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Run a Search With a Search Index

  • concept
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    Run a Search query to search and return the contents of a Search index.

    If you use the default search result sorting of _score, a document’s score determines where it appears in your search results.

    You must create a Search index before you can run a search with the Search Service.

    You can run a search against a Search index with:

    To run a Search query against multiple Search indexes at once, Create a Search Index Alias with the Web Console.

    Scoring for Search Queries

    To determine a document’s score in search results, the Search Service uses the tf-idf algorithm. tf-idf increases the score of a document based on term frequency, or the number of times a term appears in a document divided by the total number of terms in the document. It penalizes document frequency, or how often a term appears across all documents.

    The tf-idf score is calculated at a partition level in a Search index.

    The Search Service uses tf-idf to calculate the hit score for a document, multiplied by any boost parameters applied to each query inside the query object:

    hit_score = (query_1_boost * query_1_hit_score) + (query_2_boost * query_2_hit_score)

    If one of your Search queries is a Vector Search query, the calculation changes to:

    hit_score = (query_1_boost * query_1_hit_score) + (knn_boost * knn_distance)

    When running a hybrid search with the Server Web Console or REST API, the Search Service displays results as a disjunct (OR) between your regular Search and Vector Search queries.

    When running a hybrid Search query, you should add a boost value to your regular Search query to level the tf-idf score with the knn distance. Otherwise, you might see unexpected search results. This is because of the differences in the scoring algorithms between the 2 query types.

    Run a Search with the Server Web Console

    You can use the Server Web Console to test your Search index before you integrate search into your application.

    You can enter a basic search query in the Server Web Console, or use a query object and other JSON properties for a more complex search.

    For more information about how to run a search with the Server Web Console, see Run A Simple Search with the Web Console.

    For more information about how to configure a Search index and search for geospatial data, see Run a Geospatial Search Query with the Web Console.

    Run a Search with the REST API

    You can also use the REST API, curl, and HTTP to run a search.

    Use a Search request JSON payload to control how the Search Service returns results.

    For more information about how to run a search with the REST API, see Run a Simple Search with the REST API and curl/HTTP.

    For more information about how to configure a Search index and search for geospatial data, see Run a Geospatial Search Query with the REST API and curl/HTTP.

    Run a Search with a SQL++ Query

    Use the Query tab to search using natural-language search and SQL++ features in the same query.

    When using SQL++ with a hybrid Vector Search query, you have more flexibility in how you choose to display your search results. When running a hybrid search with the Server Web Console or REST API, the Search Service displays results as a disjunct (OR) between your 2 search queries. For example:

    {
    "query":
    {
        "match_phrase": "my regular query"
    }
}

OR

{
    "knn": [
        "k": 5,
        "field": "vector_field",
        "vector": [0, 0, 128]
    ]
}

    SQL++ allows you to choose whether to return search results as a conjunct (AND) or a disjunct (OR) between for hybrid search queries.

    As a conjunct, the Search Service:

    • Returns matches that score highly for both the regular Search query and the Vector Search query.

    • Excludes matches that only match the Vector Search query.

    For example:

    SELECT meta().id FROM <key_space>
WHERE text = "content"
AND SEARCH(<key_space>, {"query": {"match": "content", "field": "text"}, "knn": {"vector": <vector_embedding>", "field": "vector_field", "k": 5}});

    As a disjunct, the Search Service:

    • Returns matches for the regular Search query, followed by matches for the Vector Search query.

    As a result, you could see matches for the Vector Search query that do not contain matches for the regular Search query.

    For example:

    SELECT meta().id FROM <key_space>
WHERE SEARCH (<key_space>, {"query": {"match": "content", "field": "text"}, "knn": {"vector": <vector_embedding>", "field": "vector_field", "k": 5}});

    For more information about how to use the Search Service from a SQL++ query, see Search Functions.

    See Also