play framework: async i/o with java and scala
Post on 17-Oct-2014
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DESCRIPTION
This talk is a brief introduction to writing asynchronous code with the Play Framework.TRANSCRIPT
Asynchronous I/Owith Java and Scala
LinkedIn uses a service oriented architecture (SOA)
Hundreds of different types of services, thousands of instances in multiple data centers.
Internet Load Balancer
Profile frontend
Company frontend
Recruiter frontend
Profile backend
Search backend
Company backend
Recruiter backend
Ads backend
Data Store
Data Store
Data Store
Data Store
Services communicate with each other via remote calls
Profile frontend Profile backend/profile/123
HTTP request
Profile frontend Profile backend
JSON response
{ "id": 123, "first": "Yevgeniy", "last": "Brikman"}
Most people are used to synchronous I/O when making requests between servers
The most popular frameworks typically use one-thread-per-request and blocking I/O
executeMethod blocks the thread until the response comes back
void doGet(HttpServletRequest req, HttpServletResponse res) { // Apache HttpClient HttpClient client = new HttpClient(); GetMethod method = new GetMethod("www.example.com"); // executeMethod is a blocking, synchronous call int statusCode = client.executeMethod(method); System.out.println("Response " + statusCode);}
MyServlet.java
Evented servers have one thread/process per CPU core and use non-blocking I/O
http.request is a non-blocking call: the next line executes before the response comes back
MyNodeApp.js
var callback = function(data) { console.log("Response: " + data);};
var options = { hostname: 'www.google.com', path: '/upload'}; // Non-blocking HTTP callhttp.request(options, callback); console.log('This line may execute before the callback!');
Why threaded vs. evented matters for LinkedIn
void doGet(HttpServletRequest req, HttpServletResponse res) { // Call a number of backend services to get data Profile profile = profileSvc.getProfile(); Company company = companySvc.getCompany(); Skills skills = skillsSvc.getSkills();}
MyServlet.java
Our services spend most of their time waiting for data from other services and data stores
I/O is very expensivehttp://www.eecs.berkeley.edu/~rcs/research/interactive_latency.html
In a threaded server, threads spend most of the time idle, waiting on I/O
Threading dilemma
1. Creating new threads on the fly is expensive: a. Use a thread pool
2. Too many threads in the thread pool: a. Memory overheadb. Context switching overhead
3. Too few threads in the thread pool: a. Run out of threads, latency goes upb. Sensitive to downstream latency!
Internet Load Balancer
Frontend Server
Frontend Server
Frontend Server
Backend Server
Backend Server
Backend Server
Backend Server
Backend Server
Data Store
Data Store
Data Store
Data Store
Let's say latency goes up a little here
Internet Load Balancer
Frontend Server
Frontend Server
Frontend Server
Backend Server
Backend Server
Backend Server
Backend Server
Backend Server
Data Store
Data Store
Data Store
Data Store
Causes threads to get backed up here
Internet Load Balancer
Frontend Server
Frontend Server
Frontend Server
Backend Server
Backend Server
Backend Server
Backend Server
Backend Server
Data Store
Data Store
Data Store
Data Store
Latency goes up
Internet Load Balancer
Frontend Server
Frontend Server
Frontend Server
Backend Server
Backend Server
Backend Server
Backend Server
Backend Server
Data Store
Data Store
Data Store
Data Store
Now threads get backed up here
Internet Load Balancer
Frontend Server
Frontend Server
Frontend Server
Backend Server
Backend Server
Backend Server
Backend Server
Backend Server
Data Store
Data Store
Data Store
Data Store
And here
Internet Load Balancer
Frontend Server
Frontend Server
Frontend Server
Backend Server
Backend Server
Backend Server
Backend Server
Backend Server
Data Store
Data Store
Data Store
Data Store
Here too
Internet Load Balancer
Frontend Server
Frontend Server
Frontend Server
Backend Server
Backend Server
Backend Server
Backend Server
Backend Server
Data Store
Data Store
Data Store
Data Store
And there
Internet Load Balancer
Frontend Server
Frontend Server
Frontend Server
Backend Server
Backend Server
Backend Server
Backend Server
Backend Server
Data Store
Data Store
Data Store
Data Store
And... the site is down.
