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Productivity and Performance at Scale
You are a developer using Java to
build web services.
This is your life:
Waiting. [1]
tail -f logs/catalina.out
XML soup
"Convenient proxy factory bean superclass for proxy
factory beans that create only singletons." [2]
Thread pool usage
Latency
Thread pool hell
The Play Framework at LinkedIn
There is a better way.
Ruby on Rails!
Nah, just kidding. We have real work to do.
A modern web framework for Java and Scala
The world’s largest professional network
at
We've been using Play in production for
more than 6 months [3]
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.
This talk is the story of building web services
at massive scale with Java and Scala...
... while maintaining performance,
reliability, and developer
productivity.
Outline
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
Outline
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
Download and install Play from
http://www.playframework.com
> play new my-app
> play idea
> play eclipse
> play run
http://localhost:9000
Application layout
app → Application sources
└ assets → Compiled asset sources
└ controllers → Application controllers
└ models → Application business layer
└ views → Templates
conf → Configurations files
└ application.conf → Main configuration file
└ routes → Routes definition
public → Public assets
└ stylesheets → CSS files
└ javascripts → Javascript files
└ images → Image files
project → sbt configuration files
└ Build.scala → Application build script
└ plugins.sbt → sbt plugins
lib → Unmanaged libraries
dependencies
logs → Standard logs folder
target → Generated stuff
test → Unit or functional tests
Outline
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
public class HelloWorld extends Controller {
public static Result index() {
return ok("Hello World");
}
}
Create a new controller and action
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
Now, restart the server.
Nah, just kidding. Refresh the page.
Woohoo, hot reload!
http://localhost:9000/hello
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
http://localhost:9000/hello?name=Jim
GET /hello/:name controllers.HelloWorld.index(name)
Read the parameter from the URL instead
conf/routes
http://localhost:9000/hello/Jim
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
http://localhost:9000/hello/Jim/28
@(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
http://localhost:9000/hello/Jim/28
location = "JaxConf"
How about some config?
app/conf/application.conf
public class HelloWorld extends Controller {
public static Result index(String name, int age) {
String location = getConfig().getString("location");
return ok(views.html.hello.render(name, age,
location));
}
private static Configuration getConfig() {
return Play.application().configuration();
}
}
Read the config and pass it to the view
app/controllers/HelloWorld.java
@(name: String, age: Int, location: String)
<html>
<head></head>
<body>
<img src="/assets/images/play-logo.png"/>
<p>
Hello <b>@name</b>, you are <b>@age</b> years old
and you are at <b>@location</b>
</p>
</body>
</html>
Update the view
app/views/hello.scala.html
Refresh the page. Config hot reloads too!
Outline
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
In dev mode, Play shows error messages
right in the browser.
Parameter type checking
A helpful 404 page
Compile errors show problematic source code
in the browser
Views are compiled as well
The routes file too
Outline
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
Most people are used to threaded servers
Threaded servers assign one thread per
request and use blocking I/O
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 are gaining popularity
Evented servers have one thread/process per
CPU core and use non-blocking I/O
MyNodeApp.js
var callback = function(data) {
console.log("Response: " + data);
};
var options = {
hostname: 'www.google.com',
path: '/upload'
};
// Non-blocking HTTP call
http.request(options, callback);
console.log('This line may execute before the callback!');
Why threaded vs. evented matters for
LinkedIn
LinkedIn uses a Service Oriented Architecture
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
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 expensive [4]
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 overhead
b. Context switching overhead
3. Too few threads in the thread pool:
a. Run out of threads, latency goes up
b. 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 [5]
Play is built on top of Netty, so it supports non-
blocking I/O [6]
NIO benefits
1. No sensitivity to downstream slowness
2. Easy to parallelize I/O
3. Supports many concurrent and long-running
connections, enabling:
a. WebSockets
b. Comet
c. Server-Sent Events
Outline
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
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
Use Play's built in WS library to make a non-
blocking HTTP call
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) {
// Non blocking HTTP call
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)
Let's 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, let's add logging
Refresh the page and the logs show the
HTTP call really is non-blocking
NIO makes parallel requests easy.
Let's try it.
class Timing {
public String url;
public long latency;
public Timing(String url, long latency) {
this.url = url;
this.latency = latency;
}
// Fire an HTTP request and record how long it took
public static Promise<Timing> timedRequest(final String url) {
final long start = System.currentTimeMillis();
Promise<Response> res = WS.url(url).get();
return res.map(new Function<Response, Timing>() {
public Timing apply(Response response) {
long latency = System.currentTimeMillis() - start;
return new Timing(url, latency);
}
});
}
}
app/models/Timing.java
First, define a class that times an HTTP request
public class Parallel extends Controller {
public static Result index() {
// A Promise that will redeem when the 3 parallel
// HTTP requests are done
Promise<List<Timing>> all = Promise.waitAll(
Timing.timedRequest("http://www.yahoo.com"),
Timing.timedRequest("http://www.google.com"),
Timing.timedRequest("http://www.bing.com")
);
// Asynchronously transform timings into a JSON response
return async(all.map(new Function<List<Timing>, Result>() {
public Result apply(List<Timing> timings) {
return ok(Json.toJson(timings));
}
}));
}
}
app/controllers/Parallel.java
Next, add a controller that fetches 3 URLs in
parallel and returns the timings as JSON
GET /parallel controllers.Parallel.index()
Add it to the routes file
conf/routes
http://localhost:9000/parallel
Outline
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
Play has native support for 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
Play/Scala: the good parts
Sequential async calls
// 2 sequential async calls
for {
foo <- WS.url(url1).get()
bar <- WS.url(buildUrl(foo)).get()
} yield {
Ok(...)
