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Quick Index Mapping and Field Options

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    When you create a Search index with Quick Mode in the Capella UI, you must set options for each field or type mapping you add to the index.

    You can create the following types of type mappings in Quick Mode:

    Indexing an entire collection in Quick Mode creates a dynamic type mapping for that collection. Indexing a field creates a static type mapping for the parent collection. For more information about static and dynamic type mappings, see Search Index Features.

    For more information about how to create a Search index with Quick Mode, see Create a Search Index in Quick Mode.

    Quick Collection Type Mapping Options

    Configure an entire collection in Quick Mode to add or remove all documents in that collection from your Search index.

    You can configure the following settings in Quick Mode for a type mapping that uses an entire collection:

    Option Description

    Index everything from collection: “$COLLECTION_NAME”

    You must select Index everything from collection to add a collection type mapping in Quick Mode.

    Index text fields as identifiers

    To index any Text type fields with the keyword analyzer, select Index text fields as identifiers.

    To use other analyzers or settings on text fields, clear Index text fields as identifiers.

    For more information about analyzers, see Search Index Features.

    Analyzer/Language

    Select the language for the content inside any Text fields.

    The Search Service automatically applies an analyzer to the field’s contents based on the selected language.

    For more information about the available language options, see Quick Mode Supported Languages.

    Quick Field Type Mapping Options

    Configure a single field in Quick Mode to add or remove it from your Search index.

    You can configure the following settings in Quick Mode for a type mapping that uses a single field:

    Option Description

    Index this field as an identifier (Text Fields Only)

    To index this field with the keyword analyzer, select Index this field as an identifier.

    To use other analyzers or settings on this text field, clear Index this field as an identifier.

    For more information about analyzers, see Search Index Features.

    Language (Text Fields Only)

    Select the language for the content inside a text field.

    The Search Service automatically applies an analyzer to the field’s contents based on the selected language.

    For more information about the available language options, see Quick Mode Supported Languages.

    Dimension (Vector Fields Only)

    For a vector child field, enter the total number of elements in the vector embedding array.

    Vector Search indexes can support arrays with up to 2048 elements. Arrays can be an array of arrays.

    For more information about Vector Search indexes, see Use Vector Search for AI Applications or Create a Vector Search Index in Quick Mode.

    Similarity Metric (Vector Fields Only)

    For a vector child field, choose the method to calculate the similarity between the vector embedding in a Vector Search index and the vector embedding in a Vector Search query.

    It’s recommended to choose the same similarity metric for your Search index as the one used in your embedding model.

    • dot_product: Calculated by adding the result of multiplying a vector’s components, or the product of the magnitudes of the vectors and the cosine of the angle between them. The dot product of 2 vectors is affected by the length and direction of each of the vectors, rather than just taking a straight-line distance.

      Dot product similarity is commonly used by Large Language Models (LLMs). Use dot_product to get the best results with an embedding model that uses dot product similarity.

    • l2_norm: Also known as Euclidean distance. Uses the straight-line distance between 2 vectors to calculate similarity. Smaller euclidean distances mean that the values of each coordinate in the vectors are closer together.

      It’s best to use l2_norm similarity when your embeddings contain information about the count or measure of specific things, and your embedding model uses the same similarity metric.

    For more information about Vector Search indexes, see Use Vector Search for AI Applications or Create a Vector Search Index in Quick Mode.

    Optimized For (Vector Fields Only)

    For a vector child field, choose whether the Search Service should prioritize recall or latency when returning similar vectors in search results:

    • recall: The Search Service prioritizes returning the most accurate result. This may increase resource usage for Search queries.

      The Search Service uses an nprobe value to calculate the number of centroids to search when using recall priority. This value is calculated by taking the square root of the number of centroids in the index.

    • latency: The Search Service prioritizes returning results with lower latency. This may reduce the accuracy of results.

      The Search Service uses half the nprobe value calculated for recall priority.

    For more information about Vector Search indexes, see Use Vector Search for AI Applications or Create a Vector Search Index in Quick Mode.

    Include in search results

    To include content from the field in search results, select Include in search results.

    To exclude the field’s content from search results, clear Include in search results.

    Support highlighting

    The Search Service can highlight matching search terms in search results from an index.

    To enable highlighting in search results, select Support highlighting.

    To turn off highlighting in search results, clear Support highlighting.

    To enable Support highlighting, you must also enable Include in search results.

    Support phrase matching

    To support searches for whole phrases, select Support phrase matching.

    To turn off phrase matching, clear Support phrase matching.

    Support field agnostic search

    To search the field’s contents without specifying the field name in a search query, select Support field agnostic search.

    To turn off field agnostic search, clear Support field agnostic search.

    Support sorting and faceting

    To sort search results and use facets with the field’s contents, select Support sorting and faceting.

    To turn off sorting and facets, clear Support sorting and faceting.

    Searchable As

    Set a different name that you can use to search the field’s contents in a query.

    The default value is the field’s name.