This is thread pool hell
Play is built on top of Netty, so it supports non-blocking I/O
NIO benefits
1. No sensitivity to downstream slowness
2. Easy to parallelize I/O
3. Supports many concurrent and long-running connections, enabling:a. WebSocketsb. Cometc. Server-Sent Events
This talk is a brief introduction to writing asynchronous code with the Play Framework.
For each section, I will include simplified examples: first in Java and then Scala.
The world’s largest professional network
at
We've been using Play in production for more than 6 months
A few apps built on Play
Channels (frontend)
Premium Subscriptions (frontend)
Polls (frontend + backend)
REST search (internal tool)
About me
Leading the Play project as part of LinkedIn's Service Infrastructure Team. Also: hackdays, engineering blog, incubator, open source.
Outline1. A quick intro to Play
2. Basic async code
3. map and flatMap
4. Parallel and sequential
5. Errors and timeouts
6. Coming soon
Outline1. A quick intro to Play2. Basic async code
3. map and flatMap
4. Parallel and sequential
5. Errors and timeouts
6. Coming soon
Download and install Play fromhttp://www.playframework.com
> play new my-app
> play idea> play eclipse
> play run
Application layout
app → Application sources └ assets → Compiled asset sources └ controllers → Application controllers └ models → Application business layer └ views → Templatesconf → Configurations files └ application.conf → Main configuration file └ routes → Routes definitionpublic → Public assets └ stylesheets → CSS files └ javascripts → Javascript files └ images → Image filesproject → sbt configuration files └ Build.scala → Application build script └ plugins.sbt → sbt pluginslib → Unmanaged libraries dependencieslogs → Standard logs foldertarget → Generated stufftest → Unit or functional tests
Let's get a feel for Play by creating a Java Controller
public class HelloWorld extends Controller {
public static Result index() { return ok("Hello World"); } }
Controllers are Java classes with methods that return a Result, such as a 200 OK
app/controllers/HelloWorld.java
Don't worry about the use of static. Yes, Play supports IOC. Using static (and other shortcuts) lets me keep the examples simple.
GET /hello controllers.HelloWorld.index()
Expose the controller/action at a URL
conf/routes
Woohoo, hot reload!
public class HelloWorld extends Controller {
public static Result index(String name) { return ok("Hello " + name); } }
Add a parameter
app/controllers/HelloWorld.java
GET /hello controllers.HelloWorld.index( name)
Read the parameter from the query string
conf/routes
GET /hello/:name controllers.HelloWorld.index(name)
Read the parameter from the URL instead
conf/routes
public class HelloWorld extends Controller {
public static Result index(String name, int age) { return ok("Hello " + name + " you are " + age + " years old"); } }
Add another parameter, this time an int
app/controllers/HelloWorld.java
GET /hello/:name/:age controllers.HelloWorld.index(name: String, age: Int)
Add the parameter. Note the type checking!
conf/routes
@(name: String, age: Int)
<html> <head></head> <body> <img src="/assets/images/play-logo.png"/> <p> Hello <b>@name</b>, you are <b>@age</b> years old </p> </body></html>
Add a view
app/views/hello.scala.html
public class HelloWorld extends Controller {
public static Result index(String name, int age) { return ok(views.html.hello.render(name, age)); } }
Render the view from the controller
app/controllers/HelloWorld.java
Play also natively supports Scala
app/controllers/HelloWorldScala.scala
Just add a .scala file under /app and Play will compile it
object HelloWorldScala extends Controller {
def index = Action { Ok("Hello World Scala") }}
GET /scala controllers.HelloWorldScala.index()
Add it to the routes file as usual
conf/routes
http://localhost:9000/scala
Outline1. A quick intro to Play
2. Basic async code3. map and flatMap
4. Parallel and sequential
5. Errors and timeouts
6. Coming soon
Let's use Play's Web Services library (WS) to make some non-blocking HTTP calls
public class Proxy extends Controller {
public static Result index(String url) { // Non blocking HTTP call Promise<Response> responsePromise = WS.url(url).get(); // How do we turn a Promise into a Play Result? }}
app/controllers/Proxy.java
Create a new controller and use WS to make an HTTP GET
A Promise<T> will eventually contain the value T (or an error)
(Play Framework source code)
Play has a built-in subclass of Result called AsyncResult that takes a Promise<Result>
public static class AsyncResult implements Result { private final Promise<Result> promise; public AsyncResult(Promise<Result> promise) { this.promise = promise; }}
public class Proxy extends Controller { public static Result index(String url) { Promise<Response> response = WS.url(url).get();
// Transform asynchronously into a Play Result Promise<Result> result = response.map(toResult);
return async(result); }
// A function that can transform a Response into a Result private static Function<Response, Result> toResult = new Function<Response, Result>() { public Result apply(Response response) { return ok(response.getBody()).as(("text/html"); } };}
app/controllers/Proxy.java
We can use the map method to turn a Promise<Response> into a Promise<Result>
GET /proxy controllers.Proxy.index(url)
Add this endpoint to the routes file
conf/routes
http://localhost:9000/proxy?url=http://example.com
We just built a completely non-blocking proxy!
