Discussion about making games on Geoloqi, demoing MapAttack

1. Building MapAttack: A
real-time geolocation
game
Kyle Drake

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What is Geoloqi?
geoloqi.com

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Real-world solutions
for thousands around the globe

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Real-Time Location Tracking
Real-World Interactive Experiences

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Personal Location

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Location-Based Notes

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YOUR GPS GETS WEIRD.
WE HELP FIX THAT.

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Real-Time Applications

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First Hackathon Attempt
Layer in Geoloqi
Updates to MapAttack server
via HTTP REST API
Processing through Geoloqi’s
persistent store
Finished in a weekend
A lot of fun!

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There were some kinks
Used an REST HTTP service for
APNS (worked, but not “real-time”)
Server was getting backed up
(updates were not async)

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MapAttack Server Issues
Blocking IO (requests to Geoloqi API held
everything up)
Lots of concurrent traffic
Events had to be broadcast to all phones/
clients in the game synchronously

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HOW WE
DEALT WITH
IT

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A key-value store, and so much more
A great implementation of PUBLISH/SUBSCRIBE
So simple, you can actually understand it
Very fast and reliable
Robust library support

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HOW WE USE NODE JS
• Phones:
Custom binary protocol over UDP
• Web Browsers:
Web Sockets via Socket.IO

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Socket.IO is awesome
Adapter Pattern for realtime
Web Sockets, Flash, Long Polling!
One interface for everything
Easy to implement: ~100 LOC

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Geoloqi API
ASYNC FTW!
Delayed updates when possible
Messages queues: Beanstalk
Workers pick tasks off the stack
Process data outside of the persistent store
Simpler than AMQP

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MapAttack Server
(or: How to make Ruby ROFLscale)
MRI Ruby has a global interpreter lock
But MRI Ruby does not block on IO
JRuby and Rubinius 2: Native Threads
And it has a reactor pattern, just like Node JS!

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The Reactor Pattern
“The reactor design pattern is a concurrent
programming pattern for handling service
requests delivered concurrently to a service
handler by one or more inputs” - Wikipedia
My simplest description: Takes your blocking IO
operation, shoves it into its own kernel thread
behind the scenes, uses Unix kernel magic to make
it rejoin the reactor queue when it’s ready.
Linux: epoll(4)
BSD: kqueue/kevent

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Blocking IO a UNIVERSAL problem
All programming languages have trouble with it
The Reactor pattern is a tool to resolve it
Most languages have the Reactor pattern!
JavaScript Node.js
Python Twisted
Ruby EventMachine (libem, C)
Java JBoss_Netty
(wait, what? I thought Java had good threading..)
PHP None yet (perhaps ever)

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Sinatra::Synchrony
kyledrake.net/sinatra-synchrony
Implements EventMachine with Fibers
The result: NO CALLBACKS!
< 100 LOC
Only coding change is to use EM libs and fibers
WOW, THAT WAS EASY.

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Sinatra::Synchrony

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Let’s Talk Performance.

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Make the relevant data
stay outside of the slow
persistence store.

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If you’re trying to solve a problem by
ROFLscaling your persistent store,
you’re doing it wrong.

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Examples of doing it wrong
“Let’s rewrite everything to use TrendDB”
Using EC2 for a single-master DB “because it scales”
Buying something from Oracle
“Ruby/PHP/JS is too slow for this, let’s rewrite it in
TrendLang”
Most NoSQL solutions have dark secrets you don’t
know about. Global write locks, single write master, et
cetera

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If you must speed up your persistent
store, here’s my practical advice.

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Real Hardware FTW?
Single master database? Get a real server! Really!
Cloud is only as fast as the fastest available HDD
EBS performance is not great, even in RAID0 stripe
See orion.heroku.com/past/2009/7/29/io_performance_on_ebs
and perfcap.blogspot.com/2011/03/understanding-and-using-amazon-ebs.html
and blog.dt.org/index.php/2010/06/amazon-ec2-io-performance-local-emphemeral-disks-vs-raid0-
striped-ebs-volumes/
and endevver.com/2010/03/cost-analysis-of-an-amazon-ec2-deployment.html
and mysqlperformanceblog.com/2011/02/21/death-match-ebs-versus-ssd-price-performance-and-
qos
and google.com/search?q=heroku+ebs+performance
High end Xeon, 32GB ECC, fast 220GB SSD: ~$2K

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Real Hardware FTW?
The paradigm is diversifying, and the reason is SSD.
Say hello to the Fusion-io ioDrive Octal.
PCIe x16 slot
5.12TB
6.0 GB/s read
4.4 GB/s write
1.19 MILLION IOPS
Cost: $100,000 (plus $10 S&H).
It’s a steal at this price.. but it will get cheaper.

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Real Hardware FTW?
$500 PCIe SSD drives:
220GB
>100,000 IOPS
~700MB/s R/W
15,000 RPM SAS drives:
2TB+
~175-210 IOPS
<150MB/s R/W

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Long Term
Multi-master experiment (Brewer’s CAP)
Riak is my current favorite
Cloud companies providing real hardware
performance

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In Summary

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Geo-location games
are FUN!

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Use the Geoloqi API to make
geolocation games! We did the
hard work for you.

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MapAttack is open source!
github.com/geoloqi/MapAttack

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Other uses of Geoloqi

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Thanks!