info] p.c.s.AkkaHttpServer - Listening for HTTP on /0:0:0:0:0:0:0:0:9000

Sobald die Anwendung gestartet wurde, können wir überprüfen, ob alles in Ordnung ist, indem wir // localhost: 9000 durchsuchen , wodurch die Begrüßungsseite von Play geöffnet wird.

3.2. Die Testumgebung

Zum Testen unserer Anwendung verwenden wir die Unit-Test-Klasse HomeControllerTest .

Zunächst müssen wir WithServer erweitern, um den Serverlebenszyklus bereitzustellen:

public class HomeControllerTest extends WithServer { 

Dank ihres übergeordneten Elements startet diese Klasse unseren Skeleton-Webserver jetzt im Testmodus und an einem zufälligen Port , bevor die Tests ausgeführt werden. Die WithServer- Klasse stoppt die Anwendung auch, wenn der Test abgeschlossen ist.

Als nächstes müssen wir eine Anwendung zum Ausführen bereitstellen.

Wir können es mit erstellen Guice ‚s GuiceApplicationBuilder :

@Override protected Application provideApplication() { return new GuiceApplicationBuilder().build(); } 

Und schließlich richten wir die Server-URL für unsere Tests unter Verwendung der vom Testserver bereitgestellten Portnummer ein:

@Override @Before public void setup() { OptionalInt optHttpsPort = testServer.getRunningHttpsPort(); if (optHttpsPort.isPresent()) { port = optHttpsPort.getAsInt(); url = "//localhost:" + port; } else { port = testServer.getRunningHttpPort() .getAsInt(); url = "//localhost:" + port; } }

Jetzt können wir Tests schreiben. Mit dem umfassenden Testframework können wir uns auf die Codierung unserer Testanforderungen konzentrieren.

4. Bereiten Sie eine WSRequest vor

Mal sehen, wie wir grundlegende Arten von Anforderungen wie GET oder POST und mehrteilige Anforderungen für das Hochladen von Dateien auslösen können.

4.1. Initialisieren Sie das WSRequest- Objekt

Zunächst müssen wir eine WSClient- Instanz erhalten, um unsere Anforderungen zu konfigurieren und zu initialisieren.

In einer realen Anwendung können wir einen Client, der mit Standardeinstellungen automatisch konfiguriert wird, über die Abhängigkeitsinjektion erhalten:

@Autowired WSClient ws;

In unserer Testklasse verwenden wir jedoch WSTestClient , das im Play Test Framework verfügbar ist:

WSClient ws = play.test.WSTestClient.newClient(port);

Sobald wir unseren Client haben, können wir ein WSRequest- Objekt durch Aufrufen der URL- Methode initialisieren :

ws.url(url)

Die URL- Methode reicht aus, um eine Anfrage auszulösen. Wir können es jedoch weiter anpassen, indem wir einige benutzerdefinierte Einstellungen hinzufügen:

ws.url(url) .addHeader("key", "value") .addQueryParameter("num", "" + num);

As we can see, it's pretty easy to add headers and query parameters.

After we've fully configured our request, we can call the method to initiate it.

4.2. Generic GET Request

To trigger a GET request we just have to call the get method on our WSRequest object:

ws.url(url) ... .get();

As this is a non-blocking code, it starts the request and then continues execution at the next line of our function.

The object returned by get is a CompletionStage instance, which is part of the CompletableFuture API.

Once the HTTP call has completed, this stage executes just a few instructions. It wraps the response in a WSResponse object.

Normally, this result would be passed on to the next stage of the execution chain. In this example, we have not provided any consuming function, so the result is lost.

For this reason, this request is of type “fire-and-forget”.

4.3. Submit a Form

Submitting a form is not very different from the get example.

To trigger the request we just call the post method:

ws.url(url) ... .setContentType("application/x-www-form-urlencoded") .post("key1=value1&key2=value2");

In this scenario, we need to pass a body as a parameter. This can be a simple string like a file, a json or xml document, a BodyWritable or a Source.

4.4. Submit a Multipart/Form Data

A multipart form requires us to send both input fields and data from an attached file or stream.

To implement this in the framework, we use the post method with a Source.