public class Proxy extends Controller { public static Result index(String url) { Logger.info("Before the HTTP call"); Promise<Response> response = WS.url(url).get(); Promise<Result> result = response.map(toResult); Logger.info("After the HTTP call");
return async(result); }
private static Function<Response, Result> toResult = new Function<Response, Result>() { public Result apply(Response response) { Logger.info("Inside the toResult function"); return ok(response.getBody()).as("text/html"); } };}
app/controllers/Proxy.java
To see that it's non-blocking, add logging
Refresh the page and the logs show the HTTP call really is non-blocking
Let's create the same Proxy in Scala
object ProxyScala extends Controller {
def index(url: String) = Action {
val future: Future[Response] = WS.url(url).get()
// How do we turn a Future into a Play Result?
}
}
app/controllers/ProxyScala.scala
Create a new controller and use WS to make an HTTP GET
A Future[T] will eventually contain the value T (or an error)
(Play Framework source code)
Play has a built-in subclass of Result called AsyncResult that takes a Future<Result>
case class AsyncResult(result: Future[Result]) extends
Result
// Convenience function to create an AsyncResult
def Async(promise: Promise[Result]) = AsyncResult(promise)
object ProxyScala extends Controller {
def index(url: String) = Action {
val future: Future[Response] = WS.url(url).get()
Async {
future.map { response =>
Ok(response.body).as("text/html")
}
}
}
}
app/controllers/ProxyScala.scala
We can use the map method to turn a Future[Response] into a Future[Result]
GET /scala/proxy controllers.ProxyScala.index(url)
Add this endpoint to the routes file
conf/routes
http://localhost:9000/scala/proxy?url=http://example.com
Outline1. A quick intro to Play
2. Basic async code
3. map and flatMap4. Parallel and sequential
5. Errors and timeouts
6. Coming soon
What is this "map" thing all about?
It's easiest to think about map with Lists.
val names = List("Jim", "Dean", "Kunal")
Let's start with a List of Strings
val names = List("Jim", "Dean", "Kunal")
def lower(str: String): String = str.toLowerCase
And a simple function that converts a String to lowercase
List.map(f) will return a new List where each element in the new List is the result of
calling f on each element of the original List
val names = List("Jim", "Dean", "Kunal")
def lower(str: String): String = str.toLowerCase
names.map(lower)
// Output: List("jim", "dean", "kunal")
Mapping the lower function over names gives us a new List where each name is lowercase
We saw map transform a List[String] into a new List[String]. Can we transform a List[X] into some other type List[Y]?
val names = List("Jim", "Dean", "Kunal")
def strlen(str: String): Int = str.length
Start with the same List, but now a new function strlen that returns the length of a String
val names = List("Jim", "Dean", "Kunal")
def strlen(str: String): Int = str.length
names.map(strlen)
// Output: List(3, 4, 5)
Mapping strlen over names returns a new List with the length of each String in names
Now we see that map can transform a List[String] into a new List[Int].
class List[A] {
def map[B](f: A => B): List[B]
}
More generally, this is map's signature
Let's look at one more example
val names = List("Jim", "Dean", "Kunal")
def explode(str: String): List[Char] = str.toCharArray.
toList
Same List, but now a new function explode that returns a List of Characters in a String
val names = List("Jim", "Dean", "Kunal")
def explode(str: String): List[Char] = str.toCharArray.
