I was approached by a betting/gambling development company who potentially needed a middleware building that would pull from an existing gambling web service and basically transmit to connected iPhone clients the changes from the web service. At first, the obvious answer might be to create another REST web service that the iPhone clients could just ping for changes. However, one of the devs explained that this wouldn't be fast enough, or scale - they'd need changes to be transmitted as soon as possible, as the app would be a real-time betting app and there'd be thousands of connections to the server.

His solution involved hooking together Ratchet, Redis, Silex and Predis-async to create this sample tool for handling the websocket requests. it uses the "pubsub" mechanism of Redis to push the updates out to listening clients.

There is a lot of argument whether Redis or Memcache is better, though as the benchmarks show they perform pretty much on par with each other for basic operations. Redis has more features than Memcache has, such as in-memory and disk persistence, atomic commands and transactions, and not logging every change to disk but rather server-side data structures instead. In this article we'll take a look at some of the basic but powerful commands that Redis has to offer using the Predis library.

He helps you get a local redis server up and running and includes a link to the repository for the latest version of the Predis library. Some sample code is provided showing how to connect to the server, push data into a key/value combination, get the value back out, increment it and check to see if it exists. He also talks about some of the available data types Redis provides and a few other more complex operations you can perform on things other than strings.

Cal's "three questions" for Justin are around his work with Redis and the Utah open source community and conference:

• For those that don't know, can you tell us what Redis is and why did you choose it over other options?
• Can you tell us why "middle-scale" sites are different and what challenges do they uniquely face?
• As a developer how has getting involved in organizing helped you both personally and professionally?

You can listen to this latest episode through the in-page player, by downloading the mp3 or by subscribing to their feed.

Sometimes there are situations when you want to parallel process things. Other times you might have a list of tasks to accomplish, and you don't want to make the user wait after pressing a button. This is where "Workers" can come in. They are independent scripts that run along side of your application, performing tasks, or "jobs."

Solo is a very basic Perl script that ensures only one process of a type is running at once. Using this and a PHP library called predis, he shows how to set up workers and add items to your processing queue. The workers themselves run on a cron job and connect to the queue server to see what they need to do. He also throws in some "bells and whistles" - extras that can enhance your worker system: queue monitoring, version numbering and killing workers based on a hash value.

His code examples are posted on his github account and a screencast is included in the post to show the system in action.

We wanted not only for people to be able to visit a profile and see a score, which is easy to generate a score on demand. We wanted our users to be able to browse other profiles sorted by their score with them. This requires us to pre-generate and store these scores, and then later query them. [...] I believe we could have bent MySQL to our will and got it to work, but it would be at a high cost of server power, and that cost wouldn't scale well with our revenue stream.

He talks about some of the other options they sorted through including NoSQL databases or building something completely in-house. In the end, though, they decided that Redis was more of what they needed. He prefaces talking about their configuration with some of the limitations of the tool and then moves into their setup and statistics on its use (complete with pretty graphs). He points to predis as their Redis client of choice for PHP.

PHP Warning: PHP Startup: Unable to load dynamic library '/[...]/redis.so' - dlopen(/[...]/redis.so, 9): no suitable image found. Did find: /[...]/redis.so: mach-o, but wrong architecture in Unknown on line 0

He fixed the issue with the help of a bash script (source included) that sets up the right environment to build PHP on the OSX platform. Then the normal make, phpize, etc process can be done on the PECL extension and have it compile correctly.

Two out of [the list of libraries] caught my particular attention: Rediska due to it's impressive Zend Framework integration and phpredis as it's a native PHP extension written in C and therefore supposed to be blazingly faster than vanilla PHP client libraries. The following blog post will show how to install and configure the aforementioned, native PHP extension on a Mac OS X system.

You'll need to have the redis server already installed (via MacPorts or some other method) but with that and the necessary libraries in place installing the extension is a simple "git clone" away. He even includes the location of a gist (code snippet) to help you test it out.

NoSQL is all the rage for Web developers who are tired of building complex SQL. Redis, a NoSQL database server much like Cassandra or MongoDB, provides a powerful and speedy alternative to relational database servers for PHP developers. Redis is similar to Memcached in terms of speed, but the data isn't volatile. That means that when your server reboots, your Redis data will still be there. You can back it up too.

Installing the server for Redis is easy (if you use a package management system) and getting up and running with PHP is as easy as using one of the PHP connection libraries out there like Rediska. In his example he shows one of the most basic operations - storing string values, appending to them and pulling them back out based on their unique key.

Don't know Redis? Think Memcache, with support for for lists, and disk-based storage. You can use Redis as a database, queue, cache server or all of those combined. [...] Redis keeps the entire dataset in memory, so it's still crazy fast: 110000 SETs/second, 81000 GETs/second. Good enough for to you? [...] Yes, you can store (serialized) arrays in Memcache. But every time you change 1 element, you'd have to invalidate & overwrite the entire array.

He talks about installing the redis server (a simple task if you use the package management tool for your linux release) and some simple code to push data into the caching server for keys, lists, sets and how to pull the information back out sorted.