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Faceted Results Faceting is the name given to a set of computed counts over a search result returned together with the documents which match the search query. Facets are most often used to create additional navigational controls on the search results page or panel. Users can expand and restrict their search criteria in a natural way, without having to construct complicated queries. For example, popular e-commerce facets include product category, price range, availability, and user ratings. Fusion leverages Solr’s Faceting search components.

Field faceting

In Solr the most straightforward kind of faceting is field faceting, in which Solr’s FacetComponent computes the top values for a field and returns the list of those values along with a count of the subset of documents in the search results which match that term. Field faceting works best over fields which contain a single label or set of labels from a finite, controlled lexicon such as product category. Fusion’s Facet Query Stage can be used to configure field faceting as part of the search query pipeline.

Range faceting

Range facets are used for fields which contain date or number values. Values can be grouped into ranges by specifying additional query parameters. To configure range faceting, use the Additional Query Parameters Stage to specify Solr range faceting parameters.
LucidAcademyLucidworks offers free training to help you get started.The Quick Learning for Configuring Range Facets focuses on how to group values into ranges for faceting:
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JSON faceting

In eCommerce, one product often contains multiple SKUs. In this case, it’s ideal to group search results on the product ID, such that only one result for all SKUs of a given product will be returned. This is achieved by using the unique parameter in JSON facets. You can use JSON facets by creating Query Params in a Create a Query Profile or with the Additional Query Parameters Stage in a Query Pipeline. Configure facets with a JSON script in your query pipeline. Facets that come from Rules must be converted in code to JSON facets. they cannot be passed through as name/value params. You can use the Additional Query Parameters stage when a JSON facet is hardcoded in the pipeline as a static json.facet string.
  1. In the Fusion workspace, navigate to Querying > Query Profiles.
  2. Click New. The Add Query Profile panel appears:
Add Query Profile
  1. Enter a search mode to use with this profile.
    • dsl (Domain Specific Language) uses expressive search queries and responses via a structured, modern JSON format.
    • legacy primarily uses Solr parameters. See the Solr Query Language cheat sheet.
    • all uses both DSL and legacy search modes. This is the default value. The default value of all works well for most use cases.
      The Search Mode field is available for Fusion 5.4.x and later.
  2. Enter a Query Profile ID.
  3. Select a query pipeline to associate with this profile.
  4. Enter a Solr search handler to use with this profile. The default of select works well for most use cases.
  5. Select a collection to associate with this profile.
  6. Optionally, click New params… to enter Solr request parameters to add to the request URL when submitting queries using this profile.
  7. Optionally, select Enable experimentation to configure this profile for use with experiments.
    1. Select the percentage of experiment traffic to direct to this profile.
    2. Select the experiment to associate with this profile, or select Add Experiment to configure a new one.
  8. Click Save.
The query profile window displays the request URL for sending queries to this profile.
LucidAcademyLucidworks offers free training to help you get started.The Course for Index and Query Profiles focuses on how index and query profiles operate, and how to configure and manage them:
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JSON faceting example

For example, if a product is available in SKUs of multiple colors, the following should apply:
  1. All available colors (in any SKU in the result set) are represented in the facets
  2. The count for those facets reflects matching product counts, not SKU counts.
In this example, eight SKU records are used across two products.
SKUProductColor
Sku11Prod1Red
Sku12Prod1Blue
Sku13Prod1Blue
Sku14Prod1Blue
Sku21Prod2Red
Sku22Prod2Blue
Sku23Prod2Green
Sku24Prod2Green
With the preceding data, the color facet should show:
Color:
Red (2)
Blue (2)
Green (1)

Facet stats

The Stats component is useful for computing statistics against fields within your document set. For example, when performing a query, you can invoke the Stats component to return information about the mean price of a product or determine how many documents are missing a particular field.

Facet stats example

https://FUSION_HOST:FUSION_PORT/api/apps/exampleapp/query/examplepipeline/select?q=Cooking&stats=true&stats.field=price
  ...
  "stats":{
    "stats_fields":{
      "price":{
        "min":12.34,
        "max":57.65,
        "mean":34.56,
        ...

Faceting concepts

Key Facet Concepts:
  • Term: A specific value from a field.
  • Limit: The maximum number of terms to be returned.
  • Offset: The number of top facet values to skip in the response (just like paging through search results and choosing an offset of 51 to start on page 2 when showing 50 results per page).
  • Sort: The order in which to list facet values: count ordering is by documents per term, descending, and index ordering is sorted on term values themselves.
  • Missing: The number of documents in the results set which have no value for the facet field.
  • Choice of facet method (advanced): Specify Solr algorithm used to calculate facet counts. (See Facet Method Configuration for details).
    One of:
    • enum. Small number of distinct categories.
    • fc (“field cache”). Many different values in the field, each document has low number of values, multi-valued field.
    • fcs (“single value string fields”). Good for rapidly changing indexes.

Additional resources

LucidAcademyLucidworks offers free training to help you get started.The Course for Faceting focuses on how to use facets to ensure faster, smarter search results:
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