toList
names.map(explode)
// Output:
// List(List(J, i, m), List(D, e, a, n), List(K, u, n, a,
l))
If we map explode over names, we get nested Lists. But what if we want just one, flat List?
class List[A] {
def flatMap[B](f: A => List[B]): List[B]
}
We can use flatMap , which will combine (flatten) any nested Lists
val names = List("Jim", "Dean", "Kunal")
def explode(str: String): List[Char] = str.toCharArray.
toList
names.flatMap(explode)
// Output: List(J, i, m, D, e, a, n, K, u, n, a, l)
Using flatMap gives us a single List with each individual character
map and flatMap are defined on any "collection" or "container": List, Set, Map, etc
val namesSet = Set("Jim", "Dean", "Kunal")
def explode(str: String): List[Char] = str.toCharArray.
toList
namesSet.flatMap(explode)
// Output: Set(e, n, J, u, a, m, i, l, K, D)
Using flatMap on a Set
Futures and Promises are also "containers": they just happen to contain 1 item.
val future: Future[Response] = WS.url(url).get()
val future: Future[Result] = future.map { response =>
Ok(response.body).as("text/html")
}
This is why it makes sense to use map to turn a Future[Response] into a Future[Result]
The "container" class controls when the function passed to map or flatMap actually gets
applied!
Outline1. A quick intro to Play
2. Basic async code
3. map and flatMap
4. Parallel and sequential5. Errors and timeouts
6. Coming soon
Making I/O requests in parallel is essential for performance in a Service Oriented Architecture
With non-blocking I/O, parallel is the default
// These 3 HTTP requests will execute in parallel
Promise<Response> yahoo = WS.url("http://yahoo.com").get();
Promise<Response> google = WS.url("http://google.com").get();
Promise<Response> bing = WS.url("http://bing.com").get();
Let's fetch 3 websites in parallel and time them
First, define a function that makes makes an HTTP GET and returns a Promise with timing info
public Promise<Timing> timed(final String url) {
final long start = System.currentTimeMillis();
return WS.url(url).get().map(new Function<Response, Timing>() {
public Timing apply(Response response) throws Throwable {
return new Timing(url, System.currentTimeMillis() - start);
}
});
}
public class Timing {
public String url;
public long latency;
}
Next, make a controller that fires 3 requests in parallel using the timed function we just created
public class Parallel extends Controller {
public static Result index() {
final Promise<Timing> yahoo = timed("http://www.yahoo.com");
final Promise<Timing> google = timed("http://www.google.com");
final Promise<Timing> bing = timed("http://www.bing.com");
}
}
Compose the 3 Promises into a single Promise that will redeem when all 3 are done
public class Parallel extends Controller {
public static Result index() {
final Promise<Long> yahoo = timed("http://www.yahoo.com");
final Promise<Long> google = timed("http://www.google.com");
final Promise<Long> bing = timed("http://www.bing.com");
Promise<List<Timing>> all = Promise.waitAll(yahoo, google, bing);
}
}
Render the results as JSON
public class Parallel extends Controller {
public static Result index() {
final Promise<Timing> yahoo = timed("http://www.yahoo.com");
final Promise<Timing> google = timed("http://www.google.com");
final Promise<Timing> bing = timed("http://www.bing.com");
Promise<List<Timing>> all = Promise.waitAll(yahoo, google, bing);
return async(all.map(new Function<List<Timing>, Result>() {
public Result apply(List<Timing> timings) throws Throwable {
return ok(Json.toJson(timings));
}
}));
}
}
GET /parallel controllers.Parallel.index()
Add it to the routes file
conf/routes
http://localhost:9000/parallel
How about parallel requests in Scala?
