About this guide

This guide covers ElasticSearch search faceting capabilities and explains how Elastisch presents them in the API:

  • An overview of faceted search
  • How to perform queries with facets
  • Other topics related to facets

This work is licensed under a Creative Commons Attribution 3.0 Unported License (including images & stylesheets). The source is available on Github.

What version of Elastisch does this guide cover?

This guide covers Elastisch 2.2.x releases, including preview releases.


Faceted search (also called faceted navigation) is a feature that lets the user refine search results using data from faceted classification (categorization or labelling).

It is best demonstrated with an example from a real Web site (amazon.com):

Faceted Search Example

Here a search for "Information Retrieval" in the books section produces 993 results, 12 of which are displayed on the first page (clipped). The left hand side has a faceted navigation UI that lets us refine the query:

  • View only books released in the last 30 days
  • View only unreleased books
  • View results across deparments (in this case, Kindle Store has only one department to offer)
  • Filter out results that have a certain minimum average custom review rating

This feature is useful when dealing with large amounts of data that can be easily classified by different criteria: products in online stores, correspondence (emails), legal documents, geo and location data are just a few examples.

ElasticSearch lets you build faceted search for your applications using a feature commonly referred to as facets or faceting. Because facets are additional information to a query, ElasticSearch implements them as a feature piggiebacked on top of search queries: a few additional parameters are specified with a search query and ElasticSearch returns information relevant for building faceted navigation with the query response.

The field used for facet calculations must be of type numeric, date/time or be analyzed as a single token (see the Indexing guide on that). ElasticSearch supports multiple types of facets:

Next we will see how it works with Elastisch.

Performing Queries with Faceting

Facets piggyback on search queries and as such, performed with the clojurewerkz.elastisch.rest.document/search function discussed in the Querying guide.

With Elastisch, facet query structure is the same as described in the ElasticSearch documentation:

(require '[clojurewerkz.elastisch.rest.document :as doc])
(require '[clojurewerkz.elastisch.query         :as q])

(doc/search conn "articles" "article" :query (q/match-all) :facets {:tags {:terms {:field :tags}}})

You can give the facet a custom name (in this example, tags) and return multiple facets in a single request.

To retrieve the results, access the :facets key on the response (which is just a Clojure map with Elastisch). It will contain a map of facets:

{:tags {:_type "terms"
        :missing 0
        :total 26
        :other 6
        :terms [{:term "text" :count 2}
                {:term "technology" :count 2}
                {:term "software" :count 2}
                {:term "search" :count 2}
                {:term "opensource" :count 2}
                {:term "norteamérica" :count 2}
                {:term "lucene" :count 2}
                {:term "historia" :count 2}
                {:term "geografĂ­a" :count 2}
                {:term "full" :count 2}]}}

The exact structure will vary between different facet types.

Facet Scope

Facets can have scope. By default, facet computation is restricted to the scope of the current query (the so called main scope). It is possible to use global scope, in which case it will return values computed across all documents in the index:

(require '[clojurewerkz.elastisch.rest.document :as doc])
(require '[clojurewerkz.elastisch.query         :as q])

(doc/search conn "articles" "article" :query (q/query-string :query "T*") :facets {:tags {:terms {:field :tags} :global true}})

Different facets in a query can use different scopes if needed.

Facet Filters

All facets can be configured with an additional filter, which will reduce the documents they use for computing results. This is very similar in purpose to query filters:

  • You need to filter out some results
  • You need to narrow results to a particular account

Facet filters can, for example, help you make sure results only contain documents that belong to a particular user account or organization.

In the example below we use a filter to limit facets to articles published in a particular time period (range of years):

(require '[clojurewerkz.elastisch.rest.document :as doc])
(require '[clojurewerkz.elastisch.query         :as q])

(doc/search conn "articles" "article" :query (q/query-string :query "T*") :facets {:tags {:terms {:field :tags}
                                                                                   :facet_filter {:range {:year {:from 1990 :to 2012}}}}})

Different kinds of filters and their structure are described in the Querying guide. Their structure is the same for queries and facets.

Wrapping Up

Faceted search can be a very useful feature for . ElasticSearch has very good faceted search support with multiple kinds of facets, scoping and filtering. Facets support sits on top of search queries. With Elastisch facet requests have exactly the same structure as JSON in the ElasticSearch documentation.

The documentation is organized as a number of guides, covering different topics in depth:

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