From my perspective, one of the best parts of being a Web developer is the instant gratification. You write some code, and within minutes, it can be used by people around the world, all accessing your server via a Web browser. The rapidity with which you can go from an idea to development to deployment to actual users benefiting from (and reacting to) your work is, in my experience, highly motivating.
Users also enjoy the speed with which new developments are deployed. In the world of Web applications, users no longer need to consider, download or install the "latest version" of a program; when they load a page into their browser, they automatically get the latest version. Indeed, users have come to expect that new features will be rolled out on a regular basis. A Web application that fails to change and improve over time quickly will lose ground in users' eyes.
Another factor that users consider is the speed with which a Web application responds to their clicks. We are increasingly spoiled by the likes of Amazon and Google, which not only have many thousands of servers at their disposal, but which also tune their applications and servers for the maximum possible response time. We measure the speed of our Web applications in milliseconds, not in seconds, and in just the past few years, we have reached the point when taking even one second to respond to a user is increasingly unacceptable.
The drive to provide ever-greater speed to users has led to a number of techniques that reduce the delays they encounter. One of the simplest is that of a delayed job. Instead of trying to do everything within the span of a single user request, put some of it aside until later.
For example, let's say you are working on a Web application that implements an address book and calendar. If a user asks to see all of his or her appointments for the coming week, you almost certainly could display them right away. But if a user asks to see all appointments during the coming year, it might take some time to retrieve that from the database, format it into HTML and then send it to the user's browser.
Sometimes, you can't divide jobs in this way. For example, let's say that when you add a new appointment to your calendar, you would like the system to send e-mail to each of the participants, indicating that they should add the meeting to their calendars. Sending e-mail doesn't take a long time, but it does require some effort on the part of the server. If you have to send e-mail to a large number of users, the wait might be intolerably long—or just annoyingly long, depending on your users and the task at hand.
Thus, for several years, developers have taken advantage of various "delayed jobs" mechanisms, making it possible to say, "Yes, I want to execute this functionality, but later on, in a separate thread or process from the handling of an HTTP request." Delaying the job in like this may well mean that it'll take longer for the work to be completed. But, no one will mind if the e-mail takes an additional 30 seconds to be sent. Users certainly will mind, by contrast, if it takes an additional 30 seconds to send an HTTP response to the users' browser. And in the world of the Web, users probably will not complain, but rather move on to another site.
This month, I explore the use of delayed jobs, taking a particular look at Sidekiq, a Ruby gem (and accompanying server) written by Mike Perham that provides this functionality using a different approach from some of its predecessors. If you're like me, you'll find that using background jobs is so natural and easy, it quickly becomes part of your day-to-day toolbox for creating Web applications—whether you're sending many e-mail messages, converting files from one format to another or producing large reports that may take time to process, background jobs are a great addition to your arsenal.
Before looking at Sidekiq in particular, let's consider what is necessary for background jobs to work, at least in an object-oriented language like Ruby. The basic idea is that you create a class with a single method, called "perform", that does what you want to execute. For example, you could do something like this:
class MailSender def perform(user) send_mail_to_user(user) end end
Assuming that the
send_mail_to_user method has been
defined in your
system, you can send e-mail with something like:
But here's the thing: you won't ever actually execute that code. Indeed, you won't ever create an instance of MailSender directly. Rather, you'll invoke a class method, something like this:
Notice the difference. Here, the class method takes the parameter that you eventually want to be passed to the "perform" method. But the "perform_async" class method instead stores the request on a queue. At some point in the future, a separate process (or thread) will review method calls that have been stored in the queue, executing them one by one, separately and without any connection to the HTTP requests.
Now, the first place you might consider queuing method classes that you'll want to execute would be in the database. Most modern Web applications use a database of some sort, and that would be a natural first thought. And indeed, in the Ruby world, there have been such gems as "delayed job" and "background job" that do indeed use the database as a queue.
The big problem with this technique, however, is that the queue doesn't need all of the functionality that a database can provide. You can get away with something smaller and lighter, without all the transactional and data-safety features. A second reason not to use the database is to split the load. If your Web application is working hard, you'll probably want to let the database be owned and used by the Web application, without distracting it with your queue.
So, it has become popular to use non-relational databases, aka NoSQL solutions, as queues for background jobs. One particularly popular choice is Redis, the super-fast, packed-with-functionality NoSQL store that works something like a souped-up memcached. The first job queue to use Redis in the Ruby world was Resque, which continues to be popular and effective.
But as applications have grown in size and scope, so too have the requirements for performance. Resque is certainly good enough for most purposes, but Sidekiq attempts to go one better. It also uses Redis as a back-end store, and it even uses the same storage format as Resque, so that you either can share a Redis instance between Resque and Sidekiq or transition from one to the other easily. But, the big difference is that Sidekiq uses threads, whereas Resque uses processes.
Senior Columnist, Linux Journal
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