Once again, define a function that makes an HTTP GET and returns a Future with timing info
def timed(url: String): Future[Timing] = {
val start = System.currentTimeMillis()
WS.url(url).get().map(_ =>
Timing(url, System.currentTimeMillis() - start)
)
}
case class Timing(url: String, latency: Long)
Next, make a controller that fires 3 requests in parallel using the timed function we just created
object ParallelScala extends Controller {
def index = Action {
val yahoo = timed("http://www.yahoo.com")
val google = timed("http://www.google.com")
val bing = timed("http://www.bing.com")
}
}
Compose the 3 Futures into a single Future that will redeem when all 3 are done
object ParallelScala extends Controller {
def index = Action {
val yahoo = timed("http://www.yahoo.com")
val google = timed("http://www.google.com")
val bing = timed("http://www.bing.com")
val all = Future.sequence(Seq(yahoo, google, bing))
}
}
Render the results as JSON
object ParallelScala extends Controller {
def index = Action {
val yahoo = timed("http://www.yahoo.com")
val google = timed("http://www.google.com")
val bing = timed("http://www.bing.com")
val all = Future.sequence(Seq(yahoo, google, bing))
Async {
all.map(timings => Ok(Json.toJson(timings)))
}
}
}
GET /scala/parallel controllers.ParallelScala.index()
Add it to the routes file
conf/routes
http://localhost:9000/scala/parallel
If parallel is the default, how do you do sequential steps that depend on each other?
Example: make a request to duckduckgo's instant answer API (step 1) and proxy an image
from the response (step 2)
First, call make a non-blocking call to duckduckgo
public class LuckyImage extends Controller {
public static Result index(String query) {
Promise<Response> duck = WS.url("http://www.duckduckgo.com")
.setQueryParameter("q", query)
.setQueryParameter("format", "json")
.get();
}
}
As a first step, we'll just proxy the response
public class LuckyImage extends Controller {
public static Result index(String query) {
Promise<Response> duck = WS.url("http://www.duckduckgo.com")
.setQueryParameter("q", query)
.setQueryParameter("format", "json")
.get();
return async(duck.map(new Function<Response, Result>() {
public Result apply(Response response) throws Throwable {
return ok(response.getBodyAsStream())
.as(response.getHeader("Content-Type"));
}
}));
}
}
GET /lucky controllers.LuckyImage.index(url)
Add it to the routes file
conf/routes
http://localhost:9000/lucky?query=linkedin
As the second step, get the image URL from the response and proxy just that.
Promise<Response> duck = // ... (same request as before)
return async(duck.flatMap(new Function<Response, Promise<Result>>() {
public Promise<Result> apply(Response response) {
String url = getImageUrlFromResponse(response);
return WS.url(url).get().map(new Function<Response, Result>() {
public Result apply(Response response) {
return ok(response.getBodyAsStream())
.as(response.getHeader("Content-Type"));
}
});
}
}));
http://localhost:9000/lucky?query=linkedin
Ok, let's try the same example in Scala
First, make the request
object LuckyImageScala extends Controller {
def index(query: String) = Action {
val duck = WS.url("http://www.duckduckgo.com")
.withQueryString("q" -> query, "format" -> "json").get()
}
}
Then extract the image URL and proxy it
object LuckyImageScala extends Controller {
def index(query: String) = Action {
val duck = WS.url("http://www.duckduckgo.com")
.withQueryString("q" -> query, "format" -> "json").get()
Async {
duck.flatMap { response =>
val url = getImageUrlFromResponse(response)
WS.url(url).get().map { r =>
Ok(r.getAHCResponse.getResponseBodyAsBytes)
.as(r.getAHCResponse.getHeader("Content-Type"))
}
}
}
}
}
GET /scala/lucky controllers.LuckyImageScala.index(url)
Add it to the routes file
conf/routes
http://localhost:9000/lucky?query=play+framework
In both Java and Scala, you order async actions sequentially by nesting map and flatMap calls.
Many sequential steps will lead to lots of nesting.
step1.flatMap(new Function<Response, Promise<Result>>() {
public Promise<Result> apply(Response response1) {
step2.flatMap(new Function<Response, Promise<Result>>() {
public Promise<Result> apply(Response response2) {
step3.flatMap(new Function<Response, Promise<Result>>() {
public Promise<Result> apply(Response response3) {
// etc
}
}
}
});
}
});
This is "callback hell"
ParSeq
https://github.com/linkedin/parseq
ParSeq is a framework that makes it easier to write asynchronous code in Java
Wrap asynchronous work in ParSeq Task objects,which are similar to Promises and Futures
Task<Response> yahoo = Tasks.wrap(WS.url("http://www.yahoo.com"))
Task<Response> google = Tasks.wrap(WS.url("http://www.google.com"))
Task<Response> bing = Tasks.wrap(WS.url("http://www.bing.com"))
Use Tasks.par to compose tasks in parallel
Task<Response> yahoo = Tasks.wrap(WS.url("http://www.yahoo.com"))
Task<Response> google = Tasks.wrap(WS.url("http://www.google.com"))
Task<Response> bing = Tasks.wrap(WS.url("http://www.bing.com"))
// Create a new Task that will run all 3 tasks above at the same time
// and redeem when they are all done
Task<?> parallel = Tasks.par(yahoo, google, bing)
Use Tasks.seq to compose tasks sequentially
Task<Response> step1 = new Task() { ... }
Task<Response> step2 = new Task() { ... }
Task<Response> step3 = new Task() { ... }
// Create a new Task that will run the tasks above one at a time,
// in the order specified, and complete with the return value of the
// last one
Task<Response> sequential = Tasks.seq(task1, task2, task3)
ParSeq makes async code declarative and easier to reason about: you can read it top to bottom!