Inside the source, we can wrap all the different data types needed by our form:

Source file = FileIO.fromPath(Paths.get("hello.txt")); FilePart file = new FilePart("fileParam", "myfile.txt", "text/plain", file); DataPart data = new DataPart("key", "value"); ws.url(url) ... .post(Source.from(Arrays.asList(file, data)));

Though this approach adds some more configuration, it is still very similar to the other types of requests.

5. Process the Async Response

Up to this point, we have only triggered fire-and-forget requests, where our code doesn't do anything with the response data.

Let's now explore two techniques for processing an asynchronous response.

We can either block the main thread, waiting for a CompletableFuture, or consume asynchronously with a Consumer.

5.1. Process Response by Blocking With CompletableFuture

Even when using an asynchronous framework, we may choose to block our code's execution and wait for the response.

Using the CompletableFuture API, we just need a few changes in our code to implement this scenario:

WSResponse response = ws.url(url) .get() .toCompletableFuture() .get();

This could be useful, for example, to provide a strong data consistency that we cannot achieve in other ways.

5.2. Process Response Asynchronously

To process an asynchronous response without blocking, we provide a Consumer or Function that is run by the asynchronous framework when the response is available.

For example, let's add a Consumer to our previous example to log the response:

ws.url(url) .addHeader("key", "value") .addQueryParameter("num", "" + 1) .get() .thenAccept(r -> log.debug("Thread#" + Thread.currentThread().getId() + " Request complete: Response code = " + r.getStatus() + " | Response: " + r.getBody() + " | Current Time:" + System.currentTimeMillis()));

We then see the response in the logs:

[debug] c.HomeControllerTest - Thread#30 Request complete: Response code = 200 | Response: { "Result" : "ok", "Params" : { "num" : [ "1" ] }, "Headers" : { "accept" : [ "*/*" ], "host" : [ "localhost:19001" ], "key" : [ "value" ], "user-agent" : [ "AHC/2.1" ] } } | Current Time:1579303109613

It's worth noting that we used thenAccept, which requires a Consumer function since we don't need to return anything after logging.

When we want the current stage to return something, so that we can use it in the next stage, we need thenApply instead, which takes a Function.

These use the conventions of the standard Java Functional Interfaces.

5.3. Large Response Body

The code we've implemented so far is a good solution for small responses and most use cases. However, if we need to process a few hundreds of megabytes of data, we'll need a better strategy.

We should note: Request methods like get and post load the entire response in memory.

To avoid a possible OutOfMemoryError, we can use Akka Streams to process the response without letting it fill our memory.

For example, we can write its body in a file:

ws.url(url) .stream() .thenAccept( response -> { try { OutputStream outputStream = Files.newOutputStream(path); Sink
    
      outputWriter = Sink.foreach(bytes -> outputStream.write(bytes.toArray())); response.getBodyAsSource().runWith(outputWriter, materializer); } catch (IOException e) { log.error("An error happened while opening the output stream", e); } });
    

The stream method returns a CompletionStage where the WSResponse has a getBodyAsStream method that provides a Source.

We can tell the code how to process this type of body by using Akka's Sink, which in our example will simply write any data passing through in the OutputStream.

5.4. Timeouts

When building a request, we can also set a specific timeout, so the request is interrupted if we don't receive the complete response in time.

This is a particularly useful feature when we see that a service we're querying is particularly slow and could cause a pile-up of open connections stuck waiting for the response.

We can set a global timeout for all our requests using tuning parameters. For a request-specific timeout, we can add to a request using setRequestTimeout:

ws.url(url) .setRequestTimeout(Duration.of(1, SECONDS));

There's still one case to handle, though: We may have received all the data, but our Consumer may be very slow processing it. This might happen if there is lots of data crunching, database calls, etc.

In low throughput systems, we can simply let the code run until it completes. However, we may wish to abort long-running activities.

To achieve that, we have to wrap our code with some futures handling.

Let's simulate a very long process in our code:

ws.url(url) .get() .thenApply( result -> { try { Thread.sleep(10000L); return Results.ok(); } catch (InterruptedException e) { return Results.status(SERVICE_UNAVAILABLE); } });

This will return an OK response after 10 seconds, but we don't want to wait that long.

