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Area: Episerver Find Applies to versions: 12 and higher
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Term facets

Facets are used for grouping documents based on some criteria, for example specific terms or date range. This topic explains how facets based on terms are used in Episerver Find.

How it works

Term facets group terms, words, or whole strings, and provide a count for each. To retrieve a term facet using the fluent API, use the TermsFacetFor and TermsFacetForWordsIn methods.

  • The TermsFacetFor method works on exact values in strings in a case sensitive manner. So, "Foo", "foo," and "foo bar" are treated as three different terms.
  • The TermsFacetForWordsIn method works on analyzed values of strings in a case insensitive manner. So, it treats each word in a string a separate term. With this method "Foo", "foo," and "foo bar" are treated as two terms, "foo" and "bar".

Both methods work on values of type string and IEnumerable of string. Also, both have an overload that lets you specify the number of terms to return. Unless specified, 10 is the default number of items returned for a facetTo return more items, use x.Size as in the example below.

Examples

Before providing examples, we need to provide a context. Assume there is a class with a string property, a list of strings property, and a property of a complex type that also has a string property.

Assume you indexed three instances of this class with the following values:

TitleTagsAuthor.Name
Ten Little Indians crime, fiction Agatha Christie
The Origin of Species science Charles Darwin
David Copperfield scifi, fiction Charles Dickens

Retrieving a tag cloud

Use the TermsFacetFor method to retrieve a list of the most common tags in a search request.

Note: Use the Take method to exclude actual search results, since you are not interested in them in this scenario.

After getting the search results, you can extract the terms facet for the tags.

The above code prints:
fiction: 2
crime: 1
science: 1
scifi: 1

Grouping authors

If you modify the code to instead retrieve a terms facet for author name, the code would look like this.

The above code prints:
Agatha Christie: 1
Charles Darwin: 1
Charles Dickens: 1

Grouping by single words

In contrast, if you used the TermsFacetForWordsIn method (instead of the TermsFacetFor method) in the above code, it prints:
charles: 2
agatha: 1
christie: 1
darwin: 1
dickens: 1

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