Task<Result> complex = Tasks.seq(
Tasks.par(profileTask, companyTask, skillsTask),
Tasks.par(recommendedJobsTask, wvmxTask),
Tasks.par(hydrateImagesTask, hydrateJobsTask, hydrateSkillsTask)
Tasks.seq(assemblePageTask, fireTrackingTask)
)
We'll soon be open sourcing a plugin soon to make it easy to use ParSeq in Play.
Sequence Comprehensions
Syntactic sugar built into Scala. Translates into map and flatMap calls without the nesting.
Instead of this...
aFuture.flatMap { a =>
bFuture.flatMap { b =>
cFuture.flatMap { c =>
dFuture.map { d =>
// Build a result using a, b, c, d
}
}
}
}
Use this. Note that this syntax works for any object with map and flatMap methods.
for {
a <- aFuture
b <- bFuture
c <- cFuture
d <- dFuture
} yield {
// Build a result using a, b, c, d
}
Sequential async I/O example. Note that each step can refer to previous ones.
for {
a <- WS.url(...).get()
b <- WS.url(a).get()
c <- WS.url(a + b).get()
d <- WS.url(a + b + c).get()
} yield {
// Build a result using a, b, c, d
}
Parallel async I/O example. Only difference is that the async calls are outside the for statement.
val futureA = WS.url(...)
val futureB = WS.url(...)
val futureC = WS.url(...)
val futureD = WS.url(...)
for {
a <- futureA
b <- futureB
c <- futureC
d <- futureD
} yield {
// Build a result using a, b, c, d
}
Sequence comprehensions provide a clean and consistent API for async code: you can read it
top to bottom!
Outline1. A quick intro to Play
2. Basic async code
3. map and flatMap
4. Parallel and sequential
5. Errors and timeouts6. Coming soon
With a single server, the odds of hitting an error are relatively low
In a distributed system with thousands of servers, the odds that you hit an error are very high
Internet Load Balancer
Profile frontend
Company frontend
Recruiter frontend
Profile backend
Search backend
Company backend
Recruiter backend
Ads backend
Data Store
Data Store
Data Store
Data Store
Even if a single server is up 99.999% of the time, with 1000 servers, the odds that one is
down are 1 - 0.999991000 = ~1%
Here is how to make your async code more resilient to errors and slow performance
We can use the recover method on a Promise to specify how to handle errors
public class Errors extends Controller {
public static Result index(String url) {
F.Promise<WS.Response> promise = WS.url(url).get();
return async(promise.map(new F.Function<WS.Response, Result>() {
public Result apply(WS.Response response) throws Throwable {
return ok("Got a response!");
}
}).recover(new F.Function<Throwable, Result>() {
public Result apply(Throwable throwable) throws Throwable {
return internalServerError("Got an exception: " + throwable);
}
}));
}
}
There is an analogous recover method on Scala Futures as well
object ErrorsScala extends Controller {
def index(url: String) = Action {
Async {
WS.url(url).get().map { response =>
Ok("Got a response: " + response.status)
}.recover { case t: Throwable =>
InternalServerError("Got an exception: " + t)
}
}
}
}
GET /errors controllers.Errors.index(url)GET /scala/errors controllers.ErrorsScala.index(url)
Add to the routes file
conf/routes
http://localhost:9000/errors?url=http://www.example.com
http://localhost:9000/errors?url=http://www.not-a-real-url.com
If some of the data you fetch isn't required to render the page, you can use an Option
pattern
Create a helper method: on success, return Some<T>. On failure, log the error, return None.
