A presentation at Twitter's official developer conference, Chirp, about why we use the Scala programming language and how we build services in it. Provides a tour of a number of libraries and tools, both developed at Twitter and otherwise.

2. The Why and How
of Scala at Twitter
Alex Payne (@al3x)
Twitter Infrastructure

3. Who’s this guy?
•Working at Twitter since
2007, before it was even a
company.
•Spent a couple years on the
API.
•Co-authored Programming
Scala (O’Reilly, 2009).
•Into programming
languages, scaling stuff.

4. Part I:
Why Scala?

5. So, like, Ruby or Scala?
•Both!
•Ruby mostly on the
frontend.
•Scala mostly on the
backend.
•Thrift and data stores to
connect the two.

6. Elevator Pitch
• It’s fun.
• It’s fast.
• It’s runs on a great virtual machine (JVM).
• It’s got an awesome community.
• It can borrow from Java.

7. No, seriously, why?
• A rich static type system that gets out of your
way when you don’t need it, is awesome when
you do.
• Flexible syntax makes it easy to write
readable, maintainable code.
• Traits for cross-cutting modularity.
• Lots of OOP goodness.

8. I’m not sold yet.
• How about the choice between immutable and
mutable variables?
• Powerful functional programming: mapping,
filtering, folding, currying, so much more.
• Lazy values.
• Pattern matching.
• XML literals, and clean syntax for working
with XML documents built right in!

9. What about concurrency?
• You can do Actor concurrency (message
passing), kinda like Erlang.
• Or, use threads.
• Or, use all the java.util.concurrent tools.
• Or, use other JVM concurrency frameworks
(ex: Netty, Apache Mina).

10. Basically,
it’s the future.

12. Part II:
How do you guys
do Scala?

13. We build services.
• Isolated components, can swap them out.
• Talk to the rest of the system via Thrift (for
now, maybe Avro in the future).
• Independently tested for correctness, load.
• Can have custom operational properties.

14. Scala Services at Twitter
• Kestrel: queuing.
• Flock (and Gizzard): social graph store.
• Hawkwind: people search.
• Hosebird: streaming API.
• more in the works all the time...

15. Thrift Example
struct Results {
1: list<i64> people
2: string suggestion
3: i32 processingTime /* milliseconds */
4: list<i32> timings
5: i32 totalResults
}
service NameSearch {
Results find(1: string name, 2: i32 maxResults, 3: bool
wantSuggestion)
Results find_with_ranking(1: string name, 2: i32 maxResults, 3: bool
wantSuggestion, 4: Ranker ranking)
}

16. We build libraries.
• Reusable chunks of code that we can share
between projects.
• We open source them.
• We try to keep the “NIH” to a minimum, but
we also have very particular requirements.

17. Ostrich
• Gather stats from inside your running process.
• Counters, gauges, and timings.
• Share stats many ways: JMX, JSON-over-
HTTP, plain text Telnet-style socket, log files.

18. Ostrich Examples
Stats.time(“find-users”) {
users.find(queryString)
}
Stats.incr(“write-errors”)
Stats.makeGauge("database-lag") {
dbConnection.getLagInMillis()
}

19. Configgy
• Configuration files and logging.
• Flexible file format offers includes, more.
• Inheritance, variable substitution.
• Tunable logging, Scribe support.
• Subscription API: push and validate
configuration changes.
• Ruby support, Emacs mode.

20. Configgy Examples
hostname = “service001”
port = 8080
use_admin_interface = true
log {
filename = “my-service.log”
level = “error”
roll = “hourly”
}

21. Configgy Examples
Configgy.configure(“/etc/my-service.conf”)
val config = Configgy.config
val port = config.getInt(“port”, 8080)
val hostname = config.getString(“hostname”)
log.info(“service started”)
log.debug(“running on port %d”, port)

22. xrayspecs
• A set of extensions to the fantastic Specs BDD
test framework.
• Handles testing concurrency, time, creating
temporary folders.
• The concurrency features have been rolled into
the main distribution of Specs!

23. xrayspecs Examples
“response arrives from server” in {
get(“/example”) must eventually(notBe(null))
}
“time should stop” in {
Time.freeze()
val nowSnapshot = Time.now
Thread.sleep(30)
Time.now mustEqual nowSnapshot
}

24. scala-json
• A cleaned-up version of the official Scala JSON
codec.
• Makes clever use of parser combinators – a
good way to learn about them.
• Heavily tested, fixes a bunch of edge cases.

25. JSON Examples
val myJsonString = """
{"key": "value", "1": 2, "3": 4,
"myList": [5, 6, 7]
"""
Json.parse(myJsonString)
Json.build(List("user_id", 666))

26. Other Twitter Libraries
• Naggati: build protocols for Apache Mina.
• Smile: a memcached client that uses Actors.
• Querulous: a nice database client.
• Jackhammer: a load testing framework
(coming soon).
• probably stuff I'm leaving out...

27. Stuff We Use
• There's great open source code in the Scala
community.
• We try to use and contribute back to third-
party projects.
• Follow @implicit_ly for new Scala releases.
• Also subscribe to Repopular Scala.

28. sbt – the simple build tool
• Scala’s answer to Ant and Maven.
• Sets up new projects.
• Maintains project configuration, build tasks,
and dependencies in pure Scala. Totally open-
ended.
• Interactive console.
• Will run tasks as soon as files in your project
change – automatically compile and run tests!

29. specs
• As aforementioned: great way to do BDD
testing.
• Set up pre- and post-conditions for
individual tests, suites, etc.
• Extremely flexible and extensible.
• Great, responsive maintainer.
• Supports mocking (we like Mockito).

30. The IDE Question
• We've had the best luck with IntelliJ IDEA,
but it's still pretty rough.
• Most of us use a plain text editor like Emacs,
VIM, or TextMate.
• Combined with sbt, it's actually a really nice
workflow!

31. Questions!
Thanks for listening!