}
API is more concise, expressive, &
composable, especially for async code.
Sequential async calls
// 2 parallel async calls
val fooFuture = WS.url(url1).get()
val barFuture = WS.url(url2).get()
for {
foo <- fooFuture
bar <- barFuture
} yield {
Ok(...)
}
Interactive console with full classpath of your app
Play is Scala at its core: main libraries,
routes, templates, SBT, etc [7]
Play/Scala: the less good parts
Simple Build Tool: Play's build system. Very
powerful, but very steep learning curve.
project/Build.scala
val settings = Seq(
bootPath <<= target( _ / "boot" ),
buildDir <<= baseDirectory(_ / ".." / "build"),
srcDir <<= baseDirectory(_/ ".." / "src"),
enableConfigCompile := true,
fabrics <++= Seq("EI", "EI2")
)
Abandon all hope, ye who enter here
without knowing Scala.
project/Build.scala
fabrics <++= Seq("EI", "EI2")
WTF is <++=? Some kind of fish bones?
How do I google that?
Outline
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
Is Play web scale? [8]
Scalability can be measured along
many dimensions
Raw
horsepower
Concurrent
horsepower
Single
developer
Multiple
developers
Raw horsepower: theoretical maximum
performance for the server in ideal
conditions. A measure of language and
framework overhead.
Concurrent horsepower: performance with
many users, I/O, and more real-world
scenarios. A measure of the framework's
approach to concurrency.
Single developer: how easy it is to get
started, how quickly a single developer can
build things. A measure of the framework's
raw productivity and tooling.
Multiple developers: how the framework
tolerates many developers working
concurrently over many years. A measure of
code rot and maintainability.
Here is how I'd rate some of the
frameworks I've used. YMMV.
● Pros
○ Good raw throughput (qps, latency)
○ Type safety reduces code rot
● Cons
○ Not developer friendly. Getting things done takes
forever.
○ Threaded, synchronous approach difficult to scale
for lots of I/O in a SOA environment.
MVC
Raw
horsepower
Concurrent
horsepower
Single
developer
Multiple
developers
SpringMVC
● Pros
○ Set the bar for developer productivity; all other
frameworks are still trying to catch up.
● Cons
○ Ruby is slow
○ Ruby doesn't have real multithreading nor a great
evented framework
○ Dynamic language makes it tougher to maintain a
large codebase
Raw
horsepower
Concurrent
horsepower
Single
developer
Multiple
developers
Rails
● Pros
○ v8 engine is pretty fast for raw throughput
○ Non-blocking I/O at the core makes concurrency
easy
○ Strong open source community and lightning fast
startup time makes it easy to get things done quickly
● Cons
○ Dynamic language makes it tougher to maintain a
large codebase
○ Lots of immature libraries that constantly make
backwards incompatible changes
Raw
horsepower
Concurrent
horsepower
Single
developer
Multiple
developers
Node.js
● Pros
○ Fast for raw throughput
○ Non-blocking I/O at the core makes concurrency
easy
○ Hot reload makes it possible to get things done
quickly
○ Strong type safety throughout reduces code rot
● Cons
○ Even with hot reload, a compiled statically typed
language isn't quite as fast as an interpreted
dynamically typed language
Raw
horsepower
Concurrent
horsepower
Single
developer
Multiple
developers
Play
Outline
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
Play is open source [7]
LinkedIn is contributing
Very active google group (mailing list) [9]
StackOverflow tag [10]
Open source modules and plugins [11]
We've open sourced a few of our plugins,
with many more on the way [12]
Commercial support from Typesafe [13]
Recap
1. Getting started with Play
2. Make a change and reload
3. Error handling
4. Threaded vs. evented
5. Non-blocking I/O
6. Scala
7. Performance
8. Community
That's the story of Play at LinkedIn so far...
But we're just getting started.
LinkedIn Engineering Blog [14]
@LinkedInEng on twitter [15]
Thank you!
References
1. http://zeroturnaround.com/java-ee-productivity-report-2011/
2. http://static.springsource.org/spring/docs/2.5.x/api/org/springframework/...
3. http://engineering.linkedin.com/play/play-framework-linkedin
4. http://www.eecs.berkeley.edu/~rcs/research/interactive_latency.html
5. http://engineering.linkedin.com/play/play-framework-async-io-without...
6. http://netty.io/
7. https://github.com/playframework/Play20
8. http://mongodb-is-web-scale.com/
9. https://groups.google.com/forum/?fromgroups#!forum/play-framework
10. http://stackoverflow.com/tags/playframework
11. http://www.playframework.com/documentation/2.1.1/Modules
12. https://github.com/linkedin
13. http://typesafe.com/platform/runtime/playframework
14. http://engineering.linkedin.com/
15. https://twitter.com/LinkedInEng

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