Indexes: Term Vectors

Indexes that include term vectors can be created and configured using the API or Studio.

Using the API

To create an index and enable Term Vectors on a specific field, we can -

A. Create an index using the AbstractIndexCreationTask, and specify the term vectors there.
B. Or, we can define our term vectors in the IndexDefinition (directly or using the IndexDefinitionBuilder).

public class BlogPosts_ByTagsAndContent : AbstractIndexCreationTask<BlogPost>
{
    public BlogPosts_ByTagsAndContent()
    {
        Map = users => from doc in users
                       select new
                       {
                           doc.Tags,
                           doc.Content
                       };

        Indexes.Add(x => x.Content, FieldIndexing.Search);
        TermVectors.Add(x => x.Content, FieldTermVector.WithPositionsAndOffsets);
    }
}

IndexDefinitionBuilder<BlogPost> indexDefinitionBuilder =
    new IndexDefinitionBuilder<BlogPost>("BlogPosts/ByTagsAndContent")
    {
        Map = users => from doc in users
                       select new
                       {
                           doc.Tags,
                           doc.Content
                       },
        Indexes =
        {
            { x => x.Content, FieldIndexing.Search }
        },
        TermVectors =
        {
            { x => x.Content, FieldTermVector.WithPositionsAndOffsets }
        }
    };

IndexDefinition indexDefinition = indexDefinitionBuilder
    .ToIndexDefinition(store.Conventions);

store.Maintenance.Send(new PutIndexesOperation(indexDefinition));

Available Term Vector options include:

public enum FieldTermVector
{
    /// <summary>
    /// Do not store term vectors
    /// </summary>
    No,

    /// <summary>
    /// Store the term vectors of each document. A term vector is a list of the document's
    /// terms and their number of occurrences in that document.
    /// </summary>
    Yes,

    /// <summary>
    /// Store the term vector + token position information
    /// </summary>
    WithPositions,

    /// <summary>
    /// Store the term vector + Token offset information
    /// </summary>
    WithOffsets,

    /// <summary>
    /// Store the term vector + Token position and offset information
    /// </summary>
    WithPositionsAndOffsets
}

Learn which Lucene API methods and constants are available here.

Using Studio

Let's use as an example one of Studio's sample indexes, Product/Search, that has term vector enabled on its Name field so a feature like MoreLikeThis can use this fiels to select a product and find products similar to it.

Term vector enabled on index field

We can now use a query like:

from index 'Product/Search' 
where morelikethis(id() = 'products/7-A')