Full Text Search (FTS)

    +

    Unresolved include directive in modules/howtos/pages/full-text-searching-with-sdk.adoc - include::partial$attributes.adoc[]

    You can use the Full Text Search service (FTS) to create queryable full-text indexes in Couchbase Server.

    Full Text Search or FTS allows you to create, manage, and query full text indexes on JSON documents stored in Couchbase buckets. It uses natural language processing for querying documents, provides relevance scoring on the results of your queries, and has fast indexes for querying a wide range of possible text searches. Some of the supported query types include simple queries like Match and Term queries; range queries like Date Range and Numeric Range; and compound queries for conjunctions, disjunctions, and/or boolean queries. The Scala SDK exposes an API for performing FTS queries which abstracts some of the complexity of using the underlying REST API.

    Examples

    The examples below use these imports:

    import com.couchbase.client.scala._
    import com.couchbase.client.scala.json.JsonObject
    import com.couchbase.client.scala.kv.MutationState
    import com.couchbase.client.scala.search.{SearchOptions, SearchScanConsistency}
    import com.couchbase.client.scala.search.queries.MatchQuery
    import com.couchbase.client.scala.search.result.{SearchResult, SearchRow}
    
    import scala.util.{Failure, Success, Try}

    Search queries are executed at Cluster level (not bucket or collection). Here is a simple MatchQuery that looks for the text “swanky” using a defined index:

    val result: Try[SearchResult] = cluster.searchQuery("travel-sample-index-hotel-description",
      MatchQuery("swanky"),
      SearchOptions().limit(10))
    
    result match {
      case Success(res) =>
        val rows: Seq[SearchRow] = res.rows
        // handle rows
      case Failure(err) => println(s"Failure: ${err}")
    }

    All simple query types are created in the same manner. Some have additional properties, which can be seen in common query type descriptions. Couchbase FTS’s range of query types enable powerful searching using multiple options, to ensure results are just within the range wanted.

    Working with Results

    The result of a search query has three components: rows, facets, and metadata. Rows are the documents that match the query. Facets allow the aggregation of information collected on a particular result set. Metadata holds additional information not directly related to your query, such as total rows and how long the query took to execute in the cluster.

    val result: Try[SearchResult] = cluster.searchQuery("travel-sample-index-hotel-description",
      MatchQuery("swanky"),
      SearchOptions().limit(10))
    
    result match {
      case Success(res) =>
    
        // Rows
        res.rows.foreach(row => {
          val id: String = row.id
          val score: Double = row.score
          // ...
        })
    
        // MetaData
        val maxScore: Double = res.metaData.metrics.maxScore
        val successCount: Long = res.metaData.metrics.successPartitionCount
    
      case Failure(err) => println(s"Failure: ${err}")
    }

    Consistency

    Like the Couchbase Query Service, FTS allows provides optional Read-Your-Own-Writes (RYOW) consistency, ensuring results contain information from updated indexes:

    collection.insert("newHotel",
      JsonObject("name" -> "Hotel California", "desc" -> "Such a lonely place")) match {
    
      case Success(upsertResult) =>
        upsertResult.mutationToken.foreach(mutationToken => {
    
          val ms = MutationState(Seq(mutationToken))
    
          // Will wait until the the index contains the specified mutation
          val result = cluster.searchQuery(
            "travel-sample-index-hotel-description",
            MatchQuery("lonely"),
            SearchOptions()
              .limit(10)
              .scanConsistency(SearchScanConsistency.ConsistentWith(ms))
          )
        })
    
      case Failure(err) => println(s"Failure: ${err}")
    }