Instead, with the timeout wrapper, we instruct our code to wait for no more than 1 second:

CompletionStage f = futures.timeout( ws.url(url) .get() .thenApply(result -> { try { Thread.sleep(10000L); return Results.ok(); } catch (InterruptedException e) { return Results.status(SERVICE_UNAVAILABLE); } }), 1L, TimeUnit.SECONDS); 

Now our future will return a result either way: the computation result if the Consumer finished in time, or the exception due to the futures timeout.

5.5. Handling Exceptions

In the previous example, we created a function that either returns a result or fails with an exception. So, now we need to handle both scenarios.

We can handle both success and failure scenarios with the handleAsync method.

Let's say that we want to return the result, if we've got it, or log the error and return the exception for further handling:

CompletionStage res = f.handleAsync((result, e) -> { if (e != null) { log.error("Exception thrown", e); return e.getCause(); } else { return result; } }); 

The code should now return a CompletionStage containing the TimeoutException thrown.

We can verify it by simply calling an assertEquals on the class of the exception object returned:

Class clazz = res.toCompletableFuture().get().getClass(); assertEquals(TimeoutException.class, clazz);

When running the test, it will also log the exception we received:

[error] c.HomeControllerTest - Exception thrown java.util.concurrent.TimeoutException: Timeout after 1 second ...

6. Request Filters

Sometimes, we need to run some logic before a request is triggered.

We could manipulate the WSRequest object once initialized, but a more elegant technique is to set a WSRequestFilter.

A filter can be set during initialization, before calling the triggering method, and is attached to the request logic.

We can define our own filter by implementing the WSRequestFilter interface, or we can add a ready-made one.

A common scenario is logging what the request looks like before executing it.

In this case, we just need to set the AhcCurlRequestLogger:

ws.url(url) ... .setRequestFilter(new AhcCurlRequestLogger()) ... .get();

The resulting log has a curl-like format:

[info] p.l.w.a.AhcCurlRequestLogger - curl \ --verbose \ --request GET \ --header 'key: value' \ '//localhost:19001'

We can set the desired log level, by changing our logback.xml configuration.

7. Caching Responses

WSClient also supports the caching of responses.

This feature is particularly useful when the same request is triggered multiple times and we don't need the freshest data every time.

It also helps when the service we're calling is temporarily down.

7.1. Add Caching Dependencies

To configure caching we need first to add the dependency in our build.sbt:

libraryDependencies += ehcache

This configures Ehcache as our caching layer.

If we don't want Ehcache specifically, we can use any other JSR-107 cache implementation.

7.2. Force Caching Heuristic

By default, Play WS won't cache HTTP responses if the server doesn't return any caching configuration.

To circumvent this, we can force the heuristic caching by adding a setting to our application.conf:

play.ws.cache.heuristics.enabled=true

This will configure the system to decide when it's useful to cache an HTTP response, regardless of the remote service's advertised caching.

8. Additional Tuning

Making requests to an external service may require some client configuration. We may need to handle redirects, a slow server, or some filtering depending on the user-agent header.

To address that, we can tune our WS client, using properties in our application.conf:

play.ws.followRedirects=false play.ws.useragent=MyPlayApplication play.ws.compressionEnabled=true # time to wait for the connection to be established play.ws.timeout.connection=30 # time to wait for data after the connection is open play.ws.timeout.idle=30 # max time available to complete the request play.ws.timeout.request=300

It's also possible to configure the underlying AsyncHttpClient directly.

The full list of available properties can be checked in the source code of AhcConfig.

9. Conclusion

In this article, we explored the Play WS library and its main features. We configured our project, learned how to fire common requests and to process their response, both synchronously and asynchronously.

We worked with large data downloads and saw how to cut short long-running activities.

Schließlich haben wir uns das Caching angesehen, um die Leistung zu verbessern und den Client zu optimieren.

Wie immer ist der Quellcode für dieses Tutorial auf GitHub verfügbar.

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Ich habe gerade den neuen Learn Spring- Kurs angekündigt , der sich auf die Grundlagen von Spring 5 und Spring Boot 2 konzentriert:

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