public static <T> Promise<Option<T>> optional(Promise<T> promise) {
return promise.map(new Function<T, Option<T>>() {
public Option<T> apply(T value) throws Throwable {
if (value == null) {
return Option.None();
}
return Option.Some(value);
}
}).recover(new Function<Throwable, Option<T>>() {
public Option<T> apply(Throwable t) throws Throwable {
Logger.error("Hit an error", t);
return Option.None();
}
});
}
Wrap Promises with optional and inside of map, use isDefined to see if you have a value
public static Result index(String url) {
Promise<Option<Response>> promise = optional(WS.url(url).get());
return async(promise.map(new Function<Option<Response>, Result>() {
public Result apply(Option<Response> responseOpt){
if (responseOpt.isDefined()) {
Response response = responseOpt.get();
// Use the response to build the page
} else {
// Build the page without the response
}
}
}));
}
The same pattern is even prettier in Scala, as Option is a first-class citizen of the language
Reusable helper method to convert Future[T] to Future[Option[T]]
def optional[T](future: Future[T]): Future[Option[T]] = {
future.map(Option.apply).recover { case t: Throwable =>
Logger.error("Hit an error", t)
None
}
}
Wrap Futures with optional and use pattern matching, comprehensions, etc within map
object OptionExampleScala extends Controller {
def index(url: String) = Action {
Async {
optional(WS.url(url).get()).map {
case Some(response) => // Use the response to build the page
case _ => // Build the page without the response
}
}
}
}
Sometimes, waiting too long for data is worse than not showing that data at all
You can create a Promise that will be redeemed with someValue after the specified timeout
Promise.timeout(someValue, 500, TimeUnit.MILLISECONDS)
Compose two Promises using or: the result takes on the value of the first one to complete
Promise<Response> response = WS.url(url).get();
Promise<Either<Object, Response>> withTimeout =
Promise.timeout(null, timeout, TimeUnit.MILLISECONDS).or(response);
If right is defined, you got a value in time; otherwise, it must have timed out first.
Promise<Response> response = WS.url(url).get();
Promise<Either<Object, Response>> withTimeout =
Promise.timeout(null, timeout, TimeUnit.MILLISECONDS).or(response);
withTimeout.map(new Function<Either<Object, Response>, Result>() {
public Result apply(Either<Object, Response> either) {
if (either.right.isDefined()) {
Response response = either.right.get();
// Use the response to build the page
} else {
// Hit a timeout, build the page without the response
}
}
});
The Scala version
import play.api.libs.concurrent._
object TimeoutExampleScala extends Controller {
def index(url: String, timeout: Long) = Action {
val timeout = Promise.timeout(null, timeout, MILLISECONDS)
val future = timeout.either(WS.url(url).get())
future.map {
case Right(response) => // Use the response to build the page
case _ => // Hit a timeout, build the page without the response
}
}
}
Outline1. A quick intro to Play
2. Basic async code
3. map and flatMap
4. Parallel and sequential
5. Errors and timeouts
6. Coming soon
play-async-plugin
We'll be open sourcing this plugin soon
It is a collection of async utilities, including...
ParSeq integration for Play to make asynchronous Java code easier
Task<Response> yahoo = Tasks.wrap(WS.url("http://www.yahoo.com"))
Task<Response> google = Tasks.wrap(WS.url("http://www.google.com"))
Task<Response> bing = Tasks.wrap(WS.url("http://www.bing.com"))
// Create a new Task that will run the tasks above one at a time,
// in the order specified, and complete with the return value of the
// last one
Task<Response> sequential = Tasks.seq(yahoo, google, bing)
Config-driven SLAs (timeouts) for any async I/O
sla.plugin.slas = [
{
resources: ["/profile", "/companies"]
timeout: "2s"
},
{
resources: ["/pymk", "/skills/*"],
timeout: "500ms"
}
]
In-browser visualization of all async requests for a page, including timing, responses, and errors
We're just getting started with Play! We'll be sharing more as we go.
LinkedIn Engineering Bloghttp://engineering.linkedin.com
@LinkedInEng on Twitterhttps://twitter.com/LinkedInEng
Thank you!