# A Thinking Man's Sphinx

Today, we’ll explore the differences between UltraSphinx and ThinkingSphinx and why we chose to switch to ThinkingSphinx.

We’ve recently switched a number of projects to ThinkingSphinx here at Hashrocket. These projects were originally using SOLR or UltraSphinx. UltraSphinx is written by Evan Weaver. ThinkingSphinx is written by Pat Allan. They have some similarities: both use Sphinx (obviously); both are based on the underlying Ruby API for Sphinx, Riddle (also by Pat Allan); both have excellent documentation and well-written tutorials. The similarities pretty much end there, however, and the differences are far more interesting.

## Basic Sphinx Configuration

Both plugins help you generate a sphinx.conf file for your each of your rails environments, but they do it in drastically different ways. ThinkingSphinx lets you use a configuration format you are already used to at the expense of reduced configuration options. UltraSphinx is more flexible but less Rubyish.

### UltraSphinx

UltraSphinx generates the sphinx.conf file from a base configuration file. This base file uses the sphinx configuration syntax, passing it through ERB for some DRYness. A base file can be specified per-environment. It puts all of its configuration information in RAILS_ROOT/config/ultrasphinx/. This provides fine-grained - if rather tediously verbose - control over the multitude of Sphinx configuration options.

### ThinkingSphinx

ThinkingSphinx uses a YAML configuration file that it locates at RAILS_ROOT/config/sphinx.yml. It accepts a YAML hash of configuration settings. These settings allow you to specify most of the basic Sphinx configuration options with ease but you may be out of luck if the option you need isn’t available.

## Basic Index Configuration

Let’s start with a basic example of a sphinx index declaration. Keep in mind that your indexes will likely be significantly more complex in the real world.

### UltraSphinx

UltraSphinx uses a declarative is_indexed statement in the model that feels vaguely similar in style to an association or named scope declaration. This is the usage example given in the README:

This seems simple enough for such a simple case. We’ll see how it looks for less trivial cases.

### ThinkingSphinx

ThinkingSphinx, on the other hand, uses a define_index block in the model to allow the individual index configuration options to be stated declaratively. The canonical example from UltraSphinx would look like this in ThinkingSphinx:

The first thing you may notice is that the same index configuration is three lines in ThinkingSphinx instead of one in UltraSphinx. If you look closely, you’ll also see that the field names are not symbols as you might expect but method calls. We’ll get into why this is in a moment.

## Real World Index Configuration

Your real world applications are likely to require a significantly more complex index declaration to meet the search needs of your users. Let’s look at an example of such a real world Sphinx index declaration.

### UltraSphinx

Here’s an example of a more realistic UltraSphinx index configuration. This is the type of configuration you’re likely to use on any non-trivial project.

This is about as pretty as it’s going to get - and that’s not very pretty. Large, deeply nested hashes of arrays of hashes are not easily scannable and will become exponentially difficult to maintain as their size and complexity increases.

### ThinkingSphinx

Let’s look at that same example translated to ThinkingSphinx.

Not only did the number of lines decrease, the readability is far greater. I know which one I’d rather write. More importantly, I know which one I’d rather have to maintain weeks or months downline when it needs to be modified.

Notice that the declarations use methods rather than symbols. ThinkingSphinx uses some interesting metaprogramming to allow this. Notice also that indexed fields on associations are specified in the same way you would access that field. Simple.

Both UltraSphinx and ThinkingSphinx provide a number of rake tasks for common sphinx tasks such as generating the configuration file; generating the index; and starting, stopping, and restarting the searchd daemon. Both provide abbreviations for the more common task, such as ts:in for thinking_sphinx:index or us:conf for ultrasphinx:configure.

## Deployment and Configuration Management

Both UltraSphinx and ThinkingSphinx are pretty simple to deploy. You should symlink your configuration file from a shared location into your app’s path after deployment, just as you probably do for your database.yml file. You will probably want to run the configuration task after you update the code. Here, for instance, is a Capistrano task to run your ThinkingSphinx configuration task:

You’ll want to have this task run after each deployment:

You can create other tasks relatively easily for reindexing and managing the searchd daemon. I found a good guide to deploying a rails app with ThinkingSphinx linked from Pat Allan’s blog. I found a useful set of UltraSphinx capistrano tasks in Ruberion’s server tools plugin on Github. If you chose to host with EngineYard, they can manage either configuration for you with their pre-baked builds and deploy tasks.

## Real World Experience

We ran into a number of issues when setting up UltraSphinx:

• UltraSphinx loads your models without loading the full rails environment. This means that if your models depend on any of your lib files or any gems frozen in vendor/gems, you will have to require all of these files explicitly in each model. This is a pain.

• The fundamentally sound design and code of UltraSphinx are somewhat undermined by poorly implemented exception handling. This means that while most of the time things work swimmingly, when they fail you’re really sunk! The errors that you receive are often useless in diagnosing the actual problem.

• We had bugs in our index that only existed on our staging and production slices. These caused page counts to be incorrect and nil records to be returned in certain cases. In certain cases it also caused 5xx errors.

### Moving To ThinkingSphinx

After another Hashrocket team had success moving their project from SOLR to ThinkingSphinx, I decided to move our project as well. Moving to ThinkingSphinx proved to be a relatively painless experience. The process was essentially five-fold:

• Uninstall UltraSphinx and install ThinkingSphinx.
• Translate your is_indexed declaration into a @define_index@ block and change your search actions to use the ThinkingSphinx API.