Elasticsearch with Rails and Tire

I’ve recently had the chance and excuse to play with Elasticsearch, after reading good things about it. We’ve been using Solr with decent success, but it feels like whenever we try to do anything outside the normal index-and-search it’s more complicated than it should be. The basics are easy thanks to the terrific Sunspot gem, though. So when I had a small project to prototype that involved indexing PDFs as well as database records, I figured it was a good opportunity to try out Elasticsearch.

I quickly reached for the Tire gem, which is very similar to Sunspot if you’re using ActiveRecord. Where Sunspot has you include a “searchable” block, Tire adds a “mapping” block, but the idea is the same — that’s where you tell it what fields to index, and how to do it. For each field you can adjust the data type, boost, and more. You can also tack on a “settings” block to adjust things like the analyzers.

The documentation for Tire is pretty good, but I found that I made a number of mistakes trying to adapt the instructions on the Elasticsearch site to the Tire way of doing things, so I thought I’d write up some of the things I learned in hopes that it can help save time for others. Many thanks to the folks on StackOverflow who answered my questions and pointed me in the right direction.

One starter suggestion is to configure Tire’s debugger, which is really convenient because it will output the request being sent to the ES server as a curl command that you can copy and paste into a terminal for testing. Very handy. I added this to my config/environments/development.rb file:

  Tire.configure do
    logger STDERR, :level => 'debug'
  end

Now on to the model. I’ll call mine Publication, so inside app/models/publication.rb:

class Publication < ActiveRecord::Base
  include Tire::Model::Search
  include Tire::Model::Callbacks

  attr_accessible :title, :isbn, :authors, :abstract, :pub_date

  settings :analysis => {
    :filter  => {
      :ngram_filter => {
        :type => "nGram",
        :min_gram => 2,
        :max_gram => 12
      }
    },
    :analyzer => {
      :index_ngram_analyzer => {
        :type  => "custom",
        :tokenizer  => "standard",
        :filter  => ["lowercase", "ngram_filter"]
      },
      :search_ngram_analyzer => {
        :type  => "custom",
        :tokenizer  => "standard",
        :filter  => ["standard", "lowercase", "ngram_filter"]
      }
    }
  } do
    mapping :_source => { :excludes => ['attachment'] } do
      indexes :id, :type => 'integer'
      indexes :isbn
      [:title, :abstract].each do |attribute|
        indexes attribute, :type => 'string', :index_analyzer => 'index_ngram_analyzer', :search_analyzer => 'search_ngram_analyzer'
      end
      indexes :authors
      indexes :pub_date, :type => 'date'
      indexes :attachment, :type => 'attachment'
    end
  end

  def to_indexed_json
    to_json(:methods => [:attachment])
  end

  def attachment
    if isbn.present?
      path_to_pdf = "/Users/foobar/Documents/docs/#{isbn}.pdf"
      Base64.encode64(open(path_to_pdf) { |pdf| pdf.read })
    end
  end
end

Okay, that’s a lot of code, so let’s look things over bit by bit. Naturally the includes at the top are needed to mix-in the Tire methods. There are two includes so that you can include the calls needed for searching without the callbacks if you don’t need them. The callbacks, though, are what make things work auto-magically when you persist ActiveRecord objects. With those, whenever you call save() on an AR model, the object will be indexed into ES for you.

Next up are two blocks of code: settings, and mapping. The settings block defines a filter, and two analyzers, one for indexing and one for searching. I can’t claim to be enough of an expert yet to fully explain the ramifications of the filter/analyzer options, so rather than risk confusion I’ll just note that this code is there to set up the nGram filter and connect it with two analyzers, index and search, which differ slightly in order to ensure that the standard filter is included for searching. You may want to play with the nGram’s min and max settings to get the matching behavior you want. Note that if you don’t need the nGram filter, you can remove the settings block and let the mapping block stand on its own, in which case the default settings will be used (but you’ll have to change the mapping entry for the :title and :abstract fields, as described below).

The mapping block is the more interesting one, as it defines the fields and indexing behavior. The first line took me some searching and StackOverflow questioning to figure out. The issue that by default, Elasticsearch will put all of the fields you index into its _source storage. Because I’m indexing large PDF documents, the result was that a huge Base64-encoded field was being stored. If I wanted to serve the PDFs out of Elasticsearch that might be okay, but that’s not the plan. The :excludes instruction prevents the attachment field from being stored.

Next are the fields themselves, and I won’t spend much time on these because the Tire documentation does a fine job of explaining these. The only interesting items are the :attachment field and the entry for :title and :abstract — that one specifies that for those fields the custom analyzers defined in the settings block should be used. For :attachment it gets a little bit tricky.

When the indexing is performed, the fields themselves are gathered up by calling the method to_indexed_json(). Normally that will just do a to_json() on your model and then collect the fields. But you can also override it, which we do here. You can see that we add in the method attachment(), which is defined below. So the other fields will be JSONized as normal, as well as the output of the attachment() method. The attachment() method itself uses the ISBN number to open the PDF file, which is read and Base64-encoded. The results of that encoding will be included with the other fields and sent to ES for indexing.

Performing the searching is almost too easy, but there was one bit that threw me off initially, which was getting highlighting to work. The search block in my controller looks like this:

results = Publication.search do
  query { string query_string }
  sort { by :pub_date, 'desc' }
  highlight :title, :options => { :tag => "<strong class='highlight'>" }
end

I was trying to test the highlighting and was thrown off by the field names being case-sensitive (see my question on StackOverflow), but this now works. The other key is that the highlighted fields are returned separately from the plain fields, which was odd to see. This means that to display the highlighting I have to check for the field:

results.each do |r|
  r_title = (r.highlight.nil? ? r.title : r.highlight.title[0])
  puts "Title: #{r_title}"
end

If the highlighting is present then it’s used; if not (because the term isn’t present in that field) then the regular field is used. The other handy thing to note is that you can specify the tag with which to wrap the term. The default is “<em>” but I wanted to specify the “highlight” CSS class, as is shown here. This is a really convenient feature.

That covers the basics, though it’s also probably worth sharing just how nice it is to be able to test using curl. For example, I wanted to check how easy it is to have the search call return just a single field (to speed up certain requests), so I tried it first in curl:

curl -XPOST http://localhost:9200/publications/_search\?pretty\=true -d '{
"query": {"query_string": {"query": "Foobar"}},
"fields": ["title"]
}'

That’s of course assuming that ES is running on your local system on port 9200; if not, adjust accordingly.

There you go. I hope this writeup is helpful to folks getting started and it saves you some time.

• elasticsearch
• rails
• search
• tire