After a bit of background on the mainframe, mini, server, desktop progression, Guiseppe introduced the space that Gearman operates in: distributed heterogenous system (like the web). Amongst Gearman’s peers in the space (not to say that they fill the same role 2at all) is memcached.

Gearman is a client/server system for distributing jobs from clients to a number of workers. Guiseppe drew an analogy to a manager in a company: the manager gets a request from a customer, delegates it to one or more employees, and hands the result back to the client (monitoring progress along the way and assigning the job to new employee/s if the current ones are, e.g., hit by a bus).

The Gearman server fills the role of the manager: it accepts connections from clients and one or more workers (which can be local to the server or on other hosts). The Gearman server is responsible for then farming the jobs submitted by the clients out to appropriate worker/s for execution.

There are a numerous ways that this can be useful. It can help to decouple applications and features from each other. Rather than re-writing existing components for use in projects in another language or on a different platform, you can use Gearman to mediate the invocation of the existing code from the new system. Similarly, you can use it to offload computationally intensive tasks to more capable systems.

Using Gearman is reasonably simple: the gearmand server is written in C and there are client libraries available for, according to Guiseppe, “everything that counts”: C/C++, PHP, Python, etc. You just start a server, start one or more workers, and then use one (or more) of the available client libraries to submit jobs.

# Start a server
PORT=1234
gearmand -d -v -p $PORT

# Start a worker
gearman -p $PORT -f count_lines -- wc -l

# Submit a job
gearman -p $PORT -h localhost -f count_lines < /etc/passwd

The above code starts a Gearman server, starts a worker that can compute the count_lines function (by running wc -l on its input), and submits a job.

There are some rather more complex uses. One of those that Guiseppe mentioned is using the client in user defined functions in a relational database server (he used MySQL, but PostgreSQL is also supported). With appropriate jobs and workers this can be used to retrieve status information from, e.g., MySQL slave servers and store it in a database on the master (which will then be replicated to the slaves giving all nodes knowledge of the health of the whole cluster).

To help avoid introducing a single point of failure, you can deploy multiple servers and use all of them: if one fails, then clients and workers will try the next. It wasn’t clear, though, if the client libraries do this sensibly (re-submitting jobs, etc.)

For more information, your first stop should probably be the official Gearman web-site. There are also a number of posts on Guiseppe’s blog.