Product Selector

Fusion 5.9
    Fusion 5.9

    Faceting

    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.

    Lucidworks offers free training to help you get started with Fusion. Check out the Configuring Range Facets quick learning, which focuses on how to group values into ranges for faceting:

    Configuring Range Facets

    Visit the LucidAcademy to see the full training catalog.

    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 Query Profile or with the Additional Query Parameters Stage in a Query Pipeline.

    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.

    SKU Product Color

    Sku11

    Prod1

    Red

    Sku12

    Prod1

    Blue

    Sku13

    Prod1

    Blue

    Sku14

    Prod1

    Blue

    Sku21

    Prod2

    Red

    Sku22

    Prod2

    Blue

    Sku23

    Prod2

    Green

    Sku24

    Prod2

    Green

    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

    https://lucidworks.com/post/pivot-facets-inside-and-out/

    https://lucidworks.com/post/apache-solr-statistics/

    https://lucidworks.com/post/pivoting-to-the-query-using-pivot-facets-to-build-a-multi-field-suggester/

    Lucidworks offers free training to help you get started with Fusion. Check out the Faceting course, which focuses on how to use facets to ensure faster, smarter search results:

    Faceting

    Visit the LucidAcademy to see the full training catalog.